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Continued Confinement of Those Most Vulnerable to COVID-19

Suerie Moon, Eva Maria Belser, Claudine Burton-Jeangros, Pascal Mahon, Cornelia Hummel, Settimio Monteverde, Tanja Krones, Stéphanie Dagron, Cécile Bensimon, Bianca Schaffert, Alexander Trechsel, Luca Chiapperino, Laure Kloetzer, Tania Zittoun, Ralf Jox, Marion Fischer, Anne Dalle Ave, Peter G. Kirchschlaeger, and Samia Hurst

[This is an advance copy of an article that will appear in print in September 2020 as part of the KIEJ’s special double issue on Ethics, Pandemics, and COVID-19.]

ABSTRACT. Countries deciding on deconfinement measures after their initial lockdowns in response to the COVID-19 pandemic often include, as a matter of course, the continued confinement of those most vulnerable to the disease in these plans. Such continued confinement, however, is neither innocuous nor obviously justified. In this paper, we systematically examine issues such as: the requirements to sustain and protect vulnerable persons, the situation in institutions, legal implications of confinement, and the role of self-determination. Based on this exploration, we recommend that continued confinement cannot be the only measure in place to protect vulnerable persons. Protections are needed to enable the participation in the public sphere and the exercise of rights for persons particularly vulnerable to fatal courses of COVID-19. The situation in long-term care homes warrants particular caution and in some cases immediate mitigation of lockdown measures that have isolated residents from their caregivers, advocates, and proxies. Vulnerable persons should retain the choice to place themselves at risk, as long as they do not impose risks on others. Vulnerable persons who choose to remain in confinement should be protected against loss of their jobs or income, and against the risk of discrimination in the labor market. Associations and lobbies representing the views of groups of those particularly vulnerable to COVID-19 should be consulted and involved in outlining deconfinement measures. Moreover, most vulnerable persons are autonomous and competent and should be allowed to voice their own opinion.

INTRODUCTION

Continued confinement of those most vulnerable to COVID-19—e.g., the elderly, those with chronic diseases and other risk factors—is presented as an uncontroversial measure when planning exit strategies from lockdown measures. Policies for deconfinement assume that these persons will remain confined even when others will not (see, for example, European Commission 2020). This, however, could last quite a long time, and for some this could mean that they will remain in confinement for the rest of their lives.

In a policy brief on the ethical, legal, and social issues of transition strategies, the Swiss National COVID-19 Science Task Force stated that:

Specific interventions should target the risks associated with isolation and immobilization in the >65 population: put in place “safe spaces” for the elderly (clubs, gym classes, walks); support local shopping options, without queueing, or maintain provision by volunteers while allowing some contacts (move away from the zero contact of dropping bags behind a door and no interactions between volunteers and elderly people); allow older persons who are willing to take the risk of becoming infected to not quarantine themselves from persons in low-risk groups (for example grandchildren). (Swiss National COVID-19 Science Task Force 2020)

When discussing the option of continued confinement of those at particular risk of morbidity and mortality from COVID-19, the elderly (i.e., those over sixty-five) and those with chronic conditions and/or multimorbidity are the usual target groups that are now largely understood to be (medically) vulnerable. Defining entire categories to determine who is vulnerable, and determining public policy based on these categories, is, however, problematic. Considering all people aged over sixty-five, for example, as vulnerable is simplistic. Social scientists have regretted that it has long been assumed that those over sixty-five represent a homogeneous category. People over sixty-five, however, represent a very heterogeneous category, with varying socioeconomic statuses, family circumstances, and health conditions. The distinction between three global health statuses—independent, frail, dependent (Spini et al. 2007; Lalive d’Epinay and Spini 2008)—has been coined to underline the heterogeneity of the so called 65+ category and the multiplicity of health trajectories therein (Spini et al. 2016). The same consideration applies to persons with pre-existing conditions placing them at differential risk of dying should they contract COVID-19. Protections need to take this heterogeneity into account.

From a legal standpoint, a strict age criterion for continued confinement is problematic as well. According to many national constitutions (and international law), age discrimination is prohibited. Strict age limits can only be ethically and legally permissible if they are based on highly convincing reasons (e.g., adulthood as a condition for marriage). The fact that health risks generally tend to increase at the age of sixty-five is insufficient to apply strict age limits. Healthy sixty-six-year-old people cannot be bound by the same legal rules as people with multiple additional risk factors without violating the principle of equality. People have a right to be treated equally if they are equal regarding the matters at stake, and they have a right to differentiated treatment if there are relevant differences. Furthermore, the diseases bringing people into the group of “vulnerable people” must also be clarified. Current lists tend to be vague and explicitly not exhaustive. Here again, further differentiation is crucial.

While the protection of those most vulnerable to morbidity and mortality from COVID-19 is a duty, we content that it is far from obvious that this duty requires continued confinement. Moreover, confinement alone cannot provide such protection. In this paper, we explore what such protection requires, outline legal implications, and sketch some practical implications in our conclusion.

REASONS FOR THE CONTINUED CONFINEMENT OF THE VULNERABLE

Four reasons can be put forward to maintain confinement of those particularly vulnerable to morbidity and mortality from COVID-19: (1) protecting them as equally worthy of life in a situation where their life is more at risk; (2) preventing health system shortages; (3) protecting others in case the particularly vulnerable are also particularly likely to pass on the disease to others; and (4) protecting others from the risk of complicity in making those most vulnerable more likely to become ill, and thus risk severe disease and death.

Regarding the first reason, protection of vulnerable persons themselves cannot justify compelled confinement if they are the ones at risk. They should have the right to protection, but should be able to choose freely whether or not to place themselves at risk. State authorities are prohibited from discrimination and are obliged to take active measures to reduce inequalities. Persons with a high risk of morbidity or mortality from COVID-19 have a right to be provided access to special protection. Whether state authorities may limit their rights and freedoms in order to protect them is an entirely different question. Protecting people against their free and informed choices is not justified from a human rights perspective. The rights of vulnerable people may thus only be limited to protect the health system or other human rights holders, such as caregivers.

Regarding the second reason, vulnerable people are more likely to need special or even intensive care. Should there be a shortage of such care, this would indeed provide a prima facie reason to confine those who are most likely to be in need of it more strictly. This justification exists when intensive care structures are at risk of becoming overwhelmed, but ceases to exist when case numbers are sufficiently controlled to avoid this.

Regarding the third reason, it must first be noted that no evidence currently points to a heightened risk of contagion on the part of those most vulnerable to morbidity and mortality from COVID-19 as compared to other population groups. While their risk of becoming seriously ill or dying is increased in case of illness, their risk of becoming infected with the virus does not seem higher than that of others (NCPERET 2020). An exception exists in long-term care institutions, where the number of people living in close quarters could pose a risk and this could justify continued confinement, provided it were expected to protect other residents. Outside long-term care facilities, continued confinement may still protect healthcare professionals, since increasing the number of COVID-19 cases in hospitals would increase their risk of infection, even if structures are not at risk of being overwhelmed. This may be particularly true in the case of those most vulnerable to COVID-19, since other groups would be less likely to require hospitalization when ill and thus less likely to become a risk for healthcare providers. However, this argument is not specific to those most vulnerable to COVID-19: it would also apply, albeit with lesser weight, to anyone at risk of becoming ill and requiring hospitalization. Where personal protective equipment is available, however, this risk to health professionals can be mitigated (Jefferson et al. 2020).

Finally, if those most vulnerable to morbidity and mortality from COVID-19 are not confined, it could make the rest of us very likely to be complicit in increasing their risk of becoming ill. Avoiding such complicity in the absence of confinement could significantly change what is allowed for the rest of us. It could mean that barrier measures, such as wearing masks, performing hand hygiene, and maintaining six-feet’s distance, could remain required in public spaces for much longer in order to limit the risk of contagion to particularly vulnerable individuals who may be there. It could also mean that we should all limit close contacts to as few persons as possible to decrease the overall risk of viral circulation and thus, again, protect particularly vulnerable individuals in the public sphere. In this case, we may have to forgo the services of hairdressers, for example, avoid parties where people mingle and distances are more difficult to keep, or going to restaurants or nightclubs, where masks would interfere with some of our central reasons to be there. Continued confinement of those most vulnerable to COVID-19 would thus protect the rights of others to access a greater part of the components of life while COVID-19 is still in circulation.

None of these justifications, however, is sufficient on its own to justify continued confinement. Rather, when they are pertinent, they must be taken into account and balanced against the rights of the vulnerable to everything that confinement takes away from them.

PROTECTING THE VULNERABLE

Confinements and lockdowns are commonly accepted anti-pandemic measures on the basis of their effectiveness in protecting life and health (Thunstrom et al. 2020; Zhang et al. 2020; Douglas et al. 2020), and in particular for those who are more vulnerable to serious illness and death. Consistent concern for the protection of life and health for those who are vulnerable cannot be limited to confinement, however. Special accommodations also need to be made for vulnerable individuals during court and administrative procedures, including asylum procedures—where their presence is required, other protections must be provided. Similarly, protective refuge should be available for their family members who become ill with COVID-19 and do not require hospitalization, in order to avoid the risk of contagion within the home for these persons. Vulnerable persons should also be considered for early release from prison, as the risks of contagion are greater there. When protective measures, such as masks, are recommended, they should be free of charge. As the elderly may place themselves at risk if they take care of their grandchildren, free access to childcare for parents should also be part of an overall protection strategy, and this should be the case for all on equity grounds. Those who are vulnerable are also listed by the Swiss pandemic plan among the populations that should receive priority for a vaccine once it becomes available (SFOPH 2018). Protection should not be a privilege dependent on income for vulnerable persons, but a right.

Risks are also associated with confinement itself. Early signs of the adverse effects of confinement are being observed by professionals (Miller 2020). References have been made to the ‘failure to thrive,’ a condition that includes four aspects: weight loss, decreased appetite, poor nutrition, and inactivity (Robertson and Montagnini 2004). It can be expected that long-term confinement will lead to an increased number of deaths as a result of isolation, lack of exercise, and limited access to basic resources among the elderly. The balance of benefits and risks of mitigation measures is thus uncertain. Protection against exposure to the virus comes at the cost of other components of health when the balance between biological, psychological, and social factors is taken into consideration (Engel 1977).

In exploring components of a good life, the influential Capabilities Approach lists ten elements: life; bodily health; bodily integrity; senses, imagination and thought; emotions; practical reason; affiliation, including social interaction and the social bases of self-respect; contact to other species and the natural world; play; and control over one’s political and material environment (Nussbaum 2003). Particular attention should thus be paid to maintaining equal protection of life in all circumstances, but also equal political rights, equal possibilities for social interaction, for play, and, perhaps most importantly, equal access to the social bases of self-respect—the image mirrored back to us by society, which constitutes an important part of our assessment of our own worth. Social distancing should mean neither social exclusion, nor social devaluing. This is important, since official recommendations to continue confinement only for those vulnerable to morbidity and mortality from COVID-19 could result in stigmatization and grievous harms to the social bases of self-respect. Robeyns (2016) proposes the addition of further capabilities—sensory comfort, communication, being understood, being loved, and receiving attention—several of which are at risk during the present confinement, especially in populations unaccustomed to communicating through digital technologies. In the absence of sustained communication, those who remain confined must rely entirely on others to tell their story and cannot sustain their narrative identity (Hurst 2020; Lindemann 2014).

Since vulnerability in the face of COVID-19 is both a diverse and shifting condition, no single trade-off between these components can be described for them all. Decisions about confinement of the vulnerable should include their needs and own definition of the situation—either directly or through representation such as, for example, Pro Senectute for the elderly in Switzerland. Their perceptions of risks are likely to be different from those of other segments of the population, and from those of health professionals. Concurrent perceptions of risks thus need to be taken into account—and note, this holds for all vulnerable groups—especially in a context characterized by high uncertainty and in which trade-offs might be difficult to calculate.

Protection should be a right, not a duty. Individuals vulnerable to severe illness from COVID-19 should be afforded the same liberties and personal choices as others, and these include placing themselves at risk, as long as they do not unfairly increase the risk to others.

In situations that would pose a risk to others, such as a risk to health professionals when personal protective equipment is scarce or a risk of complicity by heightened exposure in public spaces, there is clearly a balance of rights. Far from being an obvious component of deconfinement strategies, then, continued confinement of those most vulnerable to morbidity and mortality from COVID-19 is a difficult political trade-off between types of risks and rights for different populations. Taking dignity, equality, and vulnerability seriously implies that we cannot just ask the most vulnerable to bear any burden, however great, to allow more total rights fulfillment for others during a pandemic. It also cannot, however, imply that others must make any sacrifice, however great, to enable the vulnerable more total fulfillment of their rights either.

How might this balance be struck? A first attempt could start with an attempt to rank the importance of different rights. This is likely to be thwarted by moral pluralism regarding how rights ought to be ranked, but this may not apply to the whole endeavor. For example, we are likely to agree that the right to be in the presence of family members is more important than, say, the right to stand close to another person at a non-crowded bus stop. Rather than a ranking of rights themselves, however, this sort of consensus is more likely to result from agreement on the ranking of transgressions of these rights. In the example above, seeing family members could be based on rights to family life, belonging, or proxy representation in case of incapacity. Standing at the bus stop could be based on rights to freedom of movement. In this case, however, agreeing that having to keep a distance at the bus stop is less severe than having to refrain from seeing family does not commit us to considering the right to freedom of movement to be less important than the rights to family life, belonging, or representation, or indeed any combination of these rights. All we need is to consider that the transgression made by control of standing positions while waiting is a lesser one, as compared to the transgression made by banning visitors from seeing the vulnerable.

A second approach could start by identifying where the rights of the particularly vulnerable and of the less vulnerable could be made more compatible. Rather than continued confinement, for example, protection could require that those particularly vulnerable maintain protective measures in the public sphere: distance, masks, and hand hygiene. It could also require collective efforts to decrease the risk of contagion through test-trace-isolate-quarantine strategies. Giving those particularly vulnerable the possibility to participate more safely in the public sphere would certainly require some inconvenience to others, but it is unlikely to require outright infringements of their rights. In many situations, then, the balance of rights could be resolved.

The requirement to balance rights would remain in situations where such precautions were not feasible, such as restaurants or nightclubs. Where personal protective equipment is scarce, these places may have to be off-limits to the particularly vulnerable in order to protect health professionals down the line. The problem of complicity would then remain. Complicity, however, requires some form of participation or proximity to wrongdoing, Lepora’s account of complicity in healthcare is helpful here (Lepora and Goodin 2013). Patrons of restaurants and nightclubs do not go there with the intent of placing vulnerable persons at risk. Rather than complicity, their action is closer to what Lepora calls contiguity—remaining close to the wrongdoing, when you could have avoided it. More importantly, however, what exactly would be the wrong involved in such a case? Vulnerable individuals who come to a restaurant in circumstances where there is no scarcity of personal protective equipment are not wronging healthcare providers, who can protect themselves. Are they wronging themselves? That we even can wrong ourselves, particularly when we make conscious and deliberate choices, is controversial (Ogien 2007). Even if such a wrong to ourselves is recognized, and complicity in this wrong therefore conceivable, contiguity may not, on balance, be important enough to warrant banning vulnerable persons from restaurants if they choose to come.

The Situation of Institutions

Persons who are more vulnerable to dying of COVID-19 and who also reside in institutions can become at greater risk of contracting the disease not necessarily due to their health condition, but due to the funding, staffing, and infrastructural weaknesses of these institutions (Oliver 2020). Special protections ought to be extended to them Accommodations, including adequate personal protective equipment for staff and, where appropriate, for residents should be put in place to decrease this risk.

In many places, protections have included bans on visitors. This has had the unfortunate consequence of making residents inaccessible to their family, and also to their advocates and legal representatives, resulting in an increased vulnerability to suffer violence and abuses of power (Gardner, States, and Bagley 2020). This situation must be corrected and solutions developed to enable contacts with these persons while still limiting the risk of contagion. Strategies enabling this should be shared among institutions in order to facilitate the diffusion of successful processes. Residents who are capable of decision-making must also be allowed to take risks if they so choose, as long as they do not endanger others.

Currently, explicit provisions exist in certain cases to discourage, restrict, or even prevent the referral of residents from nursing homes to hospital. This is a striking inequality if the actual place of care (and not the medical condition and needs) is the sole condition for (denying) admission. In any case, concepts of care compatible with accepted standards of care (both curative and palliative) must exist on site. Legal representatives must be actively involved in the case of a lack of mental capacity. The possibility to contact the guardianship authorities and “see behind the curtains” of those confined in institutions must be proactively granted by these institutions. The authorities must monitor these measures. These institutions have to be staffed with adequate resources to fulfill this task, which is assigned to them by the civil code.

Those confined in long-term care institutions should also continue to have access to some forms of social contacts, as well as daylight, sun, and fresh air daily—similar to the rights of persons under detention. Especially if conditions have to change in order to decrease the risk of contagion, accommodations need to be made to enable the maintenance and continuation of people’s meaningful daily activities, their “engagements” that have existential values. Many of these activities have complex functions.

Finally, residents of institutions have the same rights to clear, loyal, and truthful information regarding the pandemic situation and the reasons why measures are in place as the rest of the population. This will require active engagement by the staff in order to overcome sensory and cognitive impairments when they are present, and to inform residents on measures taken by the institution itself and their reasons.

While some institutions kept visitors out and residents in, others shut down entirely, leaving elderly and dependent individuals to the care of family members. As a consequence, they were either very isolated with only sporadic visits from professional caregivers and family members—who were afraid of bringing a risk of contagion with them—or left only with the option of living with a relative for whom the burden was suddenly very heavy (Young and Fick 2020).

LEGAL IMPLICATIONS

If confinement for specific groups should continue, there would be a great need for clarification: Is the confinement a government recommendation or a legal obligation? What exactly does confinement involve? What are confined people allowed or not allowed to do? Who exactly is concerned? Is there one category of vulnerable persons or several? Who decides whether a person falls in the category or not, and how can such a decision be challenged? What is the situation of people living in the same household with confined people?

All these questions would need to be clarified in order to provide such continued confinement on a legal basis. The legal implications of an obligation would also be considerably different from those of a recommendation.

Legal Implications of an Obligation

A legal obligation would involve very numerous and serious legal issues. Some of the legal problems involved are so great that we would qualify them as insurmountable. As the restrictions to fundamental rights would be severe, the legal basis would have to (1) be a law made by parliament (federal or cantonal, depending on competencies), as the decision would have to be made by an authority with the legitimacy to strike a balance between the competing rights outlined above; (2) be based on an overriding public interest (which cannot be to protect vulnerable people against their will); and (3) be proportionate. Human rights limitations cannot be justified by the political will of protecting people from themselves. Persons who are capable of judgement enjoy the right to self-determination, which includes the right to take unreasonable and risky decisions. Any person capable of judgement, vulnerable or not, has the right to accept health risks.

Mandatory confinement could only be justified in three situations:

  1. The vulnerable person is not capable of decision-making (because she suffers from dementia, depression, etc.). In such a situation, the civil law rules on the protection of adults, and an agency or legal representative decides what is in the best interest of the person.
  2. The person fulfills the requirements of a mandatory care accommodation (Art. 426 Swiss Civil Code) and is deprived of liberty because no other means guarantee the person’s health and security.
  3. There is an overriding public interest other than protecting the confined person, such as a risk to the rights and freedoms of other people, or a need to protect the overall health system from becoming dysfunctional. In our view, this is the only public interest on which confinement policies could be based.

Even if one of these situations is given, all confinement measures would still have to be proportionate. Even a person incapable of decision-making could thus not be confined without ensuring that this measure is necessary to protect her and that the confinement is reasonable given her overall situation. Family members or legal representatives would have to make the necessary decisions. If the confinement is established to protect the overall health system, only a flexible system (reacting to the situation in the hospitals, to the number of available intensive care beds and ventilators) would be proportionate. In addition, it would not be proportionate—and hence would not be constitutional—to confine vulnerable people who have renounced the use of intensive care/ventilators in an advance directive.

The European Court of Human Rights (ECHR) case law is quite clear on this issue. Deprivation of liberty, according the ECHR, involves the following:

Taking the above principles into account, the Court finds that the essential criteria when assessing the “lawfulness” of the detention of a person “for the prevention of the spreading of infectious diseases” are whether the spreading of the infectious disease is dangerous to public health or safety, and whether detention of the person infected is the last resort in order to prevent the spreading of the disease, because less severe measures have been considered and found to be insufficient to safeguard the public interest. When these criteria are no longer fulfilled, the basis for the deprivation of liberty ceases to exist.

Confinement measures can thus only be examined under the criteria of contributing to the prevention of disease spread and when this is the last resort. Where other preventive measures can prevent disease spread, such as distancing or test-trace-isolate-quarantine strategies, confinement measures become unjustified.

Numerous aspects of the situation of mandatorily-confined people would have to be determined, such as: work, social security, health services, political rights, religious rights, tenancy, family, social, and cultural life, and more. Appeals procedures would have to be in place. The government, severely limiting fundamental rights and freedoms, would have to take special responsibilities for all concerned people and be obliged to make best efforts in order to limit harm and to enable maximum human rights enjoyment. Such confinement could not take place at home without negating the entire aim, since others living with the confined individual could still transmit the virus outside the home.

Overall, then, a legal obligation for continued confinement of the vulnerable seems to entirely lack feasibility and justification. We conclude that this path should not be pursued.

Legal Implications of a Recommendation

A government recommendation would raise very different questions than a legal obligation. As long as vulnerable people are not legally bound to stay at home, the government can use its soft power to protect specific groups and the health system. As long as people are free to follow or not follow a recommendation, freedom rights are not limited. The issuing of recommendations as such is thus not a legal problem. A recommendation may not be enforced, not even by soft measures.

However, numerous questions would need to be clarified. What is the legal situation of vulnerable people deciding to follow the recommendation? And what would be the situation of people not following it? If negative legal (e.g., financial) consequences are attached to such a decision, a recommendation can turn into a de facto obligation. This is to be prevented, as it blurs rights and obligations.

In Switzerland, for example, employers are obliged to allow persons at-risk to work from home. If their presence is indispensable, the employer must take necessary measures to protect these persons. Still, a particularly vulnerable person may refuse to work if he or she considers the health risks to be too high. If working at home or from the workplace is not possible, the employer must allow the person to stop working while continuing to pay wages. This regulation, as it stands, is not fully clear (when is working from home or from the workplace “possible”?). In addition, the individual employer can be overburdened by it. She or he can take all necessary measures at the workplace and the vulnerable person is still allowed to refuse to work. The refusal to work might be caused by the risks of commuting, or the fear of endangering other vulnerable persons living in the same household, etc. The obligation of the employer to continue to pay wages is currently not limited—in contrast to the rules that normally apply.

If people vulnerable to COVID-19 are allowed to opt out of work obligations, the duty of the employer to pay wages would have to be limited in time as well. After this period, social security would have to step in. Otherwise, there is an (increased) risk that employers stop employing vulnerable people or terminate work contracts. The continued confinement would then further disadvantage vulnerable people in the labor market.

The situation of vulnerable persons without a work contract (e.g., the self-employed) would also need to be clarified.

The effects on families and on childcare would have to be taken into account as well. Of all grandparents in Switzerland, 40% take care of their grandchildren weekly. Overall, they spend about 160 million hours a year looking after children. If there is a recommendation (or an obligation) not to do so, young families (and childcare institutions) will have to carry new burdens. These burdens would have to be borne collectively, at least in part. If grandparents are prevented from looking after children—they (and their families) would then be obliged to make special efforts to protect the health system in the interest of all and should not have to shoulder the financial costs of it.

SUSTAINING THE VULNERABLE

What is our responsibility to take certain actions so that the more vulnerable can have more freedom to participate in social and public life without exposing themselves to unacceptable levels of harm? Individual rights that are balanced with safety during a pandemic do not go away. Rather, they are balanced against the right to life and health during exceptional circumstances. When the situation is acute and leaves no time for measures other than confinement, this balance can be justified. When the situation persists for a longer time, however, providing safe spaces and measures that re-enable the exercise of individual rights becomes necessary. Societies are adapting to living with COVID-19 and re-organizing many activities. This reorganization to re-enable life and the exercise of individual rights, then, needs to happen for everyone and not only for those who are professionally active and not particularly vulnerable to COVID-19.

Examples could include reserved times in shops, museums, libraries, or cinemas, where fewer people would be allowed in at any one time so that those particularly vulnerable to dying of COVID-19 could interact without placing themselves at risk. It could include safe transports for those at particular risk: as the lockdown measures ease and more people move around, it will become more problematic for high-risk persons to go out (in order to get regular cancer treatment, for instance). In a situation where distance is being promoted, special measures aimed at re-establishing social ties will also be needed. And so on.

When assessing whether to make such accommodations—and whether to accept the attendant costs—it should be remembered that everyone’s freedom is assisted and that this always has a cost. We have collectively invested in transportation infrastructure to allow us to come, go, earn a living, exercise our social and political rights, etc. We need to invest in such institutions for the benefit of everyone, not of some only. Responding to the COVID-19 pandemic has forced us to reorganize many aspects of our collective life. It should also force us to reorganize the possibilities for everyone to participate. Equal regard for the dignity of all persons, considered to be the basis for all fundamental rights, would seem to require it.

Inevitably, however, trade-offs will arise. The question then becomes one of balancing the rights and interests of different groups against others. It seems unjust to disregard the rights of the ‘vulnerable’ or the ‘non/less-vulnerable’ entirely, meaning neither confinement of vulnerable groups nor total freedom to engage in any action by non/less-vulnerable groups is acceptable. This must be informed by science and public health principles, but ultimately these are decisions that must be made in a democratically legitimate manner.

SELF-DETERMINATION

From a risk management perspective, the COVID-19 pandemic does not appear as a riskier situation than many of the other—sometimes serious—health problems facing the elderly or those with chronic conditions. Where confinement aims to protect the vulnerable themselves, then, there is no justification to withhold the choice from them. If the pandemic can be sufficiently controlled, then an individual should have the right to decide how much risk they are willing to take. For many, the level of acceptable risk is above zero. The health system is there to care for those who become ill, in the same way that it cares for those who get into ski accidents or develop chronic illnesses linked to personal choices. A low-level, sustainable steady rate of cases may be inevitable and tolerable, in the same way that a low-level, steady rate of car accidents happens every year, despite reasonable precautions by the state.

This means that it is important to distinguish situations where choices made by individuals actually harm others (for example, a resident in long-term care who insists on holding a birthday party with all the other residents and invites her family) from situations where these choices do not harm others (for example, a resident in long-term care who insists on receiving a visit from her seven-year-old granddaughter, who can visit without crossing paths with anyone else).

It also means that taking away the choice wrongs the vulnerable in two distinct ways: first by limiting their self-determination, but also by sending the implicit message that vulnerable individuals are not competent to make their own decisions.

A prolonged confinement based on age will mean age segregation and could reinforce current negative reactions towards those who do not follow the ‘stay-at-home’ message. Messages advising for self-determination could undermine such stigmatization. They would also limit intra-family conflicts of younger generations being overprotective towards their parents and grandparents as a result of official messages.

CONCLUSION

Far from being an obvious component of deconfinement strategies, then, continued confinement of those most vulnerable to morbidity and mortality from COVID-19 is a difficult political trade-off between types of risks and rights for different populations. Confinement cannot be the only measure in place to protect vulnerable persons. Protections are needed to enable and sustain participation in the public sphere and the exercise of rights for persons particularly vulnerable to COVID-19.

Many long-term care homes have currently banned visits from residents’ next of kin and legal representatives. Solutions must be developed to enable contacts with these persons while still limiting the risk of contagion for residents. Such strategies should be shared among institutions in order to facilitate the diffusion of successful processes. Concepts of care compatible with accepted standards of care (both curative and palliative) must exist on site. Institutions must be staffed with adequate resources to fulfill these tasks. Those confined in long-term care institutions should also continue to have access to some forms of social contacts, as well daylight, sun, and fresh air daily. Residents of institutions have the same rights to clear, loyal, and truthful information regarding the pandemic situation and the reasons why measures are in place as the rest of the population. The authorities must monitor these measures.

Vulnerable persons should retain the choice to place themselves at risk, as long as they do not impose risks on others. Vulnerable persons who choose to remain in confinement should be protected against loss of their jobs or income, and against the risk of discrimination in the labor market. If people vulnerable COVID-19 are allowed to opt out of working obligations, the duty of the employer to pay wages must be limited. After this period, social security should step in. If confinement persists, retraining through invalidity insurance may have to be considered in these cases. As the elderly may place themselves at risk if they take care of their grandchildren, free access to childcare for parents should also be part of a protection strategy.

Risk and crisis communication stresses the importance of listening to the people themselves, and to set up participatory approaches. Associations and lobbies representing the views of groups of those particularly vulnerable to COVID-19 (both the elderly and those with diseases placing them at particular risk) should be consulted. Most vulnerable persons are autonomous and competent, and should be allowed to voice their own opinion.

DISCLAIMER

This work was initially developed for a policy brief by the ELSI group of the Swiss National COVID-19 Science Task Force. Five of the authors (CBJ, EMB, SM, PM and SAH) are members of this group. The views expressed here do not necessarily reflect the positions of the Swiss National COVID-19 Science Task Force, or of the Swiss government.

ACKNOWLEDGMENTS

The authors wish to thank an anonymous reviewer, whose insightful comments helped us to substantially improve this paper.

REFERENCES

Douglas Margaret, Srinivasa Vittal Katikireddi, Martin Taulbut, Martin McKee, and Gerry McCartney. 2020. “Mitigating the Wider Health Effects of COVID-19 Pandemic Response.” BMJ 369: m155

Engel, Georg L. 1977. “The Need for a New Medical Model: A Challenge for Biomedicine.” Science 196(4286) :129–136.

European Commission. 2020. “Joint European Roadmap Towards Lifting COVID-19 Containment Measures.” https://ec.europa.eu/info/sites/info/files/communication_-_a_european_roadmap_to_lifting_coronavirus_containment_measures_0.pdf

Gardner, William, David States, and Nicholas Bagley. 2020. “The Coronavirus and the Risks to the Elderly in Long-term Care.” Journal of Aging and Social Policy. Published online. https://doi.org/10.1080/08959420.2020.1750543.

Hurst, Samia A. 2020. “Vulnerability in Old Age: The Fragility of Inappropriately Protected Interests. ” In Aging and Human Nature, edited by Mark Schweda, Michael Coors, and Claudia Bozzaro, 241–52. Springer.

Jefferson, Tom, Mark M. Jones, Lubna A Al Ansari, et al. “Physical Interventions to Interrupt or Reduce the Spread of Respiratory Viruses. Part 1 – Face Masks, Eye Protection and Person Distancing: Systematic Review and Meta-analysis.” medRxiv. doi: https://doi.org/10.1101/2020.03.30.20047217

Christian Lalive d’Epinay, and Dario Spini. 2008. Les Années Fragiles. Québec: Presses de l’Université de Laval.

Lepora, Chiara, and Robert E. Goodin. 2013. On Complicity and Compromise. Oxford: Oxford University Press.

Lindemann, Hilde. 2014. Holding and Letting Go: The Social Practice of Personal Identity. Oxford, New York: Oxford University Press.

Miller, Greg. 2020. “Social Distancing Prevents Infections, but It Can Have Unintended Consequences.” Science, March 16. https://www.sciencemag.org/news/2020/03/we-are-social-species-how-will-social-distancing-affect-us.

The Novel Coronavirus Pneumonia Emergency Response Epidemiology Team. 2020. “Vital Surveillances: The Epidemiological Characteristics of an Outbreak of 2019 Novel Coronavirus Diseases (COVID-19) – China 2020. ” China CDC Weekly. 2 (8): 113–22.

Nussbaum, Martha. 2003. “Capabilities as Fundamental Entitlements: Sen and Social Justice.” Feminist Economics 9 (2–3): 33–59

Ogien, Ruwin. 2007. Ethics Today: Maximalists and Minimalists [L’éthique Aujourd’hui; Maximalistes et Minimalistes]. Paris: Gallimard

Oliver, David. 2020. “Let’s Not Forget Care Homes When COVID-19 is Over.” BMJ 369: m1629. doi: https://doi.org/10.1136/bmj.m1629

Robertson, Russell G., and Marcos Montagnini. 2004. “Geriatric Failure to Thrive.” American Family Physician 70: 343–50.

Robeyns, Ingrid. 2016. “Conceptualising Well-Being for Autistic Persons.” Journal of Medical Ethics 42: 383–90.

Spini, Dario, Daniela S. Jopp, Stephanie Pin, and Silvia Stringhini. 2016. “The Multiplicity of Aging: Lessons for Theory and Conceptual Development from Longitudinal Studies.” In Handbook of Theories of Aging, edited by Vern L. Bengston and Richard A. Setterston, 669–90. New York: Springer.

Spini, Dario, P Ghisletta, E Guilley, and C Lalive d’Epinay. 2007. “Frail elderly.” In Encyclopedia of Gerontology, edited by James E. Birren, 572–79. Oxford: Elsevier.

Swiss Federal Office for Public Health. 2018. Swiss Influenza Pandemic Plan. Strategies and Measures to Prepare for an Influenza Pandemic in Switzerland, Fifth edition. https://www.bag.admin.ch/bag/en/home/das-bag/publikationen/broschueren/publikationen-uebertragbare-krankheiten/pandemieplan-2018.html.

Swiss National COVID19 Science Task Force. 2020. “Ethical, Legal and Social Issues of Transition Strategies.” https://ncs-tf.ch/de/policy-briefs/elsi-input-into-transition-strategy-11-april-20-en-2/download.

Thunstrom, Linda, Stephen C. Newbold, David Finnoff, Madison Ashworth and Jason Shogren. 2020. “The Benefits and Costs of Using Social Distancing to Flatten the Curve for COVID-19.” Journal of Benefit-Cost Analysis. DOI: https://doi.org/10.1017/bca.2020.12.

Young, Heather M., and Donna Fick. 2020. “Public Health and Ethics Intersect at New Levels with Gerontological Nursing in COVID-19 Pandemic.” Journal of Gerontological Nursing 46 (5): 4–7.

Zhang, Juanjuan, Maria Litvinova, Yuxia Liang, et al. 2020. “Changes in Contact Patterns Shape the Dynamics of the COVID-19 Outbreak in China.” Science eabb8001. doi: 10.1126/science.abb8001

Special Issue, Uncategorized

Should I Do as I’m Told? Trust, Experts, and COVID-19

Matthew Bennett

[This is an advance copy of an article that will appear in print in September 2020 as part of the KIEJ’s special double issue on Ethics, Pandemics, and COVID-19.]

ABSTRACT. The success of public health responses to the COVID-19 pandemic is sensitive to public trust in experts. Despite a great deal of attention to attitudes towards experts in the context of such crises, one significant feature of public trust remains underexamined. When public policy claims to follow the science, citizens are asked not just to believe what they are told by experts, but to follow expert recommendations. I argue that this requires a more demanding form of trust, which I call recommendation trust. I argue for three claims about recommendation trust: recommendation trust is different from both epistemic and practical trust; the conditions for well-placed recommendation trust are more demanding than the conditions for well-placed epistemic trust; and many measures that have been proposed to cultivate trust in experts do not give the public good reasons to trust in expert-led policy.

1. Introduction

In 2019 public trust in politicians was at an all-time low in many parts of the world. Then again, it had been low for quite some time.[1] Public trust in epistemic authority is a more complicated matter. The success of many right-wing politicians—Trump, Johnson, Bolsonaro, etc.—is partly due to their efforts to discredit traditional sources of information, including the “mainstream media” and whichever scientific institutions prove inconvenient to their political interests. But worries about the erosion of epistemic standards in public discourse are easily overstated, and some polling data have shown that publics are not as distrustful of experts as we might fear.[2]

Nonetheless, there are some political and social crises in which even a small degree of suspicion of scientific authorities can have disastrous consequences. One such crisis is the climate change emergency. It is often with a focus on the climate crisis that social epistemologists and philosophers of science have tackled a range of questions around trust in expertise, including how we can defend the rationality of trusting experts and what measures we can take to cultivate such trust (see e.g., Anderson 2011; John 2016). Public health crises are also highly sensitive to public trust in experts, and the COVID-19 pandemic is no exception to the principle that when epidemics pose serious threats to the health of whole nations, distrust of the relevant public health experts can have serious consequences.

Despite a great deal of attention to attitudes towards experts in the context of such crises, one significant factor in public trust in experts remains underexamined. The vast majority of philosophical work on public trust in experts has addressed questions about epistemic trust: forming beliefs on the basis of the testimony, broadly construed, of scientists and scientific communities. But as the COVID-19 pandemic shows us, a distinct kind of trust in experts is needed when experts not only provide information and data, but also play an instrumental role in the formation of science-led policy. When public policy claims to follow the science, citizens are asked not just to believe what they are told, but to follow expert recommendations. I argue that this requires a distinct form of trust, which I call recommendation trust.

I will argue for three claims about recommendation trust. The first is that recommendation trust is different from both epistemic trust and a third form of trust, also popular among philosophers, which I call practical trust (Section 3). The second is that the conditions in which recommendation trust is well-placed are more demanding than the conditions for well-placed epistemic trust (also Section 3). This is because to have good reason to follow an expert recommendation I must not only believe that the expert is sincere and competent in their field, but also that the action they recommend is in my interest. This leads me to argue for my third claim (Sections 4 and 5): because the norm that governs the rationality of recommendation trust is more demanding than that which governs epistemic trust, many measures that have been proposed to cultivate trust in experts do not help to cultivate recommendation trust in science-led policy. In short, experts have a higher bar to clear when we are asked to follow their recommendations. If we are to ask the public to trust the recommendations of scientists, we must acknowledge that this is different from asking novices to accept facts. When science leads policy, it must work harder to merit public trust

2. THE SIGNIFICANCE OF TRUST

My account depends foremost on the assumption that public trust in experts is both necessary and desirable for an effective public health response to the coronavirus pandemic.[3] One reason to think trust in experts is particularly important in the context of the pandemic is that most current public health policies in response to the crisis depend on a significant degree of voluntary compliance. Many countries have taken social distancing measures to reduce infection rates to a manageable level. This usually involves radical lifestyle changes for citizens, including the closure of businesses, workplaces, and many public spaces, bans on travel for all but essential journeys, and complete self-isolation for those at greater risk of serious illness. It is fair to assume that it would be wholly unpractical to apply social distancing solely through comprehensive policing and direct enforcement. And I am confident that even if compliance with social distancing could be guaranteed wholly through coercion, this would be undesirable.

A state could coerce compliance with social distancing in ways that are less direct than totalitarian policing. The simple threat of such measures might be enough to persuade the public to comply. I am also taking for granted that we would prefer voluntary compliance with a public health policy to compliance secured solely through public fear of what the state might do to them if they do not comply. But note that this is not an all-or-nothing test of the desirability of a public health policy, as if such a policy either depends on states applying coercive power to all citizens, or it does not depend on such power at all. Any state-enforced policy, even where it is granted democratic legitimacy through public trust, will involve exercising coercive power over the few who refuse to comply. In this respect, trust in government secures not just a sufficient level of compliance with government policy, but also sufficient public support for the policing of that policy. It would be wrong to think that a public health response secured through trust would involve no coercive state power at all.

Though I am taking for granted that public trust is a necessary part of a desirable response to the pandemic, I do not assume it is sufficient. There are many reasons for this. One is that citizens may be willing but unable to comply with government policy. Emerging research on public behavior during the pandemic in the UK indicates that although willingness to follow social distancing measures is generally high, the ability to self-isolate is not evenly distributed, with the most economically disadvantaged unable to comply (Atchison et al. 2020). Thus, some citizens who trust policymakers enough to be willing to follow policy might not be able to do so.

It is also possible for citizens to trust policy that does not merit trust, and I will be assuming that the kind of public trust that features in a desirable response to the pandemic is specifically trust that is well-placed. Here it helps to invoke a distinction sometimes made by social epistemologists between trustworthiness and credibility (Rolin 2002). An authority is credible when it is likely to be believed. Credibility is vulnerable to faulty reasoning by individuals when making judgements about whom to believe, but the more insidious threat to well-placed trust is posed by structural injustices that grant illegitimate authority to privileged social groups (Fricker 1998). By contrast, an authority is trustworthy when its claims should be given credence. Following Onora O’Neill’s work on public trust (see e.g., O’Neill 2020), I will assume that desirable public trust must be trust in the trustworthy, and it is only accidentally related to credibility. However, one of the tasks of good science-led policy is to bridge any extant gaps between credibility and trustworthiness. I will return to this challenge in Sections 4 and 5.

My framing of the issues so far might be accused of confusing two very different matters: public trust in scientific experts and public willingness to comply with government policy. If some readers worry about this, then all the better for the purposes of this paper, for the distinction I wish to argue for is very similar to the distinction between trust in science per se and compliance with scientifically-informed policy. But before proceeding to put some conceptual distance between trust in science and trust in technocracy, it is worth noting some observations about the tandem pairing of government policy and scientific expertise that we see in many (though not all) government responses to the coronavirus crisis. What we find in the pandemic is that when science has a significant role to play in policy, trust in experts and compliance with government go hand in hand.

In the UK, where I write this paper, the government’s response to the pandemic has been consistently presented to the public as “following the science.” Daily press conferences began on March 12, 2020 with a briefing delivered by the prime minister flanked either side by the government’s chief medical officer, Chris Whitty, and chief science officer, Patrick Vallance. Vallance and Whitty have since played a prominent role in communicating the government’s policy on the coronavirus, standing alongside government ministers in many more press conferences and appearing on television, on radio, and in print to explain the UK’s public health strategy. Between March and May, Whitty and Vallance have been joined in this communications effort by inter alia Angela McLean, deputy chief scientific adviser, Jenny Harries, deputy chief medical officer, and NHS England’s medical director, Stephen Powis.

Each of these government spokespersons are scientists—epidemiologists, clinical pharmacologists, mathematicians, public health physicians, and medical professors. Their most evident role in the current emergency appears to be to amplify the message that there is authoritative scientific reasoning that supports the social distancing measures the public are being asked to adopt. This “following the science” message depends on the public believing not just that these scientists are part of the communication of the policy, but also that they are involved in deliberations that result in that policy. That the UK government is in fact following the science is very much open to question, but it is evident that the UK’s approach to communicating its message to its citizens is to heavily emphasize its (putative) technocratic nature.

Most other national government responses lie somewhere between two extremes: namely, policy that is directly contradicting the recommendations of most scientists and policy that is designed and implemented by scientists. These extremes are somewhat idealized insofar as the question of whether a given national policy denies or follows “the science” ignores the fact that there is no single authoritative scientific perspective on what should be done. Nonetheless, some notable examples approximate these extremes. In Brazil, Jair Bolsonaro has argued publicly with regional governors and the national health ministry about the wisdom of advice to all citizens to stay home. In the US, Donald Trump has made a series of dangerously ill-informed claims about possible treatments for COVID-19, from hydroxychloroquine to disinfectant, prompting multiple high-profile corrections from Anthony Fauci, director of the US National Institute of Allergy and Infectious Diseases. By stark contrast, the Swedish government has in large part handed over their public health response to state epidemiologist Anders Tegnell, who has become the public face of the Swedish government during the pandemic and leads a state science agency with a significant degree of autonomy from the government. Though it would be easy to overstate the level of political authority granted Swedish public health agencies (responsibility for policy still formally lies with government ministers), the Swedish case is perhaps the closest thing we have to a purely technocratic response to the pandemic.

For those governments that are not actively discrediting the recommendations of scientific experts, public trust in experts and public compliance with government policy go hand in hand. The significance of public trust in experts increases with the degree to which government policy is presented as technocratic. Note that this does not mean that a government’s strategy for dealing with the pandemic must in fact be technocratic in order for public trust in experts to be a significant factor in securing public support. Public trust in experts can support policy implementation by ensuring that citizens are willing to comply with government public health responses that are perceived to be led by science, regardless of whether they are in fact led by science. Public trust in experts is also a significant factor in public support for genuinely technocratic policy, provided we wish to avoid measures to secure public endorsement that involve coercion or dishonesty.[4]

3. RECOMMENDATION TRUST

Limited though they are, there are lessons to be learned from the coronavirus pandemic about the nature of the public trust that supports acceptance of (at least putatively) science-led policy. Before outlining those lessons directly, it will help to be more precise about the kinds of trust that are relevant to the pandemic.

I will be treating trust in all of its forms as a tripartite relation: one person trusts another with regard to a particular object of trust.[5] What I call practical trust is to stake something of importance on a particular action or range of actions that I expect another to perform. Thus, what I mean when I say ‘I trust the babysitter’ is that I place the wellbeing of a child in the hands of the babysitter, and I am confident in doing this because I expect the babysitter will take good care of the child. Moreover, the domain of my trust in the babysitter is restricted, insofar as I do not trust them to do just anything. Epistemic trust is to believe something because another person has told us it is true. Epistemic trust requires that the truster ascribes sincerity to the trusted, but also competence in the matter about which the trusted is providing testimony. A similar domain restriction applies. I might trust a classicist to help me with Greek etymology but not trust them on matters of bicycle repair, even if I expect them to be sincere when answering questions in either area.[6] Both epistemic and practical trust differ from a third form of trust that I will call recommendation trust. I recommendation-trust someone when I believe I should do something because they have told me I should. The domain restriction also applies to the act recommended by the person I recommendation-trust: when I trust the recommendation of another it is because there is a particular area in which I take that person’s recommendations to be trustworthy.

As I am primarily interested in differences between recommendation trust and epistemic trust, I will stop short of a full account of these three forms of trust. A comprehensive definition of recommendation trust would need to do more to distinguish it from other, deceptively similar ways in which we form beliefs about what we should do. Say I am taking a trip by car with a friend. The friend recommends I avoid the M25 this afternoon because of the likely traffic. But I have good reason to think that taking a detour route will take just as long, despite the heavy traffic on the M25. There are a number of ways I might do as my friend suggests, in response to their suggestion, without thereby following their recommendation. Perhaps I avoid the M25 to humour my friend (I know they tend to be insecure about others not taking their travel advice). Perhaps I avoid the M25 because I know that my friend has a phobia of traffic jams and is too proud to cite this as the reason for asking that we take a detour. Perhaps my friend is an intimidating person, and I fear the consequences of questioning their advice. Doing as my friend recommends for any of these reasons is not trusting their recommendation.

Note also that the same principle applies to public trust in the recommendations of politicians and experts. If members of the public accord with the recommendations of government because they fear what the government would do were they not to follow its recommendations, then the public is not acting on trust, but on fear. Policy that depends on this form of compliance is precisely the coercion-based policy that earlier I suggested we would prefer to avoid. Moreover, compliance with public health recommendation is significantly different from compliance with law. I will restrict my focus to the question of when we have good reason to follow public health recommendations issued by experts.

One very common concern about epistemic trust is that to believe what we are told by experts we must believe without the warrant available to other kinds of belief (Burge 1995; Hardwig 1985, 1991; John 2018; Kukla 2007). Experts know about things I do not know about and sometimes could not know about. But many areas of expertise are areas in which it is important for non-experts to form true beliefs. Such beliefs must be formed without access to all of the evidence and without expert ability to understand the evidence. This threatens the possibility of both knowledge and rational belief about a wide array of basic facts. Do I know whether the Earth is flat without travelling? Should I believe that penicillin can be used to treat infection without first studying biochemistry? Knowledge of such matters depends on the rationality of beliefs grounded in the testimony of others, and the rationality of such beliefs is questionable in ways that the rationality of other beliefs is not.

John Hardwig’s influential solution to this problem was to argue for the following principle:

(T) If person A has good reasons to believe that person B has good reasons to believe that P, then A has good reasons to believe that P. (1991, 697–98)

Hardwig suggests that if such principles can be demonstrated, we can rescue testimony-based beliefs from scepticism. If (T) holds, Hardwig argues, then we can be epistemically justified in believing what others tell us is the case without having to investigate the evidence ourselves. If Hardwig is right, the principle also gets us part of the way to understanding how epistemic trust in experts could be rational. Say that I believe my doctor to be competent, well-informed, and sincere. This same doctor tells me that if a person’s heart stops outside of hospital there is a 20 percent chance that CPR will save their life. Provided I have good reason to believe the doctor to be competent, well-informed, and sincere, I have good reason to believe that if a person’s heart stops outside of hospital there is a 20 percent chance that CPR will save their life.

With much greater complexity, a novice can adopt a comparable relation of epistemic trust in public experts communicating facts about COVID-19. The greater complexity comes partly from the fact that it is very unlikely that most non-experts would have direct access to the testimony of experts. Most of us will read about what experts have to say about the pandemic as it is reported by journalists. Thus, for example, the question of whether I should (epistemic) trust UK chief medical officer Chris Whitty is made more difficult if, rather than watching the press briefings led by Whitty, I instead read reports based on the briefings in a national newspaper. Most obviously the problem of the rationality of my trust in this situation is compounded by the additional question of whether I can trust the newspaper; I must have reason not just to believe that Whitty is competent and sincere, but also to believe that the journalists working at the newspaper are competent and sincere.

Hardwig’s principle does not render epistemic trust easily won; there are many obstacles to rational epistemic trust.[7] It nonetheless does give us an account of how epistemic trust can be rational, and it is not implausible that its conditions for rational trust might sometimes be met. But even if the conditions set by Hardwig’s principle for rational trust are met, we have not thereby met conditions for rational recommendation trust. This much is evident when we attempt to adjust Hardwig’s principle to apply to recommendation trust.[8] When a person provides factual testimony, they communicate their belief that something is the case, and the question is whether this gives the receiver of testimony good reason to believe the same. When a person makes a recommendation, they communicate their belief that the receiver of the recommendation should do something. Accordingly, the analogous question is whether the recommendation gives the receiver good reason to agree that they should act as recommended. If we adapt Hardwig’s principle to apply to recommendations, we arrive at the following:

(R) if A has good reasons to believe B has good reasons to believe that A should act a certain way, then A has good reasons to believe that they should act that way.

But (R) is not true.[9] Consider again the doctor who has told me about the likelihood of a person being revived through CPR. Imagine that this same doctor follows up with a recommendation: given the low likelihood of resuscitation and the potential for distress if CPR is attempted unsuccessfully, it would be best if I signed a Do Not Attempt CPR (DNACPR) form. Grant that the doctor has good reasons to believe I should sign the DNACPR and that I still think my doctor competent and sincere. And set aside for the sake of argument the significant ethics violations involved in a physician making a recommendation on the decision to sign a DNACPR. Do I have good reason to sign?

Not necessarily. If the doctor’s good reason to think I should sign is that their employer has imposed perverse targets for DNACPR signatures, then this is not likely to be a good reason for me. Perhaps that is stretching what counts as a good reason for the doctor to recommend signing. But say instead that the doctor recommends signing because they have seen too many patients and families suffer the indignity of a failed CPR attempt at the end of life or that they think it is likely that patients whose lives are saved by CPR would only live for a few days more with broken ribs and severe pain. Though these are still questionable reasons for the doctor, they are not evidently bad reasons for them to believe I should sign the DNACPR. But even if they are good reasons for the doctor to think I should sign, they are not necessarily good reasons for me to think this. For I may, for example, have a deeply held conviction in the value of life or in the purpose of medicine to preserve life at all costs. The doctor’s good reasons are not necessarily even reasons that I accept but decide are overridden by other reasons (“I agree, but I consider other things more important”), for I may altogether repudiate the value of a dignified end of life. Thus, even if I am in a position, given the sincerity and competence of the doctor, to believe that they have good reasons to think I should sign the DNACPR, I do not thereby have reason to sign.

An additional condition must hold for it to be rational to trust in the recommendation of an expert. That additional condition is that the person has good reason to believe that the expert bases their recommendation on values that are held by the recipient of the recommendation. To be more specific, a recommendation is based on the values of another when B recommends an action to A because B believes that action is in A’s interests. The ambiguity of “interest” here helps to keep this condition flexible enough to cover actions that are valuable for a person in virtue of their desires (“Given you wish to lift heavier weights, I recommend you work on your shoulder mobility.”) and actions that are valuable for a person despite their occurrent desires (“Smoking is bad for you; stop it.”). This flexibility is important because without it we would be committed to thinking that one can never rationally trust a person who is trying to teach us to change our values. Sometimes we turn to experts not just because they can show us the means to our ends, but because we want their advice on the ends themselves.

We thus reach a more demanding version of a principle for recommendation trust:

(R*) if A has good reasons to believe B has good reasons to believe that a certain action is in A’s interest, then A has good reasons to believe that they should perform that action.

One way in which this is a more demanding principle than that which governs epistemic trust is that it requires that we have good reason to think that the expert issuing the recommendation understands what is in our interest. In some cases, this condition might be easily met. Most of the time when we ask a doctor for a recommendation we expect them to tell us what is good for our health, and we will be happy to defer on precisely what health means and what we should do to preserve it. But even in medical cases we will sometimes encounter situations in which we cannot take for granted that a competent doctor’s recommendations will be in our interest. The potential divergence of values in a decision about a DNACPR is one example of this.

4. HOW DO WE CULTIVATE TRUST?

The difference between epistemic trust and recommendation trust has ramifications for the measures appropriate to cultivating trust in experts. Much of the literature theorising ways in which we could help to build trust in science focuses on the sceptical problem posed by the decline of the value-free ideal of science (see, e.g., Anderson 2011; John 2018; Schroeder 2019). In doing so, this work focuses on how we can cultivate epistemic trust. There is no one answer to this challenge for epistemic trust in science, nor is this the only challenge.[10] To keep things manageable, I will focus only on the problem that values in science poses for trust, and to a selection of solutions to this problem. The question I raise is whether any proposed measures to cultivate epistemic trust in experts could also build recommendation trust. The purposes of this are twofold: to demonstrate that not all measures that help to cultivate epistemic trust help to build recommendation trust; and to arrive at a positive—though provisional—proposal for two measures to cultivate recommendation trust in experts.[11]

Consider first a popular argument against the value-free ideal of science, namely the argument from inductive risk (Douglas 2000; John 2016). Evidence gathered to test a scientific hypothesis typically underdetermines whether we should accept or reject the hypothesis because it fails to support deductive inferences either way. This introduces an inductive risk of either false positives or false negatives, depending on the level of caution we exercise in rejecting or accepting hypotheses. The level of caution we exercise cannot be grounded in epistemic reasons, and so we must appeal to non-epistemic reasons—primarily ethical values—to decide how cautious we will be.

Such judgements about the inductive risk we are willing to accept are particularly prevalent in our current emergency, where decisions need to be made quickly and data are scant. The parameters of our epidemiological modelling, for example, will partly be determined by non-epistemic reasons for whether we are more willing to risk overestimates or underestimates in infection and mortality rates. These decisions are sometimes said to be based on a trade-off between COVID-19 deaths now and deaths or decreased wellbeing in the future as a result of the economic impact of social distancing. However, the role of values is likely to be much more complex than this. Our values will affect, among other things, what we consider to be possible responses to a pandemic-generated recession, and political decisions will partially determine the outcomes of a recession, including who bears the brunt of its negative effects. Even setting the terms of the trade-off is influenced by our politics.

In response to such reasons to think science cannot be value free, some have called for greater transparency about the way in which values affect scientific results.[12] Greater transparency promises two benefits. First, transparency encourages novices to believe that scientists are honest about their procedures and findings. This belief in honesty is one of the crucial components in epistemic trust in science. Second, greater transparency could mitigate whatever tendency there might be among the public to think that the collapse of the value-free ideal of science warrants a blanket scepticism about all scientific claims. Values influence science in a variety of ways, some of which merit much less scepticism about the results of science than others. Heather Douglas (2008) has argued that there is a significant difference between direct and indirect influence of values on science. Values play an illegitimate direct role in science when they are used to warrant an empirical claim. Values play a legitimate indirect role in science when they determine what we accept as sufficient warrant for an empirical claim, with the warrant provided solely by epistemic evidence. Thus, for Douglas values should guide our judgements about acceptable levels of inductive risk, but they should not guide our judgement of the probability that an empirical claim is true. If greater transparency reveals that values play a legitimate role in science, then it can help to allay suspicion.

Transparency is by no means an unquestionably effective measure even for building epistemic trust (John 2018; Schroeder 2019). But aside from the problems that arise for using transparency to increase epistemic trust, there are three new problems that arise if we wish to use transparency to build recommendation trust. First, confidence in the sincerity of experts is not enough to meet conditions for rational trust in the recommendations of experts. An individual expert or an expert community could disclose as much information as possible about their methods, procedures, and even value assumptions that lead to their results, without giving the public reason to accept their recommendations. In order to have recommendation trust in experts, we need to know not just that their testimony about their area of expertise is sincere, but also that their recommendations are in our interest. Our confidence in this is not secured by transparency alone.

Perhaps this requires simply that our attempts to increase public transparency of science focus specifically on the values, goals, and ends that inform expert recommendations, thus allowing the public to judge for themselves whether the values of the experts align with their interests. But this fails to address the other two problems with using transparency to build recommendation trust. The second problem for transparency is that the way that values inform scientific results is very often not as simple as we need it to be in order to have reliable ways of communicating this to non-experts. A basic principle of precautionary reasoning used in epidemiological modelling of infection rate may be simple enough to communicate effectively to non-epidemiologists, but transparency about the political assumptions involved in economic modelling of the effects of the pandemic could be much more difficult to achieve. Indeed, the role that values play in setting the parameters for an expert community may not even be transparent to the experts themselves; not all scientists are philosophers of science. Revealing the values that influence scientific recommendations and expert-led policy might sometimes be possible, but often such transparency is highly impracticable.

But even if we can achieve transparency, it is not clear that it will benefit recommendation trust in the same way it can benefit epistemic trust. This leads to the third problem with transparency. One of the purported benefits of transparency is to show non-experts that values are playing the role they should play in science. Provided that everything is running as it should—that the science in question is trustworthy—transparency can allay suspicion that values play an illegitimate direct role. But this relies on a distinction between direct and indirect use of value judgements that does not apply to expert recommendations. Values must play a direct role in a recommendation because values must feature in the reasoning that supports the recommendation. There is thus nothing to be gained simply by showing non-experts what role values play in an expert recommendation, because there is no relevant distinction between more or less legitimate roles for values to play in such recommendations.

In fact, showing the public that their interests are aligned with the values informing science is not just an unhelpful and often unworkable step, but it is an unnecessary step.[13] For my trust in an expert recommendation to be rational, I need to have well-placed confidence in the alignment of the ends of the recommendation and my own ends. But confidence in this can be secured through means other than first learning about the values that inform the expert recommendations and then comparing them with my own. Instead of allowing the public to examine recommendations through transparency of values, we could instead secure confidence in the alignment of values through building public values into the procedures used to arrive at recommendations. If I have good reason to believe that my interests have played a significant role in the procedures used to arrive at expert-led policy, then I need not examine each element of the policy and each expert recommendation for alignment with my interests, because confidence in the procedure can provide confidence in the policy outcome.

5. DEMOCRATIZED SCIENCE AND ITS LIMITED VALUE FOR RECOMMENDATION TRUST

How might we build public interests into decision-making procedures in a way that supports recommendation trust in experts? Many have proposed a range of measures for democratizing science to build public trust in experts, but, again, not all of these proposals will help us deal with the extra demands when building trust in expert recommendations. One popular option is James Fishkin’s deliberative polling (2009).[14] The deliberative polling process reaches policy verdicts through face-to-face deliberation between representative samples of the population, informed by relevant scientific information and bound by norms of appropriate discussion. The role of experts in the process is to explain the relevant scientific consensus, where there is one, and as much as possible the relevant concepts, methods, and standards of evidence used in reaching that consensus. Citizen participants are also informed of the most significant robust opposition to the consensus, with an opportunity to learn about the reasons that could be given for dissent, and to hear more from the experts about their defence against objections. Non-expert participants are thus given opportunities to resolve doubts as much as possible before coming to a collective conclusion about the correct policy decision, informed by the expert advice.

As Elizabeth Anderson has noted, one of the virtues of Fishkin’s deliberative polling model is that there is evidence that such a procedure mitigates the effects of cultural cognition, a social psychological phenomenon in which individuals are more likely to accept information that is compatible with their existing values and to deny information that challenges those values (Anderson 2011, 158). Interaction with participants with other political views and a much more extensive interaction with experts than would usually be the case can help to increase the chances that a non-expert will respond to the data regardless of whether they affirm previously held convictions.

But the distinctive challenge of generating recommendation trust in experts is not to overcome cognitive bias. Even if the outgroup prejudice against experts is overcome through deliberative polling, a non-expert participant could still be warranted in refusing to accept what the experts tell them when the experts are issuing recommendations and not just giving factual testimony. Deliberative polling could successfully disabuse a citizen of epistemic prejudice against expert testimony without thereby giving them a reason to accept that the same epistemic-trustworthy expert is issuing recommendations that are in their interest. If this is the case, as I have argued above, the citizen will have good reason to epistemic-trust the expert without having good reason to recommendation-trust them.

Perhaps deliberative polling is used to tackle the problem not by showing citizens they have good reason to recommendation-trust, but instead by eliminating the need for recommendation trust in the first place. It could be that in deliberative polling experts no longer play the role of issuing recommendations for policy, and instead they simply provide information for the non-expert deliberators to use in their collective policy verdicts. But though this might be valuable so far as it goes, it leaves us without a solution for the emergency situations in which expert-led policy, trusted by the public, is desirable and cannot be substituted with policy decisions made solely by novices. As I have argued in Section 2, this is precisely the kind of scenario we find ourselves in during the COVID-19 pandemic.

There is another way to secure confidence in the alignment of public interest and expert recommendation that relies on neither transparency nor novice participation in policy deliberation. We can look instead to the way in which science-led policy is communicated to the public. In addition to Fishkin’s deliberative polling model, Anderson (2011) proposes two other means by which we can overcome cultural cognition and persuade the public to become better disposed to trusting experts where indeed they have good reason to do so.

The first, “expressive overdetermination,” is borrowed from Braman, Kahan, and Grimmelmann (2005, 297): investing policy with multiple meanings such that it can be accepted from diverse political perspectives. Braman et al. cite French abortion law reform as an example of this. After decades of disagreement, France adopted law that made abortion permissible provided the individual has been granted an unreviewable certification of personal emergency. Evidence that such an approach would be effective pre-existed the new law, but such evidence had proved unconvincing to concerned parties. This new policy was sufficiently polyvalent to be acceptable to the most important parties to the debate; religious conservatives understood the certification to be protecting life, while pro-choice advocates saw the unreviewable nature of the certification as protection for the autonomy of women. With this framework in place, acceptable to all, opposing sides to the debate were able to converge on the details of implementation (ibid., 298).

Anderson’s second alternative is to recruit spokespersons who are identifiable to diverse groups as similar to them in political outlook. The strategy is to overcome cultural cognition by convincing citizens that the relevant scientific consensus is likely not to be a threat to their values because that same consensus is accepted by those with similar values. Anderson cites Barack Obama establishing links with Evangelical Christians such as Rick Warren, one of the 86 evangelical leaders who had signed the Evangelical Climate Initiative two years before the beginning of Obama’s presidency (Frazier-Crawford Boerl 2010, 153). She suggests that Obama’s public association with Warren was an attempt to win over conservative Christians to his climate-change policy. Braman et al. call this “identity vouching” (2005, 297).

Can these strategies for communicating science to sceptical publics also work for building recommendation trust? I believe they can, with the right caveats. First, given that we are looking for measures to build well-placed recommendation trust, it must be the case that the evidence-based policy that is communicated through expressive overdetermination and identity vouching is in fact in the interests of the public whose trust we are soliciting. These strategies could also be used to mislead the public into accepting recommendations from experts that are not in their interest, if, for instance, the spokespersons are dishonest about whether this is the case. But this would not be a strategy to cultivate well-placed recommendation trust, because the public would not have good reason to trust such recommendations.

Second, if we are to use these strategies specifically for recommendation trust, the goal of the strategies is different, and this will likely affect the details of how we implement them. Expressive overdetermination and identity vouching support epistemic trust by encouraging citizens to believe expert-testimony that would otherwise be resisted as a threat to those citizens’ values. The same strategies support recommendation trust only if they encourage citizens to see that the relevant expert recommendations are in their interests. But it is not difficult to imagine how these strategies could do this. Braman et al. (2005, 297) suggest that French religious conservatives were more willing to accept the evidence in favour of abortion law reform once they saw that the law affirmed the sanctity of human life. However, it is also likely that this adjustment gave those same religious conservatives good reason to believe that this policy was in their interests (“If you want a policy that respects the sanctity of life, this is the policy for you.”). Similarly, evidence-led policy could be presented to the public by spokespersons whose interests are already thought to align with the relevant members of the public. Thus, an American Evangelical Christian might think that if recommendations to cut carbon emission are good for Rick Warren, then they are good for them too.

With these caveats, using these communication strategies to cultivate recommendation trust is, I submit, preferable to other proposals. Expressive overdetermination and identity vouching avoid the problems of transparency measures: they demonstrate specifically that public interests align with expert recommendations, and  they do so without relying on novices (or even experts themselves) understanding the complex ways in which expert values shape scientific recommendations. And these communication strategies also provide an approach that is preferable to deliberative polling in times of crisis. When an emergency situation precludes a lengthy process of expert-informed citizen deliberation, expert-led policymaking might be necessary. Where this is the case, trust must be won by demonstrating to the public that expert recommendations are in their interest.

6. CONCLUSION

The account I have given offers reasons for a cautious optimism about the possibility of building well-placed trust in science-led policy. I am afraid I will conclude on a more pessimistic note. I have argued for the view that there are additional challenges to rational trust in experts when those experts are leading public policy and not just providing policy-relevant information. The additional demands of this kind of trust boil down to three claims that I have argued for: recommendation trust is different from both epistemic and practical trust; the conditions for rational recommendation trust are more demanding than the conditions for rational epistemic trust; and many measures that have been proposed to cultivate trust in experts do not help to cultivate recommendation trust in science-led policy. The measures that can help involve communicating science-led policy to the public in a way that allows the public to see, where it is indeed the case, that it is in their interest to follow the policy.

But the success of such a strategy is likely to be limited by factors that I have not had space to address. One such factor is the fragility of public confidence in the very idea of science-led policy. Where governments present their policy as technocratic, only for their claim to be “following the science” to be exposed as false, citizens will have good reason to be suspicious of future policy that is sold to them on a similar basis. Another significant factor is the broader climate of public trust, most notably the levels of public trust in politicians and government. Perhaps science-led policy is the product of experts and politicians working together. Perhaps science-led policy is the product of a full-blown technocracy, where experts become our political leaders. Either way, once science is corrupted by politics, its authority is vulnerable to public trust in the political system. Rebuilding this kind of trust is a much more difficult task.

REFERENCES

Anderson, Elizabeth. 2011. “Democracy, Public Policy, and Lay Assessments of Scientific Testimony.” Episteme 8 (2): 144–64.

Atchison, Christina, Leigh Bowman, Charlotte Vrinten, Rozlyn Redd, Philippa Pristera, Jeffrey W Eaton, and Helen Ward. 2020. “Perceptions and Behavioural Responses of the General Public During the COVID-19 Pandemic: A Cross-sectional Survey of UK Adults.” medRxiv doi: 10.1101/2020.04.01.20050039

Braman, Donald, Dan Kahan, and James Grimmelmann. 2005. “Modelling Facts, Culture, and Cognition in the Gun Debate.” Social Justice Research 18 (3): 283–304.

Brennan, Johnny. 2020. “Can Novice Trust Themselves to Choose Trustworthy Experts? Reasons for (Reserved) Optimism.” Social Epistemology 34 (3): 227–40.

Burge, Tyler. 1995. “Content Preservation.” Philosophical Issues 6: 271–300.

Croce, Michel. 2019. “On What it Takes to be an Expert.” Philosophical Quarterly 69 (274): 1–21.

Douglas, Heather. 2000. “Inductive Risk and Values in Science.” Philosophy of Science 67 (4): 559–79.

–––––– 2008. “The Role of Values in Expert Reasoning.” Public Affairs Quarterly 22 (1): 1–18.

Fishkin, James. 2009. When the People Speak: Deliberative Democracy and Public Consultation. Oxford: Oxford University Press.

Frazier-Crawford Boerl, Christopher Wayne. 2010. “American Evangelicals and the Politics of Climate Change.” St Antony’s International Review 5 (2): 147–63.

Fricker, Miranda. 1998. “Rational Authority and Social Power: Towards a Truly Social Epistemology.” Proceedings of the Aristotelian Society 98 (2): 159–77.

Hardwig, John. 1985. “Epistemic Dependence.” Journal of Philosophy 82 (7): 335–49.

–––––– 1991. “The Role of Trust in Knowledge.” Journal of Philosophy 88 (12): 693–708.

Holton, Richard, and Jacopo Domenicucci. 2017. “Trust as a Two-place Relation.” In The Philosophy of Trust, edited by Paul Faulkner and Thomas Simpson, 149–260. Oxford: Oxford University Press.

Ipsos MORI. 2019. “Trust in Politicians Falls Sending Them Spiralling Back to the Bottom of the Ipsos MORI Veracity Index.” https://www.ipsos.com/ipsos-mori/en-uk/trust-politicians-falls-sending-them-spiralling-back-bottom-ipsos-mori-veracity-index (Accessed 15 May 2020)

John, Stephen. 2016. “From Social Values to P-Values: The Social Epistemology of the Intergovernmental Panel on Climate Change.” Journal of Applied Philosophy 34 (2): 157–71.

–––––– 2018. “Epistemic Trust and the Ethics of Science Communication: Against Transparency, Openness, Sincerity and Honesty.” Social Epistemology 32 (2): 72–87.

Kappel, Klemens. 2014. “Believing on Trust.” Synthese 191 (9): 2009–28.

Kitcher, Philip. 2001. Science, Truth, and Democracy. Oxford: Oxford University Press

Kukla, Rebecca. 2007. “How do Patients Know?” The Hastings Center Report 37 (5): 27–35.

O’Neill, Onora. 2020. “Trust and Accountability in a Digital Age.” Philosophy 95 (1): 3–17.

Pew Research Center. 2019a. “Public Trust in Government: 1958–2019.” Accessed May 15, 2020. https://www.people-press.org/2019/04/11/public-trust-in-government-1958-2019/.

–––––– 2019b. “Trust and Distrust in America.” July. Accessed May 15, 2020. https://www.people-press.org/2019/07/22/trust-and-distrust-in-america/.

Rolin, Kristina. 2002. “Gender and Trust in Science.” Hypatia: A Journal of Feminist Philosophy 17 (4): 95–120.

Schroeder, S. Andrew. 2019. “Democratic Values: A Better Foundation for Public Trust in Science.” The British Journal for the Philosophy of Science axz023. https://doi.org/10.1093/bjps/axz023.

Watson, Jamie Carlin. 2020. “Hunting the Expert: The Precarious Epistemic Position of a Novice.” Social Epistemology Review and Reply Collective 9 (4): 51–58.

Wilsdon, James, and Rebecca Willis. 2004. See-through Science: Why Public Engagement Needs to Move Upstream. London: Demos.

Wylie, Alison. 2003. “Why Standpoint Matters.” In Science and Other Cultures, edited by Robert Figueroa and Sandra Harding, 26–48. New York: Routledge.


[1] Ipsos MORI data on public trust in the UK in November 2019 showed that 14% of the public trusted politicians to tell the truth, matching previous recorded lows in 2016, 2011, and 2009 (Ipsos MORI 2019). Data from the Pew Research Center in April 2019 showed that 17% of respondents in the US trusted the government to do what is right at least “most of the time” (Pew Research Center 2019a), but this same figure has passed 50% only three times since 1972 (ibid.).

[2] Ipsos MORI’s data show that 86% of respondents said they generally trusted professors to tell the truth, 84% scientists (Ipsos MORI 2019). Pew Research Center data from 2018 showed that 83% of respondents said they have at least a fair amount of confidence in scientists, with very little (1%) variation between age groups (Pew Research Center 2019b, 19).

[3] What is an expert? The account of trust in experts I give here will remain neutral on debates about how best to define experts. However, I am inclined to what Michel Croce (2019) calls novice-oriented accounts because the experts I am concerned with are those that play the role of providing information and recommendations to non-experts.

[4] Where decisions really are exclusively within the remit of politicians, science-led policy can only be such if politicians trust experts. The norms governing when it is reasonable for politicians to trust experts, and the measures that we can take to build this trust, might well differ from those relating to public trust in science.

[5] It is not universally accepted that trust is tripartite. For more see Holton and Domenicucci (2017).

[6] The domain restriction can also reflect a principle that underpins some standpoint epistemology: some facts about, for instance, social and political injustice are better understood by those who suffer those injustices (Wylie 2003). Thus marginalized groups might be more epistemic-trustworthy in relevant domains.

[7] Hardwig is also not without his critics (see e.g., Kappel 2014; Rolin 2002). Nonetheless, the criticisms of Hardwig that I am aware of do not give us reason to adjust his principles in ways that would threaten the distinction in norms of rational trust that I am arguing for. Demonstrating this would, I suggest, take me beyond the scope of this paper.

[8] Note my argument in this section is not an argument against Hardwig, because Hardwig does not claim his principle would apply to anything other than epistemic trust.

[9] Does this mean that Hardwig’s principle (T) is not true? (R) appears to be a more specific version of (T) insofar as it specifies the nature of the belief professed by B and accepted by A. But if (R) is entailed by (T), and (R) is false, then (T) must also be false. Given that the truth of (T) is not at stake in this paper, I will remain agnostic on this issue, though I provisionally suggest that (T) might be saved were we to specify that B’s belief is about non-moral facts—this adapted (T) would not entail (R). I thank an anonymous reviewer for raising this.

[10] Other concerns include the difficulty for novices of identifying experts. See e.g., Brennan 2020 and Watson 2020.

[11] I am also setting aside matters of practical trust in experts, not to mention practical trust in government.

[12] See e.g., Kitcher (2001, chapter 6) and Wilsdon and Willis (2004).

[13] It could also be a dangerous step, as Schroeder (2019) has argued, insofar as it could encourage non-experts to be selective about the experts they prefer to follow, and as a result it might politicize science such that scientists and the public become divided along ideological lines.

[14] This has been endorsed as a means to build trust byAnderson (2011) and Kitcher (2011, chapter 8).

Special Issue, Uncategorized

How Government Leaders Violated Their Epistemic Duties during the SARS-CoV-2 Crisis

Eric Winsberg, Jason Brennan, & Chris W. Surprenant[1]

[This is an advance copy of an article that will appear in print in September 2020 as part of the KIEJ’s special double issue on Ethics, Pandemics, and COVID-19.]

ABSTRACT. In spring 2020, in response to the COVID-19 crisis, many world leaders imposed universal lockdowns. We argue that these restrictions have not been accompanied by the epistemic practices morally required for their adoption or continuation. While in theory lockdowns can be justified, governments did not meet and have not yet met their justificatory burdens. We will not argue that less stringent policies were optimal or better justified. Rather, we explain how government leaders failed and have continued to fail to meet their epistemic duties by relying upon data, models, and evidence of insufficiently good quality to justify their actions.

Sovereign is he who provides the exception.…The exception is more interesting than the rule. The rule proves nothing; the exception proves everything. In the exception the power of real life breaks through the crust of a mechanism that has become torpid by repetition. (Schmitt 2010, 1, 15)

1.     INTRODUCTION

In spring 2020, in response to the COVID-19 crisis, world leaders imposed severe restrictions on citizens’ civil, political, and economic liberties. These restrictions went beyond less controversial and less demanding social distancing measures seen in past epidemics. Many states and countries imposed universal lockdowns. Lockdowns, as we define them here, require people to stay home; in some countries and places, citizens must have ad hoc licenses to leave their homes for any reason. Citizens are often forbidden from playing outside, e.g., by jogging alone in the park. Citizens are forbidden from gathering in groups larger than ten, and in some cases they are forbidden from visiting friends and family even in small groups. Lockdowns do not merely prohibit large gatherings, such as conferences or concerts, but also prohibit small backyard parties. Most places of work are ordered to close, resulting in mass unemployment.

In this paper, we argue that these restrictions have not been accompanied by the epistemic practices morally required for their adoption or continuation. While in theory, lockdowns can be justified, governments did not meet and have not yet met their justificatory burdens.

This paper will not attempt to assess or determine which suppression mechanisms governments ought to have imposed, either in light of the information they had or have now. We will not argue that less stringent policies were optimal or better justified. Rather, our goal is to explain how government leaders failed and have continued to fail to meet their epistemic duties. We will argue that states relied upon bad data and flawed models, and they lacked the other kinds of evidence they would need to justify lockdowns. Again, we do not thereby claim that lockdowns were bad policy, nor are we assessing how dangerous COVID-19 is. Instead, we argue that most governments have failed to meet their epistemic duties.

As a partial analogy, imagine the state strongly suspects a person is a dangerous serial killer. Suppose there is indeed some evidence he is. To ensure he does not further endanger the public, they arrest and detain him. Months later, however, he remains in prison, yet the state has not convicted him; in fact, it has barely begun to collect the evidence it needs to demonstrate his guilt. Moreover, suppose we learn that the state has made demonstrable errors in its reasoning in accusing the person of the killings. Here, civil rights lawyers might well complain that the state has not met the epistemic obligations needed to hold the prisoner. This does not mean the lawyers necessarily deny the suspect is a killer. They may not even want him set free. But to justify infringing the suspect’s rights, the state needs to be more than factually correct: it needs to have strong epistemic grounds for its claims. For state agents to imprison someone without proper evidence is a severe ethical failing. Note that we are not, in this analogy, claiming that lockdowns are equivalent to imprisonment; our point is simply to provide an example where governments are required to possess a certain level of justification before they may restrict citizens’ liberties.

2.     BASIC LIBERTIES, CONSTITUTIONAL RIGHTS, AND PUBLIC JUSTIFICATION

Liberal political philosophies regard liberty as the fundamental political value. All citizens possess an extensive sphere of individual liberty. Governments may restrict such liberties only in exceptional cases and upon meeting high justificatory burdens.

Consider John Rawls’s theory as an exemplar. Rawls’s theory claims that each person is “entitled to a fully adequate scheme of equal basic liberties…compatible with like liberties for all” (2001, 42). “Basic liberty” here is a technical concept, referring to a liberty which may not easily be overridden by concerns for social stability, economic efficiency, economic fairness, or general welfare. While non-basic liberties (such as the right to invest) may be restricted in order to promote other values (such as equity or welfare), basic liberties may not. Any reduction of basic liberties must meet standards of strict scrutiny. While trade-offs among the basic liberties are permitted, trade-offs between the basic liberties and various other social goals generally are not, except perhaps in extreme cases.

Rawls claims that not all liberties are basic. He defends an enumerated list of particular liberal freedoms, including liberty of conscience, freedom of thought, freedom of association, rights of due process and equal protection under the rule of law, freedom of occupation, and a right to own personal property (Rawls 1996; Freeman 2006, 46).

Of course, a major debate within liberalism is which liberties are “basic” in Rawls’s sense. We will not resolve this debate here. We simply remark that lockdowns restrict and reduce citizens’ basic liberties according to any major liberal theory.

The equivalent of the distinction between basic and non-basic liberties appears in most liberal democratic constitutions. For instance, in the United States, political speech is more strongly protected than commercial speech, while the right of free association for religious, political, or social purposes is more strongly protected than commercial freedom of association. For Congress to restrict citizens’ religious expression or to forbid their gathering for friendship or private events, the state must meet a high burden of justification, both in terms of the values it purports to promote through such restrictions, and in terms of the evidence it must give in support of any causal claims (Killion 2019).

Liberals have a variety of grounds for such views. Some appeal to the long run utility of rights (Mill 1859; Schmidtz 2008), others to autonomy, equality, and personhood (Rawls 1971; 1996; Gaus 2011). Others claim rights prevent state overreach (Spaulding 2009).[2]

Note, however, that the liberal position is not that basic liberties can be impeded or reduced only under conditions of strict scrutiny, while all other liberties can be reduced at will. Instead, all liberals believe in a “presumption of liberty” (Feinberg 1984, 9; Benn 1988, 87; Gaus 1996, 162–66; Rawls 2001, 44, 112; Gaus, Courtland, and Schmidtz 2018): Liberty is presumed to be normatively basic. By default, citizens are presumed free to do as they please, and by default, liberty does not need to be justified. However, any restrictions on liberty must be justified by appeal to various public values. Basic liberties can be restricted only if justifications survive strict scrutiny, while restrictions on non-basic liberties still require significant justification. The stronger the imposition and the greater the potential harm it imposes, the stronger the needed justification.

Our discussion here abstracts from these theoretical details in order to appeal to the generic principles that liberals share, and which supposedly undergird modern democratic nation-states. Liberals and constitutional democrats generally believe that (a) all restrictions on freedom must be justified, and (b) freedom cannot easily be overridden or silenced in the name of the common good, though some freedoms are more easily restricted than others. Further, liberals believe that (c) the justifications governments offer for overriding basic rights must be grounded in and appeal to public reasons and information that is appropriately available to all citizens.

3.     JUSTIFYING RESTRICTIONS IN PRINCIPLE

Nevertheless, many liberals do believe that restrictions on basic liberties, including forced quarantine and social isolation (Parmet and Sinha 2020), are in principle justifiable. Even many libertarians, whose rejection of state interference is especially strong, share this view. For instance, although Robert Nozick argues that the state may not violate rights just because doing so produces better consequences, he suggests that rights may be violated to “avoid catastrophic moral horror” (Nozick 1974, 31). Along similar lines, Jessica Flanigan (2014; 2017) and Jason Brennan (2018) argue that mandatory vaccination can be justified. Although both reject paternalistic grounds for mandatory vaccination, they agree that states may mandate vaccines to prevent citizens from imposing undue risk onto others. Flanigan argues that firing a gun in the air over a crowded place imposes an undue risk of harm upon innocent bystanders (Flanigan 2014, 6). She claims that infected people who venture into crowds behave analogously. Brennan (2018) revises Flanigan’s argument by accounting for problems of uncertainty, collective action, and overdetermination, but reaches a similar conclusion.

Thus, even libertarian liberals, despite their anti-statism, often defend restrictions on basic liberties, particularly in the name of preventing harm. In the case of mandatory vaccination, this argument is made on the grounds that the people have no right to expose others to undue risk of infection. Considering these arguments, then, one might think it trivial to justify COVID-19 lockdowns on the same grounds. Such restrictions on liberty prevent citizens from exposing their neighbors to undue risk—potentially resulting in catastrophic moral horror as infections spread rapidly through the population—and thus they are justified from a liberal point of view.

4.     EPISTEMIC CONSTRAINTS ON STATE POWER

Liberals and constitutional democrats agree that under the right conditions, states may restrict or remove people’s liberty, force them to accept medicines, deprive them of their jobs, imprison them, or even kill them. But in order to do these things justifiably, the state must meet certain conditions, including certain epistemic conditions. For example, it may not mandate an untested vaccine. It may not imprison a suspected killer without proving his guilt. It may not start a war concerning possible weapons of mass destruction on poor intelligence. It may not place citizens in internment camps on mere suspicion of disloyalty.

Epistemic norms are sometimes also moral duties (Chignell 2018). In some cases, individuals or groups have moral duties to collect good evidence, reason carefully about that evidence, engage in proper self-skepticism, and overcome their cognitive biases. This often occurs when one person is the fiduciary of another, when one person exerts significant power and authority over another, or when two people have certain contracts with each other. For instance, parents owe their children duties of care; these duties of care require parents to reason properly about issues related to their children’s welfare. Similarly, a financial advisor owes it to her clients to assess possible investment plans with high levels of competence and rational evaluation.

In recent work, Jason Brennan (2011; 2016) argues that governments have strong epistemic duties when making high stakes decisions. He motivates this idea with the example of a murder trial.

Imagine a defendant is charged with first degree murder. During the trial, both sides present evidence, question witnesses, and make arguments. The defendant will likely be executed or imprisoned for life if found guilty. Suppose the members of jury find him guilty. However, they are ignorant of the facts of the case, decide on the basis of false or pseudoscientific information, lack the cognitive capacity to understand the case, or process the information presented in the trial in irrational and biased ways. Alternatively, suppose they have improper motivations, such as malice toward the defendant, a conflict of interests, or simply want to please the judge and the press with a guilty verdict regardless of the defendant’s actual guilt.

If we knew a jury found the defendant guilty for any of these reasons, we would conclude they have acted unjustly. The jurors owe it to the defendant—and to society, as our representatives—to conduct a fair, impartial, and unbiased trial, and to reason in truth-conductive, reliable ways. In this case, we would conclude the jury’s decision should be thrown out and the trial conducted again. This judgment is reflected in the laws of many US states, which entitle a defendant to a new trial if he shows his jury had these problems.

We would not excuse the jury’s behavior if they claimed they acted on the best information available, but the available information was very bad. For instance, suppose the trial is held three days after capturing the defendant. Because of the lack of time, neither the prosecution nor the defense have much evidence for their side, and the evidence they have is of poor quality. In this case, if the jurors find the defendant guilty, they act wrongly. Saying they acted on the best available information is not sufficient justification. Instead, the evidence must meet an objective rather than relative standard; in this case, there must be no reasonable doubts that the defendant is guilty.

It would not be acceptable for a government to convict a person on the basis of poor evidence, and then collect good evidence later, after the fact. If critics complained about this behavior, it would make little sense for apologists to say, “Sure, everyone admits the government needs better evidence, which thankfully they are now, two months after the conviction, starting to collect.” The evidentiary bill comes due before conviction. Even if we discover later that the defendant was guilty, any liberal or constitutional democrat must nevertheless condemn the state’s behavior and demand the state follow pre-established rules of evidence in the future.

Liberals or democrats in the public reason tradition (e.g., Benhabib 2002; Christiano 2010; Eberle 2002; Estlund 2008; Freeman 2009; Gaus 1996; 2003; 2011; Habermas 1995; 1996; Larmore 2008; Rawls 1996; 2001; Tomasi 2001; 2012; Vallier 2018)—now the dominant paradigm in English-language political philosophy—hold that governments are subject to additional constraints. When they impose policies upon citizens, these policies must be justifiable to those citizens in light of certain publicly shared values and publicly available evidence which all reasonable citizens can accept. Governments are generally forbidden from acting on private, inaccessible, or non-public sources of information. They must instead appeal to widely shared values implicit in a democratic conception of personhood, which views everyone as free and equal (Rawls 1996; Gaus 2011). Public reason liberals in particular have reason to avoid claiming that citizens should blindly follow government leaders without demanding a public justification for their decisions.

Note that in using these analogies, we are not claiming that COVID-19 lockdowns are like imprisonment or punishment, though governments’ use of the word ‘lockdown’ does tend to push public rhetoric in that direction. Nor are we arguing that the appropriate remedy here is the same as in the case of a trial. In the case of a trial, if the state fails to meet its epistemic duties, the defendant goes free. We are not arguing that when the state fails to meet its epistemic duties, a quarantine must be immediately ended. Instead, Brennan argues that the point about the capital murder trial generalizes. When governments make high-stakes political decisions, decisions which can greatly harm people, or deprive them of livelihood, property, liberty, or even life, they are morally obligated to make such decisions competently and in good faith. What should happen when the state fails to meet its duties is a separate question that we do not address here. We simply argue that meeting the epistemic duty means relying on good information—not the best information available, but good information, period. The jury example motivates this intuition, but it generalizes to a wide range of political decisions. Below, we will explain why the COVID-19 lockdowns are “high stakes” in the relevant way, though we suspect this point is obvious.

Liberal democrats have good reason to endorse something like this in light of their own principles. They hold that certain liberties are basic and that liberty in general is normatively fundamental. Overriding, silencing, or forfeiting freedom requires that governments meet a strong justificatory burden. Governments must make such decisions using proper epistemic reasoning procedures, on the basis of good information, and while acting in good faith.

The foregoing comments provide the basic normative background of our argument. Appealing to ideas and principles shared within democratic or liberal traditions, we will show why governments have failed to meet the justificatory burdens required to legitimate the COVID-19 lockdowns. First, we will argue that the quality of the data and models used by officials was poor. We will argue that work on the philosophy of science and the reliability of experts gives us further reason to be cautious in deferring to such models. Second, we will argue (though this is far more obvious) that the decisions were extremely high stakes, imposing significant harms and costs upon people everywhere, especially those in extreme poverty. Together, this provides strong evidence that governments violated the Competence Principle and have failed to meet their justificatory burdens. We will not try to draw a precise line at which governments would meet their epistemic obligations to justify the lockdowns. Any precise line would be controversial. Instead, we will argue the information, models, etc., that governments used were sufficiently poor that they fall below any plausible line we might draw.

One might object to this entire line of argument by saying that while imprisoning a defendant is “high stakes,” so is letting him go. In the same way, lockdowns are high stakes—involving mass suppression of freedom of movement and association, serious psychological trauma, and severe economic loss—but refusing to impose lockdowns is also high stakes—as it could lead to serious death. First, as we have emphasized, we do not argue for the analog of “letting the suspect go.” We argue for no general form of remedy to the situation of states failing to meet their epistemic duties when they deprive their citizens of rights. Second, even though it is true that there is a parity of risks, it also misses the point. If one simply rejects the ideals of constitutional democracy or simply rejects liberalism, then the question of whether to impose lockdowns or not becomes a utilitarian issue. At the time lockdowns were imposed, the quality of information in support of any choice was quite poor (as we will explain below), and so from a utilitarian standpoint, it is just as difficult to justify staying open as it is to justify closing things down. But our point here is that constitutional democrats and liberals do not take all options to start on equal footing. They regard freedom as the default from which departures must be justified; the greater the imposition, the stronger the justification needed. While not all readers are liberals or constitutional democrats, these are nevertheless the dominant paradigms in political philosophy and actual political practice in the West.

5.     PROBLEMS WITH THE SARS-CoV-2 DATA AND THE MODELS

           Cooper/Smith epidemiologist Dylan Green reports the following:

I’ve been asked to generate modeling results in a matter of weeks (in a disease which I/we know very little about) which I previously would have done over the course of several months, with structured input and validation from collaborators on a disease I have studied for a decade. This ultimately leads to simpler rather than more complicated efforts, as well as difficult decisions in assumptions and parameterization. We do not have the luxury of waiting for better information or improvements in design, even if it takes a matter of days. (Cowen 2020)

When epidemiologists model an emerging epidemic, data are sparse. In constructing their models to make forecasts, they have myriad methodological decisions to make, many of which are unconstrained by data or existing background knowledge.

Consider the Imperial College London (ICL) model, which had significant impact on policy decisions in the UK and US.[3] The model was used to estimate what public interventions would be needed to prevent hospital systems from becoming overwhelmed. The model’s primary job was to predict the impact of various policy choices on demand for hospital beds, intensive care unit (ICU) beds, and the like. Thus, the model needed inputs for the expected death rate, hospitalization rate, and ICU admittance rate for each 100,000 people infected. In all, the model employed almost 700 different parameters.

At the beginning of the COVID-19 epidemic, and even now as we write this sentence, these magnitudes were not well estimated. The WHO’s early estimates used case rates from China and other early areas of infection. But case rates are directly a product of surveillance /selection bias. When medical professionals predominantly test people who demand care, the resulting data are biased toward more severe results. Not all infected people become sick, and not all sick people need treatment, but the most severely ill people are most likely to seek treatment. Early WHO estimates were extremely high, with fatality rates as high as 3.4% and hospitalization rates well into the double-digit percentages. The correct numbers are still unknown, but early estimates were clearly too high.[4]

A bar graph comparing predicted weekly ICU cases. It is labeled "Figure 4: Illustration of adaptive triggering of suppression strategies in GB, for R-0=2.2, a policy of all four interventions considered, an "on" trigger of 100 ICU cases in a week and an "off" trigger of 50 ICU cases. The policy is in force approximate 2/3 of the time. Only social distancing and school/university closure are triggered; other policies remain in force throughout. Weekly ICU incident is shown in orange, policy triggering in blue."
Figure 1. (Ferguson et al. 2020)

The ICL model is a massive extension of so-called “SIR” models. SIR models divide an epidemiological population into three groups: Susceptible, Infected, and Recovered. SIR models excel at explaining, in retrospect, why epidemics tend to fit a familiar curve pattern. But to be useful for making policy recommendations, such as closing schools, ordering people in general to stay home, ordering the elderly in particular to stay home, closing restaurants, etc., SIR models must be considerably more complex. Each of the three main groups must be now divided—for example, into age categories, into those that stay at home, go to school, go to work, etc.

Let’s examine the ICL model in further depth. The ICL code creates a hypothetical random population for each country it models. Each individual is assigned to a household and, depending on age, to a school/university or workplace. (The sizes of these are chosen in proportion to their real values in the world.) The model is then simulated in six-hour steps; it determines the probability that each individual gets infected based on where s/he is in the model, and then randomly decides (against a background probability estimate) whether each individual is infected, and what happens to infected individuals (hospitalization, death, etc.).

There are a huge number of decisions behind such models. One must choose and code in a death rate, hospitalization rate, and rate of admittance to intensive care; one must choose a time step (which can have a large impact, since people move around in the world on a diurnal basis, and the time step is a significant fraction of the day), as well as the probability of infection at work, school, or at home.

For example, the ICL model assumes that when people socially distance, their probability of getting infected at home increases by 25%. But why 25%? Why not 35%? In fact, there is no data or research to support any particular choice in the model, since we have few well-established rates for any past virus, let alone rates for the novel SARS-CoV-2 virus. In retrospect, it appears now that SARS-CoV-2 is particularly virulent at home, relative to other places and relative to other viruses (Qian et al. 2020). There was enormous uncertainty concerning nearly every parameter built into the model’s coding. Most modeling choices were relatively unconstrained by data or background knowledge; when there was data, it was of poor quality. Our complaint here is not that the ICL model relied upon hundreds of parameters, but that the inputs into these parameters were largely arbitrary and unsupported by evidence.

A single run of the ICL model requires about 20,000 processor hours. It was impossible, on short notice, to explore how varying the (largely arbitrary) parameter values would impact the model’s predictions.[5] It was impossible to determine to what extent the model’s predictions were robust under varying parameter values. Indeed, now that a cleaned-up version of the model’s code is available, it is clear that the ICL model can generate significantly different estimates even with the same parameters inputted. In the end, therefore, the outcome of the simulation was highly dependent on the largely unconstrained choices that the modelers had to make, as well as on chance.

In a recent working paper, economists Christopher Avery et al. (2020) identify many other shortcomings of the major models, including the ICL model. These include failing to account for heterogeneity in degree of viral exposure, failing to account for endogenous behavioral changes (such as that people will self-isolate or reduce their contact with others as the disease spreads), a lack of parameters for hospital capacity, and a lack of parameters for underlying comorbidities. The authors complain, as we do, that many of the assumptions in the SIR and related models are ad hoc and unsupported by evidence, that the arbitrary choice of parameter values greatly changes the models’ predictions, and further that the data fed into these models suffer from heavy selection bias. They conclude that the “each type of model can be reasonably well-calibrated to an initial period of spread of disease, but further assumptions, often necessarily ad hoc in nature, are needed to extend either type of model to later phases of an epidemic” (Avery et al. 2020, 13).

It is no wonder, then, that the model performed poorly at anticipating ICU demand, which was at the heart of the policy recommendations that emerged from the model. Recall that the ICL scientists recommended a policy of “maximum suppression”(Ferguson et al. 2020). This was the most draconian set of policies the group imagined. They anticipated that even maximum suppression would at first barely avoid overwhelming the UK’s existing ICU and ventilator capacity, and it would then require cycling the economy on and off until a vaccine was available. Despite less than maximum suppression, this did not occur. It projected, for the US, that unless maximum suppression measures were used to “reverse epidemic growth, reducing case numbers to low levels and maintaining that situation indefinitely,” the US would experience over a million deaths (Ferguson et al. 2020). On March 20, 2020, Ferguson told reporter Nicholas Kristof that the US’s “best-case” scenario with moderate social distancing would be 1.1 million deaths (Kristof 2020).

A strong indictment of the ICL model comes from examining what it would have predicted for Sweden, which has not implemented any lockdowns. Of course, ICL never ran their model on Sweden, but the model has few country-specific inputs. A group of epidemiologists based in Sweden, Belgium, and the United States (Gardner et al. 2020, 31) ran a model very closely based on the ICL model[6] using parameters adjusted for Sweden’s population density, demographics, etc. They reported, “Our model for Sweden shows that, under conservative epidemiological parameter estimates, the current Swedish public-health strategy will result in a peak intensive-care load in May that exceeds pre-pandemic capacity by over 40-fold, with a median mortality of 96,000 (95% CI 52,000 to 183,000).” Their best-case estimate, if Sweden used maximal suppression and lockdown techniques, was that Sweden would have over 15,000 deaths by the end of April. Of course, Sweden is not actually suffering from overload of its healthcare system. According to their article, Sweden under its current policies should be crossing 70,000 deaths sometime in the next week. As of this writing on May 19, 2020, Sweden has experienced 3,743 deaths from COVID-19.

It’s unclear what the ultimate death toll will be in the US or the UK. But it is clear that this and other models’ projections of ICU and ventilator demand were overly pessimistic. (See Figure 1 above.) Note, also, that the ICL and most similar models did not make projections for deaths of individuals in nursing homes or other critical care facilities.

Another egregious (though not particularly exceptional) example of modeling failure can be seen in the projection stated by New York State Governor Andrew Cuomo on March 25, 2020, that, unless the state went into severe lockdown, it would need 40,000 ventilators by April 7, but that the best case scenario was a need for 40,000 ventilators by April 14. Here are the actual data according to covidtracking.com/data/

A chart, showing the two predictions of levels of ICU beds needed, compared to actual ICU beds used in New York. The predictions called for 40,000 beds needed by 4/7 or 4/14, and in fact, at most only 5,039 beds were needed.

Figure 2. (Adapted from https://twitter.com/ElonBachman.)

Here, Cuomo relied on a regression model of the kind used by the now famous Institute for Health Metrics and Evaluation (IHME). The IHME is a “mixed effects non-linear regression framework” (IHME 2020). It basically takes death, hospitalization, ICU, and ventilator data, as well as the date that particular location has gone on lockdown as inputs, and then fits it to a modified Gaussian curve that looks like the red and yellow lines in Figure 2. The projections of the IHME models of hospitals’ needs, ICU needs, and deaths, for each state, are now legendary for their poor performance and frequent massive updating. These failures have not been limited to New York. For example, consider the IHME’s central projections for how many ICUs the state of Florida would need on April 20, 2020. On the April 7 version of the projection, it was 2,409 units. By April 13, that number had fallen to 763. By the seventeenth, it had fallen again to 354.[7] These were not minor changes, given that Florida was said, at the time when the first projections were released, to have only 1,695 ICU beds available. So, the model predicted on the seventh a large and rapidly approaching shortage, which turned on the thirteenth into a long-delayed shortage, and then finally into a lasting surplus on the seventeenth. As one recent survey put it, “the true number of next day deaths fell outside the IHME prediction [95% confidence] intervals as much as 70% of the time, in comparison to the expected value of 5%” (Marchant et al. 2020). The IHME model has consistently performed far worse than chance, even as the modelers revise it in light of new data.

Given the internal deficiencies of the models being used to justify the policy responses to COVID-19 (such as lockdowns), we might hope that the models themselves (and the policy recommendations stemming from them) would be bolstered by empirical evidence from past pandemics. However, a literature search reveals there are no published, peer-reviewed papers demonstrating the effectiveness of universal lockdown procedures to combat any epidemic. To be clear, there are papers showing that closing schools reduces flu transmission in children (e.g., Chowell et al. 2014). There many papers demonstrating the effectiveness of centralized quarantines, in which infected individuals are confined in designated state facilities. But we lack empirical evidence that extensive lockdown policies or maximal suppression work at all, never mind that they are superior to other, less draconian practices. In Paediatric Respiratory Review, Rashid et al. (2015) survey and review eighty major studies examining various kinds of mild to moderate social distancing (though not lockdown) measures imposed in response to the 2009 influenza pandemic. They note that most papers conclude that social distancing measures are “moderately effective,” but at the same time, they find that “overall, the quality of the evidence was quite weak, drawing primarily on observational or simulated data.” Only one of the eighty papers used “more established methods” such as quasi-randomized control trials (Rashid et al. 2015).

The best paper we can find defending lockdowns is a working paper by Friedson et al. (2020), but this paper has significant limitations. In particular, it counts drops in deaths five days after California’s closing as evidence that lockdowns work. Since the virus takes longer than that to incubate, this drop could not have been caused by the lockdowns.

Issues like these are not unique to the field of epidemiology. On the contrary, we have strong grounds in general to be skeptical about experts’ predictions on hard problems. For instance, in Expert Political Judgment, Philip Tetlock (2005) examined nearly 83,000 predictions made by experts in a variety of fields. He focuses on what the experts themselves consider hard problems rather than easy problems. In general, he finds that on such questions, experts performed poorly, barely better than Berkeley undergraduates. Tetlock’s work warns us against simply “deferring to the science” on hard predictions, since the science in fact shows the scientists are bad at such predictions.

Basic liberties are not to be suspended lightly. Governments must meet high standards of evidence before doing so. We might debate just what the standards need to be to justify lockdowns. However, as the forgoing discussion shows, the actual quality of evidence was quite poor. No plausible theory claims governments may engage in the mass suppression of civil and economic liberty on the basis of poor evidence.

6.     PROBLEMS WITH THE MODELERS AND POLICYMAKERS

Why did so many expert epidemiologists fail so badly, or rely on speculative parameters within their models? Why did so many liberal democracies massively restrict their citizens’ civil and economic liberties on the basis of poor levels of information? Here, we turn from critiquing the models to reminding readers of what the literature on the philosophy of science tells us about the modelers themselves (Douglas 2000; 2009; Winsberg 2012; 2018; Parker and Winsberg 2018; Rudner 1953; Hempel 1965). Philosophers of science have long recognized that when scientists face unconstrained modeling decisions, their choices are often strongly influenced by their social and ethical values—as well as the various pressures the scientists are under. Insofar as the way we design our models has a strong effect on which policies the models will tend to make look attractive or unattractive, these underlying choices can play an important role in determining how useful a model is for guiding complex public policy decisions.

By way of illustration, suppose you would like to use a scientific model to help decide which of two policy choices you ought to implement. But in making the model, there are two ways you can proceed. On the first way of designing the model, the first policy option ends up looking attractive. On the second approach, the second policy option looks more attractive. Which model do you go with? What if both approaches seem reasonable on the basis of the limited evidence you have? This kind of dilemma is very common when model builders face methodological choices.

One way of resolving this dilemma is to ask which version of the model aligns the balance of inductive risks in the way that accords with your values. For instance, consider the ICL model and the choice of value for the parameter representing the probability of infection transmission at home while socially isolating. If you assume that the probability of getting infected at home goes up by 25% while socially isolating, this makes social isolation look far more attractive than if you assume that the probability of getting infected at home goes up by 35% while socially isolating. If you think that social isolation is the more prudent policy, because you think that risking losing lives to disease is a more serious risk than risking losses to the economy or to political freedoms, this may be reason enough to choose the former specification. The reader might think this is a small change. And indeed, maybe it is. But a model with almost 700 such unconstrained choices, each of which produces non-linear effects on the model output, creates a highly flexible model.

Alternatively, you might consider what will happen if you choose the wrong approach. Imagine that you are an epidemiologist who faces the kind of pressures that Dylan Green describes—asked to instantaneously deliver policy-defining predictions about a disease you know little about, with potentially hundreds of thousands of lives on the line. What are you to do, particularly when you have no independent evidence upon which to determine the correct value of that parameter? Any choice you make will reflect a value decision about the danger of overpredicting deaths vs. the danger of underpredicting deaths. We hope it will not be terribly controversial to say that epidemiologists, faced with Green’s pressures, are inclined to avoid underpredicting rather than overpredicting deaths (see, e.g., Green and Farahany 2014). They will be inclined to recommend policy choices that minimize the risk of death as opposed to, say, minimizing the chances of overreaction. Moreover, they will focus primarily on reducing the risk of death by disease—given that this is the subject of their expertise—and not on potential collateral damage resulting, for example, from hunger and dislocation that might result from an overly aggressive policy choice. The nature of the work they do directs their attention more to the damage caused by viruses like COVID-19 then to damage done by economic loss or reduction of political freedom. The consequences to themselves, their careers, their discipline, their own sense of moral culpability will be much larger if they underpredict rather than overpredict death by disease. It is the primary social role and responsibility of epidemiologists to focus on avoiding disease. It is their role to make their best guess when information is lacking. In contrast, it is the social role and responsibility of policymakers, and our political representatives, to make policy decisions that reflect the whole spectrum of our moral values. It is their role and responsibility to make the hard decisions and to take uncertainty and scientific ignorance into account.

Given these influences, it is unsurprising to find a great deal of evidence from past experiences that epidemiologists favor a balance of inductive risks that leads to over-forecasting the severity of diseases. The infection fatality rate of Mad Cow Disease, H1N1, H5N1, H7N9, and MERS all were considerably lower than what epidemiologists predicted. And while SARS 2002 actually ended up being twice as fatal as originally predicted, its infectious spread was tiny compared to what they predicted (Yu et al. 2013; Wang, Parides, and Palese 2012; Lipsitch et al. 2015; Cauchemez et al. 2014). Repeated cases of overprediction can even be diagnosed in single individuals. For example, Neil Ferguson, the famous epidemiologist behind the ICL model, has often overestimated disease dangers. To cite one example, he claimed in a 2001 New York Times article that it would be “unjustifiably optimistic” to think Mad Cow Disease would kill only a few thousand people; his group claimed it would kill around 136,000 (Blakeslee 2001). So far, the actual number of deaths, after 20 years, is under 200. In 2005, he told the BBC that the deaths from bird flu could be between 5,000,000 and 150,000,000; the actual number was around 300 (Sturcke 2005).

These reflections should give us pause in endorsing restrictions on citizens’ basic liberties that are rooted solely in expert policy recommendations during crises. Government leaders may claim that their actions are justified purely in deference to expert recommendations regarding SARS-CoV-2. But we have strong empirical evidence that experts in most fields are systematically awful at making predictions in difficult situations that require them to predict the effects of untried policy measures on a brand new, poorly studied, and poorly understood problem. As a general matter, the demand that we simply defer to what scientists tell us is based on a largely falsified theory of scientific expertise.

Even so, it might be appropriate, at the beginning of a potential catastrophe, for policymakers to adopt a very cautious stance. In doing so, it might be excusable to accept, provisionally, the extremely cautious predictions of epidemiologists, despite the problems in their data and models. It might be fine to act first and ask questions later. It should be stressed that even this concession is questionable—after all, governments must have strong and solid evidence, rather than poor evidence, that a potential disaster of a certain size is occurring in order to justify their behavior. Historically, “we must avert disaster” has been the main excuse for government overreach. But even so, as Nozick (1974) rightly observes, the potential to avert “catastrophic moral horror” through speedy action can license many responses that would normally go beyond the pale.

Regardless, this kind of justification will not do beyond the very short term. Even in the direst emergencies when immediate action is required, we expect policymakers to supply the needed justification shortly thereafter, to rely upon established standards of evidence, to rely on high quality evidence, and to show their work in which they balance various social and ethical values against each other.

For all the reasons outlined above, it will not do, in more than the very short run, for policy makers to declare, as Governor Newsom of California has done, that they are simply “following the science” in responding to a crisis like the COVID-19 pandemic. In the interest of transparency, they should make it clear that they are adopting precautionary reasoning and inform their constituents what the plan is to quickly move to a more substantive cost-benefit analysis—and explain what values are to undergird that analysis. But states are under more substantive obligations as well. They should begin collecting the data needed to properly assess their strategies and determine whether continued restrictions of citizens’ basic liberties are justified. The longer they neglect to take measures like these, the more their impositions look incompatible with the foundational commitments of liberalism.

Making decisions under uncertainty is hard. It is likely impossible to avoid over- or undervaluing various considerations depending on social mood and other similar factors. But one thing that can help mitigate the influence of individual scientists’ values on the advice they offer to policy makers is to follow established methodological standards.

Policy makers have a moral obligation, as soon as they are even considering restricting the political and economic rights of citizens, to immediately begin gathering the best and most systematic data available. We do not try suspected criminals in the absence of standards of how to evaluate DNA or fingerprint evidence. Likewise, we should not be reacting to fears of pandemics by limiting people’s rights in the absence of clear standards regarding how to collect and evaluate evidence of the severity of the threat we face from such a pandemic. In responding to the 2020 SARS-CoV-2 pandemic, however, Western governments have largely failed to put such standards in place, or even to collect evidence in a minimally adequate way.

Consider that it quickly became clear that SARS-CoV-2 case counts undercount actual infections. To some extent, this undercounting was inevitable: we could have easily predicted that some amount of infection would be asymptomatic, and the widespread lack of adequate testing capacity meant that tests could not be administered to all suspected victims. But it is indisputable that undercounting went beyond these factors. In every case where there have been “natural experiments” with SARS-CoV-2 infections—on cruise ships, navy ships, among women giving birth in hospitals, in testing people experiencing homelessness, prisons, etc.—it has been made clear that infection is much more widespread than case counts suggest, although we do not know quite by how much.

One very promising avenue for filling this hole is antibody serological testing. If you can test a representative sample of a population of people with such tests, and you know their rate of false positives and false negatives, you can very easily, with a reasonably large sample, get a very good picture of how much infection there is. But very little of this testing has taken place, and what testing has been done has failed to appease skeptics who have legitimate worries about how representative the sampling is. As a general matter, we know that small n studies will be biased toward false positives. Worse, we still have no clear sense of what the rate of false positives and false negatives of these tests are.

Yet, these problems would be relatively trivial for well-organized policy makers to fix. Around the world, governments have imposed unprecedented and dramatic restrictions on citizens’ civil and economic freedom. For instance, at least 30 million Americans have so far lost their jobs. Governments could easily have opened a few blood banks storing SARS-CoV-2-free blood and run 5000 tests on these antibody kits to determine their rate of false positives. They could have done extensive representative sampling of citizens in various locations around the country and sample the rate of infection using both blood testing and PCR testing. But governments have not done this, even now. They should have done much of this testing beforehand. The balance of civic considerations here makes little sense. It is as if generals decided to invade a foreign shore but chose not to acquire aerial photographs of the enemy’s defenses.

We have been criticizing the major public models and data which various world leaders reference as justifying their actions. We admit it is possible government leaders have private, classified, and otherwise non-public data and models of higher quality which would justify their actions. Nevertheless, we remind readers that in liberal, democratic, constitutional governments, acting on such private information and refusal to disclose such information is prohibited except in truly exceptional circumstances. We can understand not disclosing military secrets, but the SARS-CoV-2 is not a strategic actor which would take advantage of classified information. Governments must disclose their best information to the public.

Before moving on, it should be emphasized that while although we have criticized the quality of the COVID-19 data and the models which policymakers have used—and while we criticize policymakers’ deference to such models—our core contention is not that the danger of SARS-CoV-2 has been overstated, or that lockdowns were the wrong policy to adopt. Nor is our aim to establish what the optimal suppression strategy would have been in light of what information governments had. (Doing so would require an extensive cost-benefit analysis, which would take another paper’s worth of work at least.) Our concern is more procedural in nature. Whether or not governments have encountered correct information or adopted the right policies, the process by which they have made their determinations cannot be reconciled with basic liberal commitments. States must meet strong epistemic standards if they are to justifiably restrict their citizens’ basic liberties, and they have failed to do this. This failure cannot be dismissed by saying that the governments got it right in the end. By analogy, if we criticize a colleague’s data and evidence, her model, and her reasoning process, we are not thereby claiming to know the paper’s conclusion is false. A poorly researched paper could still have a correct conclusion. But without performing the appropriate epistemic work, our colleague would still be unjustified in drawing that conclusion, and we would be justified in criticizing her right to assert it.

Academics frequently make bold claims in journals or public opinion pieces, and the bolder an academic’s claims the more likely he will receive attention for his work. For academics, there are often no negative consequences for being wrong, even horribly wrong. But for policymakers, especially chief executives, the story is far different. State governors, mayors, and other chief executives can order their citizens to stay in their homes, to close their businesses, and otherwise make themselves dependent on the state for their survival because all of these orders can be backed up by overwhelming force. Even when policymakers do not issue formal orders but provide strong suggestions for how citizens should behave, these suggestions are taken seriously by most people and impact how they choose to live their lives.

7.     THE HIGH STAKES

As of April 20, 2020, governors of 42 US states have issued stay-at-home orders to slow down the spread of COVID-19 (Mervosh, Lu, and Swales 2020). Political leaders around the world implemented similar measures. Almost without exception, political leaders claim such drastic measures are necessary because people will otherwise die. But the lockdown has caused and will cause deaths as well—along with a range of other maladies. Deaths connected to layoffs that are the result of COVID-19 might already be in the same ballpark as the number of deaths caused by the virus itself (Cordle 2020), and, over the long-term, we are likely to see more deaths and a decreased life expectancy connected to rising unemployment (Forster 2018). Reports of child abuse and domestic violence have both increased significantly since the stay-at-home orders have taken effect (Taub 2020; Da Silva 2020). Hospitals are laying off staff and closing from a lack of revenue as most procedures are postponed. Deaths from untreated cancer will increase in the long-run. Many businesses deemed “nonessential” will also die because they have been forced to close, even if there was no good reason to close them—hobby shops, specialty food stores, cobblers and tailors, art studios, various factories. We do not equate the death of a business with a death of a person, of course. But for many business-owners, their businesses are not merely the means to support their families but also life projects from which they derive meaning and fulfillment. Further, mass job losses and workplace closures will have serious negative effects on citizens’ welfare. These decisions should not be taken lightly, especially as we do not know how to model the long-term economic effects of shutdowns.

The stakes are higher in poorer places. UN officials complain that the COVID-19 shutdowns may lead to “famines of biblical proportions” (McNamara 2020). Of course, such dramatic claims partnered with requests for money should be taken with a grain of salt. (After all, the same dynamics that led epidemiologists to overpredict the impacts of SARS-CoV-2 hold for the UN’s forecasts.) Nevertheless, the point remains that putting, say, 30 million relatively rich Americans out of work is one thing; putting those in extreme poverty out of work (while also possibly shutting down food supply chains) is another.

As we have emphasized throughout this paper, these mandates also impact civil liberties. Evacuation and shelter-in-place orders normally are issued when there’s an immediate threat that is visible or otherwise easily recognized by everyone in the community—natural disasters, active shooters, etc. For the COVID-19 pandemic, there were far more unknowns than knowns about the level of the danger when shutdown orders were given. Citizens will tolerate government restrictions to basic civil liberties from immediate, known dangers. But when we allow these restrictions even under circumstances where there are so many unknowns, we create conditions susceptible to abuse and oppression, especially for members of historically disadvantaged groups. And we are seeing this situation play out now.
Expanding the conditions under which the state is willing to impinge on civil liberties requires us to broaden the conditions under which agents of the state are directed to use force against citizens who are not complying with these mandates. In the US, this will often create situations in which citizens are subjected to police interventions. Invariably, some of these end in the death of citizens who are unarmed or otherwise doing nothing wrong. These encounters are especially dangerous for members of historically disadvantaged groups. Initial data surrounding the enforcement of COVID-19 orders have shown that these orders have been disproportionately enforced against minority citizens. In New York City, nine out of ten people arrested for COVID-19-related issues have been Black or Hispanic (Associated Press 2020). In Ohio, Black Americans were four times more likely to be charged with violating stay-at-home orders than White Americans (Kaplan and Hardy 2020), even though in Ohio White Americans make up 79% of the population while Black Americans make up only 12% (State of Ohio 2019). As more arrest data starts to trickle out in the coming weeks and months, similar data is likely to come out from cities across the US.

It’s clear that lockdown orders are high-stakes decisions which significantly harm certain people, impede their liberties, and deprive them of their livelihoods. They reduce people’s freedom to work, freedom to associate, and freedom of movement. To what degree they impede basic vs. non-basic liberties will vary from liberal theory to liberal theory. Our point here is simply that these are high-stakes decisions, and thus subject to the epistemic considerations we defended above.

8.     SUMMARY AND CONCLUSION

Government officials must meet certain evidentiary standards before they detain someone. They must meet stricter standards before they arrest them. They must meet stricter standards to hold that person in prison before trial. They must meet even stricter standards to convict that person and imprison them over the long term. Even if one thinks a particular suspect is in fact guilty, it is nevertheless crucial in the name of preserving the rule of law and protecting constitutional rights to hold the government accountable if it fails to meet its epistemic duties. Likewise, in cases of such failure, it is important to demand better behavior in the future. Emergencies and dangers are often pretexts for government overreach and abuses of power, and it is precisely when the stakes are highest that government officials must use the best possible epistemic practices.

This paper offers a general indictment of government leaders across the world, though the specifics vary from leader to leader. The models and data used in support of lockdowns were poor. There was not sufficient evidence to justify lockdowns over other less restrictive policies. Governments did not and have not yet collected the data needed to continue their practices. Even if aggressive actions were initially excusable in the name of precaution, such pretexts cannot be sustained now that governments have broadly failed to remedy the deficiencies in their epistemic positions. Even if governments had acted on the best available evidence­ at the time—a highly controversial claim—nevertheless, the information and evidence available was objectively poor, as we argued above. To suppress liberty, they must act on sufficiently good information, not merely the best available information.

Again, we are not thereby making any claims about which suppression policies governments should have implemented in the short or longer term. We claim only that governments have systematically failed to meet their epistemic obligations in this crisis and that, for this reason, their actions cannot be reconciled with the values of a free society.

REFERENCES

Associated Press. 2020. “9 Out of 10 People Arrested for Coronavirus-Related Offenses in NYC Have Been Black or Hispanic.” Time, May 12. Accessed May 14, 2020. https://time.com/5835815/nypd-coronavirus-related-arrests/.

Avery, Christopher, William Bossert, Adam Clark, Glenn Ellison, and Sara Fisher Ellison. 2020. “Policy Implications of the Spread of Coronavirus.” National Bureau of Economic Research, Working Paper 27007. http://www.nber.org/papers/w27007.

Benn, Stanley. 1988. A Theory of Freedom. New York: Cambridge University Press.

Benhabib, Seyla. 2002. The Claims of Culture: Equality and Diversity in the Global Era. Princeton: Princeton University Press.

Blakeslee, Sandra. 2001. “Estimates of Future Human Death Toll from Mad Cow Disease Vary Widely.” The New York Times, October 30. https://www.nytimes.com/2001/10/30/health/estimates-of-future-human-death-toll-from-mad-cow-disease-vary-widely.html.

Brennan, Jason. 2011. “The Right to a Competent Government.” Philosophical Quarterly 61: 700–24.

––––––. 2016. Against Democracy. Princeton: Princeton University Press.

––––––. 2018. “A Libertarian Case for Mandatory Vaccination.” Journal of Medical Ethics 44: 37–43.

Cauchemez, Simon, Christophe Fraser, Maria D. Van Kerkhove, et al. 2014. “Middle East Respiratory Syndrome Coronavirus: Quantification of the Extent of the Epidemic, Surveillance Biases, and Transmissibility.” The Lancet – Infectious Diseases 14 (1): 50–56. https://doi.org/10.1016/S1473-3099(13)70304-9.

Chignell, Andrew. 2018. “The Ethics of Belief.” Stanford Encyclopedia of Philosophy. https://plato.stanford.edu/entries/ethics-belief/.

Chowell, Gerardo (editor), Charlotte Hackson, Punam Mangtani, Jeremy Hawker, Babatunde Olowokure, and Emilia Vynnycky. 2014. “The Effects of School Closures on Influenza Outbreaks and Pandemics: Systematic Review of Simulation Studies.” PLoS One 9 (5): e97297.

Christiano, Thomas. 2010. The Constitution of Equality: Democratic Authority and Its Limits. Oxford: Oxford University Press.

Cordle, Vaughn. 2020. “Pandemic 2020: Layoff-related Deaths.” April 23. https://www.linkedin.com/pulse/pandemic-2020-layoff-related-deaths-increase-covid-19-cordle-cfa/?fbclid=IwAR18TeBQA3Lna61kdMPzPcWyrBnj70n6EP9qF7sFIL10JZlPdVeX9Mnt6Ok.

Cowen, Tyler. 2020. “More on Economists and Epidemiologists.” Marginal Revolution, April 19. https://marginalrevolution.com/marginalrevolution/2020/04/more-on-economists-and-epidemiologists.html.

Da Silva, Chantal. 2020. “Texas Hospital Child Abuse Cases Rise in COVID-19 Outbreak: ‘It’s Hard to Think That It’s Just Coincidental.’” Newsweek, March 22. https://www.newsweek.com/texas-hospital-child-abuse-cases-rise-covid-19-outbreak-1493642.

Douglas, Heather. 2000. “Inductive Risk and Values in Science.” Philosophy of Science 67 (4): 559–79.

———. 2009. Science, Policy, and the Value-Free Ideal. University of Pittsburgh Press.

Eberle, Christopher J. 2002. Religious Conviction in Liberal Politics. New York: Cambridge University Press.

Estlund, David. 2008. Democratic Authority. Princeton: Princeton University Press.

Ferguson, Neil M., Daniel Laydon, Gemma Nedjati Gilani, et al. 2020. “Report 9: Impact of Non-Pharmaceutical Interventions (NPIs) to Reduce COVID19 Mortality and Healthcare Demand.” Imperial College London. https://doi.org/10.25561/77482.

Feinberg, Joel. 1984. Harm to Others. New York: Oxford University Press.

Flanigan, Jessica. 2014. “A Defense of Compulsory Vaccination.” HEC Forum 26: 5–25.

–––––––. 2017. Pharmaceutical Freedom: Why Patients Have a Right to Self-Medicate. Oxford: Oxford University Press.

Forster, Nicky. 2018. “AP Analysis: Unemployment, Income Affect Life Expectancy.” AP News, December 18. https://apnews.com/66ac44186b6249709501f07a7eab36da

Freeman, Samuel. 2006. Justice and the Social Contract. Oxford: Oxford University Press.

––––––. 2009. “Constructivism, Facts, and Moral Justification.” In Contemporary Debates in Political Philosophy, edited by Thomas Christiano and John Philip Christman, 41–60. Oxford: Wiley-Blackwell.

Friedson, Andrew, Drew McNichols, Joseph J. Sabia, and Dhaval Dave. 2020. “Did California’s Shelter-in-Place Order Work? Early Coronavirus-Related Public Health Effects.” NBER Working Paper No. 26992.

Gardner, Jasmine, Lander Willem, Wooter Van der Wigngaart, Shina C. L. Kamerlin, Nele Brusselaers, and Peter Kasson. 2020. “Intervention Strategies Against COVID-19 and Their Estimated Impact on Swedish Healthcare Capacity.” https://www.medrxiv.org/content/10.1101/2020.04.11.20062133v1.full.pdf.

Gaus, Gerald. 1996. Justificatory Liberalism: An Essay on Epistemology and Political Theory. New York: Oxford University Press.

––––––. 2003. Contemporary Theories of Liberalism: Public Reason as a Post-Enlightenment Project. London: Sage.

–––––– 2011. The Order of Public Reason: A Theory of Freedom and Morality in a Diverse and Bounded World. Cambridge: Cambridge University Press.

Gaus, Gerald, Shane Courtland, and David Schmidtz. 2018. “Liberalism.” Stanford Encyclopedia of Philosophy. https://plato.stanford.edu/entries/liberalism/.

Green, Robert C., and Nita Farahany. 2014. “Regulation: The FDA is Overcautious on Consumer Genomics.” Nature 505: 286–7.

Habermas, Jurgen. 1995. “On the Internal Relation between the Rule of Law and Democracy.” European Journal of Philosophy 3 (1): 12–20.

–––––– 1996. Between Facts and Norms. Cambridge, MA: MIT Press.

Hempel, Carl G. 1965. “Science and Human Values.” In Aspects of Scientific Explanation and Other Essays in the Philosophy of Science, 81–96. The Free Press.

IHME. 2020. “Forecasting the Impact of the First Wave of the COVID-19 Pandemic on Hospital Demand and Deaths for the USA and European Economic Area Countries.” Institute for Health Metrics and Evaluation. www.healthdata.org/research-article/forecasting-impact-first-wave-covid-19-pandemic-hospital-demand-and-deaths-usa-and

Kaplan, Joshua, and Benjamin Hardy. 2020. “Early Data Shows Black People are being Disproportionally Arrested for Social Distancing Violations.” ProPublica, May 8. https://www.propublica.org/article/in-some-of-ohios-most-populous-areas-black-people-were-at-least-4-times-as-likely-to-be-charged-with-stay-at-home-violations-as-whites.

Killion, Victoria. 2019. “The First Amendment: Categories of Speech.” In Focus, Congressional Research Service, www.crs.gov. URL= https://fas.org/sgp/crs/misc/IF11072.pdf

Kristof, Nicholas. 2020. “The Best-Case Outcome for the Coronavirus, and the Worst.” The New York Times, March 20. https://www.nytimes.com/2020/03/20/opinion/sunday/coronavirus-outcomes.html.

Larmore, Charles. 2008. The Autonomy of Morality. Cambridge: Cambridge University Press.

Lemoine, Philippe. 2020. “Are We Headed toward an Unprecedented Public Health Disaster?” Nec Pluribus Impar. March 21. https://necpluribusimpar.net/are-we-headed-toward-an-unprecedented-public-health-disaster/.

Lipsitch, Marc, Christl A. Donnelly, Christophe Fraser, et al. 2015. “Potential Biases in Estimating Absolute and Relative Case-Fatality Risks during Outbreaks.” PLoS Neglected Tropical Diseases 9 (7). https://doi.org/10.1371/journal.pntd.0003846.

Marchant, Roman, Noelle I. Samia, Ori Rosen, Martin A. Tanner, and Sally Cripps. 2020. “Learning as We Go: An Examination of the Statistical Accuracy of COVID-19 Daily Death Count Predictions.” ArXiv:2004.04734 [q-Bio, Stat], April. http://arxiv.org/abs/2004.04734.

McNamara, Audrey. 2020. “UN Food Agency Chief: World Could See Famines of ‘Biblical Proportions’ Within Months.” CBS News, April 22. https://www.cbsnews.com/news/coronavirus-famines-united-nations-warning/

Mervosh, Sarah, Denise Lu, and Vanessa Swales. 2020. “See Which States and Cities Have Told Residents to Stay at Home.” The New York Times, April 20. https://www.nytimes.com/interactive/2020/us/coronavirus-stay-at-home-order.html

Mill, John Stuart. 1859. On Liberty. London: John W. Parker and Son. https://archive.org/details/onlibertyxero00milluoft/page/n9/mode/2up

Nozick, Robert. 1974. Anarchy, State, and Utopia. New York: Basic Books.

Parker, Wendy S., and Eric Winsberg. 2018. “Values and Evidence: How Models Make a Difference.” European Journal for Philosophy of Science 8 (1): 125–142.

Parmet, Wendy E., and Michael S. Sinha. 2020. “Covid-19––The Law and Limits of Quarantine.” The New England Journal of Medicine 382: e28.

Qian, Hua, Te Miao, Li Liu, Xiaohong Zheng, Danting Luo, and Yuguo Li. 2020. “Indoor Transmission of SARS-CoV-2.” MedRxiv, April, 2020.04.04.20053058. https://doi.org/10.1101/2020.04.04.20053058.

Rashid, Harunor, Iman Ridda, Catherine King, et al. 2015. “Evidence Compendium and Advice on Social Distancing and Other Related Measures for Response to an Influenza Pandemic.” Paediatric Respiratory Reviews 16 (2): 119–26.

Rawls, John. 1971. A Theory of Justice. Cambridge: Harvard University Press.

––––––1996. Political Liberalism. New York: Columbia University Press.

–––––– 2001. Justice as Fairness: A Restatement. Edited by Erin Kelly. New York: Columbia University Press.

Rudner, Richard. 1953. “The Scientist Qua Scientist Makes Value Judgments.” Philosophy of Science 20 (1): 1–6.

Schmidtz, David. 2008. Person, Polis, Planet: Essays in Applied Philosophy. Oxford: Oxford University Press.

Schmitt, Carl. 2010. Political Theology: Four Chapters on the Concept of Sovereignty. Chicago: University of Chicago Press.

Spaulding, Norman. 2008. “The Rule of Law in Action: A Defense of Adversary System Values.” Cornell Law Review 93: 1377-1412.

State of Ohio. 2019. “Ohio Population Overview.” Report of the Development Services Agency. https://www.development.ohio.gov/files/research/P7001.pdf

Sturcke, James. 2005. “Bird Flu Pandemic ‘Could Kill 150m.’” The Guardian, September 30. https://www.theguardian.com/world/2005/sep/30/birdflu.jamessturcke

Taub, Amanda. 2020. “A New Covid-19 Crisis: Domestic Abuse Rises Worldwide.” The New York Times. April 6. https://www.nytimes.com/2020/04/06/world/coronavirus-domestic-violence.html.

Tetlock, Philip. 2005. Expert Political Judgment: How Good Is It? How Can We Know? Princeton: Princeton University Press.

Tomasi, John. 2001. Liberalism Beyond Justice: Citizens, Society, and the Boundaries of Political Theory. Princeton: Princeton University Press.

––––––. 2012. Free Market Fairness. Princeton: Princeton University Press.

Vallier, Kevin. 2018. “Public Justification,” in The Stanford Encyclopedia of Philosophy, ed. Edward N. Zalta. https://plato.stanford.edu/entries/justification-public/

Wang, Taia T., Michael K. Parides, and Peter Palese. 2012. “Seroevidence for H5N1 Influenza Infections in Humans: Meta-Analysis.” Science 335 (6075): 1463. https://doi.org/10.1126/science.1218888.

Winsberg, Eric. 2012. “Values and Uncertainties in the Predictions of Global Climate Models.” Kennedy Institute of Ethics Journal 22 (2): 111–37.

———. 2018. Philosophy and Climate Science. Cambridge: Cambridge University Press.

Yu, Hongjie, Benjamin J. Cowling, Luzhao Feng, et al. 2013. “Human Infection with Avian Influenza A H7N9 Virus: An Assessment of Clinical Severity.” Lancet 382 (9887): 138–45. https://doi.org/10.1016/S0140-6736(13)61207-6.


[1] Authors’ names appear in random order.

[2] See also In re Winship, 397 U.S. 358 (1970).

[3] See (Ferguson et al. 2020). See also (Lemoine 2020) on which we draw heavily for this section.

[4] In places where testing is extensive, even case fatality rates are lower than this. There is much debate about various serological testing, but little disagreement that it indicates an upper bound of at most 1%.

[5] In climate science this is called running a “perturbed physics ensemble” and it plays a central role in estimating model forecast uncertainty (Winsberg 2018).

[6] “We employed an individual agent-based model based on work by Ferguson et al. Individual-based models are increasingly used to model epidemic spread with explicit representation of demographic and spatial factors such as population distribution, workplace data, school data, and mobility” (Gardner et al. 2020, 8).

[7] Source http://www.healthdata.org/covid/data-downloads. This is not even a tiny bit cherry picked. We picked Florida because the author who researched this lives in Florida and the date for its humorous overtones. Any other state and date could have revealed a similar pattern.

News, Special Issue

Call for papers – Time Sensitive!

Call for Papers – Time Sensitive!

The Kennedy Institute of Ethics Journal announces a special emergency, open-access issue on Ethics, Pandemics, and COVID-19

Papers from 3,000-12,000 words on ethical issues raised by the COVID-19 pandemic are invited. Papers on resource allocation; duties towards the vulnerable; rights to privacy and mobility; pandemics and xenophobia; the ethical and existential significance of social distancing; and any other ethical issues (in a broad sense of ethics) raised by the pandemic are welcome. In keeping with the mission of the journal, we wish to publish papers that are practically relevant and engaged as well as conceptually rigorous. We are aiming for an extremely fast turn around. Submissions will be reviewed in-house at Georgetown University for speed, and they will receive at least one anonymous review, so this will count as an anonymous peer reviewed article for curriculum vitae purposes.


We are aiming for online publication by midsummer, to come out in print as our September issue. Please direct any questions to Editor-in-Chief Quill Kukla at rkukla@gmail.com, or Acting Editor Travis Rieder at trieder@jhu.edu. Papers may be submitted through our usual submission portal at https://kiej.scholasticahq.com/. Deadline for submissions is May 15, 2020.

Book Reviews

Jenny Reardon, The Postgenomic Condition: Ethics, Justice, and Knowledge After the Genome, University of Chicago Press, 2017.

In The Postgenomic Condition, Jenny Roberts asks whether massive investments in genome sequencing have yielded meaningful knowledge. Her book presses important questions about what has really been gained from high through-put sequencing of strings of A, C, G, and T, and who has benefited from the genome project and its aftermath. More fundamentally, her target is liberalism in science and in bioethics; the volume is less about genomics than it is more generally about the business of contemporary science. Roberts asks telling questions, tells illuminating stories, and raises trenchant criticisms.  Nonetheless, she comes perilously close to over-simplified attacks on technology, capitalism, and contemporary forms of science.

Roberts narrates significant events in genome sequencing to reveal failures in liberal democratic approaches to six core areas of concern: information, inclusion, the people, persons, property, privacy, and the public. Roberts structures each of the narratives to end with questions about whether the enterprise has been worthwhile.  The questions are both a strength and a weakness of the volume; not always well-formed, they are often left frustratingly unanswered.

 The “information of life” tells the story of the race to sequence the genome between public sector groups led by Francis Collins and corporate sponsors led by Craig Venter.  According to Roberts, the race was overtaken by the technological power needed for efficient sequencing.  Humans at the laboratory bench were replaced by sequencing machines and thus “many on the ground feared that genomics ushered in a technocratic and capitalist mode of producing information, one in which computer-run machines designed to increase speed and efficiency replaced humans who sought knowledge and justice.” In exchange for efficiency, Roberts opines, we got the industrialization of biology and instead of the free flow of information we got “the life of information.” (44) This dehumanization of science, Roberts contends, left “one central question…How can we know and act ethically in a world where life becomes information, information becomes capital, and capital is equated with freedom?” (27)

“Inclusion” narrates controversies over early efforts to ascertain whether there are significant genomic variations among population subgroups.  Projects seeking to obtain genome information from isolated indigenous populations and then from racial and ethnic minorities in the United States were fraught with charges of exploitation and racism.  Despite the rejection of biological bases for race, concerns remained over failures to include minorities in medical research. Amidst apologies for the Tuskegee syphilis study, the National Human Genome Research Institute (NHGRI) funded a major research project at Tuskegee on the genetics of heart disease.  Although designed to address a major health problem of the area, the project soon failed in recruiting subjects.  Concerns were the history of suspicion from the syphilis study, along with the charge that such an expensive genetics study would not address the health needs of an area of the country lacking effective access to even minimal emergency care.  According to Roberts, technology was the other culprit: Tuskegee simply did not have the sequencing power needed for high powered genomic research. 

Further issues attended efforts to increase diversity in genomic understanding internationally. In her case study of the international haplotype map (HapMap) assembly of genomes from different communities across the globe, Roberts describes difficult problems of community engagement and consent. To avoid any suggestion of discrimination, the HapMap sought to sample large, genetically variable populations.  HapMap sponsors also sought to discuss issues and concerns with community members.  At the point of constituting community, however, they foundered; the “people” of Japan, for example, were simply the Japanese population and there was no easy way to determine whether a small number of samples obtained from population members were in any way representative of genomes in Japan.  Nor was there a political theory adequate to address questions such as who should be included in the HapMap, other than existing global political delineations themselves.

Some particular political delineations, however—Iceland, Estonia, and Scotland in particular—had taken up their own genome initiatives. These efforts proved paradoxical, on Roberts’ account. Iceland’s outright commercialization of the data of its residents through deCODE generated intense controversy over the assumption that genetic data should be treated as a natural resource.  Roberts ends her description of Iceland’s deCODE with the observation that it “foreshadowed the crisis of value that would soon come to characterize the postgenomic condition” and with unanswered questions: “What kind of thing was the human genome, and who had the right to know and control it? A nation? A corporation? All humans” (99).  Roberts then recounts how Iceland’s example of commercialization was not followed by Scotland.  Generation Scotland (GS) attempted to assemble Scottish DNA for medically relevant research. While presented as a resource for Scotland, to be used by researchers in Scotland, GS found itself without sufficient local technological resources to perform the needed sequencing.  But by the time GS recognized this problem, the infrastructure they had built to seek feedback from participants about use of their samples had been disbanded.  Efforts to re-consent participants to the newer plans to send samples outside of Scotland foundered.  The resulting reduction in available samples, compounded by the economic crisis in 2008, left GS with an apparently useless resource and, according to Roberts, these nagging questions: “in these postgenomic times, is there any ‘thing’ at all? If not, and we are unable to gather around a thing of clear value, should scientists and society proceed?” (118)

Roberts’ treatment of direct to consumer (DTC) genomics further illustrates the strengths and weaknesses of her book. Her case example is 23andMe, selected for its success and for its announced commitment to making individual genetic information available to the wider public.  According to Roberts’ overall plan for the volume, the liberal value put to the test by this case example is property. Yet issues about data as property largely fade into the background of a wider critique of whether 23andMe creates knowledge. Roberts situates this debate in the context of the politics of knowledge more generally: “the debates over personal genomics make visible a broader contemporary struggle over how to constitute knowledge and justice in the midst of challenges to the credibility of dominant institutions, and investments in informatics as the new infrastructure for collective living and understanding.” (121-122)

As Roberts tells the story, the original vision behind 23andMe was research, specifically the assembly of sufficiently large data sets of genotype and phenotype information to understand the significance of genetic variants for Parkinson’s disease. Acquiring genetic material from saliva samples was the easy step; far more difficult was the enterprise of assembling sufficient phenotypical data to illuminate the significance of genetic variants. Roberts details how 23andMe created an engaging social media experience to encourage people to submit ongoing phenotypic information. On Roberts’ view, 23andMe portrayed itself as revolutionizing genetics by linking it to individual identity and freedom. However, it was in fact encouraging consumers to become patients-in-waiting as they “par[took] in biocapitalism” and paid to “play with [their] genome on the 23andMe website (128). Indeed, 23andMe belied its supposed democratization with its initially high price tag and appeals to computer-savvy “digerati.” When it was pushed out to wider populations, it attracted claims that the information it provided consumers was meaningless or potentially harmful; both the Food and Drug Administration and California regulators objected to any suggestion that the company was engaged in medical testing.  These objections were bolstered by the observation that companies curated DTC information differently.  Conflicts also emerged between supposedly more impartial academic science and corporate science. Roberts ends this discussion once again with a question, this time from life scientists: would the “science for the people” envisioned by 23andMe and the DTC movement enact the displacement of science “and the takeover by machines and their multinational corporations?” (143)

Roberts concludes her stories with case studies of privacy and justice.  On privacy, she questions whether terms and conditions of receiving medical care should include sharing data for research.  From her personal experience as a patient expected to share data at UCSF, Roberts segues to the Personal Genome Project (PGP), an effort based at Harvard to allow anyone interested to have their genome sequenced at a low cost and shared openly. The corporate benefit of the PGP was available DNA to develop faster and cheaper sequencing capabilities for do-it-yourself personal biology. The benefit to researchers was breaking what they saw as the bureaucratic over-regulation of medical research. The claim to openness was upfront acknowledgement that privacy in medical research cannot be guaranteed; even deidentified data bears significant potential for re-identification with a sufficiently rich data set. To be sure that participants were willing, PGP deliberately did not engage in recruitment; the result is a database that is almost exclusively white.

On justice, Roberts locates genetics at the epicenter of contemporary structural injustice.  She contrasts the vast wealth of the UCSF Mission Bay campus and nearby commercial facilities such as the sequencing giant Illumina with the deep poverty of Hunter’s Point only a few blocks further south. Her concerns about justice reach far beyond whether minorities are benefiting from genetic medicine to whether it is justifiable to allocate massive investments to “big science” when clinics that provide basic preventive care to the poor lack funds.  While Roberts is surely right to question the structural injustice furthered by investment decisions, targeting the genome project and the research infrastructure associated with it may be unfair; at most, investment in genome science is part of a larger picture of contemporary maldistribution. Relatedly, Roberts sees supposed efforts to democratize genomics by bringing in communities as ultimately undemocratic failures confront the full meaning of what is “in-formation” rather than informative.  Roberts further questions the introduction of information technology into medical records, arguing that although some information of value may emerge, the benefits overall are less clear. Cooperation and transparency about medical information, she contends, has become the province of Salesforce and other data analytics firms rather than serving the individuals who have become subsumed and forgotten in biocapitalism. Instead, Roberts cites a suggestion from an African American group discussion of The Immortal Life of Henrietta Lacks: we might tag everyone’s biospecimens in a way that could enable them to log on and see how these specimens have been used (192).

So how should we move forward in the postgenomic world? Roberts has three central ideas. First, we must recognize that information is a source of power and turn this power back into the hands of people, not through more efficient consent forms but through the creation of conditions that give people effective control over the use of their bodily tissues (182). Here, we must recognize how money flows around information, not just with its use but in its production, curation, and storage. Roberts urges transparency about the environmental impact of data processing.  We should make difficult decisions to move away from boutique “tailored” medicine (183) to investments that include us all.  Roberts’ second idea is that to do this, we must invest, she says, in “institutions that support the arts of collective judgment.” (184). In so doing, we must reimagine what is possible and think about creating meaning beyond a biotechnical idea of health.  We must, she says, “re-member” life. Third, we must bring justice in as a gathering concern, reconsidering its relegation to last place in the Belmont Report and liberal approaches to research ethics. Roberts concludes that, as publics, we must question the meaning of science and technology, link policy discussions to policy change, and keep at the forefront the relationship between innovation in science and technology and inequality.

Roberts admits that her view is highly programmatic and will need to be instituted differently in different contexts.  As a non-ideal theorist, I fully agree.  Yet she ends the volume with a mixed message about contemporary science.  On one side is the need to reassert human control over technology.  On the other side is pessimism about our ability to gain knowledge to further such reassertion. Here, Roberts asks “Under these conditions, how can anybody know what the public interest is and if it is being represented when one shares their data and DNA?” (201)

This final question struck me as primarily an expression of despair rather than an attempt to grapple with the substantive issues that it raises.  Careful thinking about public interests in health information, including but not limited to genomic information, is sorely needed.  In this regard, it is important to counter misunderstandings that foster genetic exceptionalism.  Other health information, for example about infectious or environmental exposures, has implications beyond the individual to whom it immediately pertains. Neither protestation about technological imperatives nor insistence on individual ownership of health information is particularly useful in the effort to developed principled accounts of permissible (and even potentially obligatory) uses of health information. Instead, we need to consider injustices in current forms of collection and use of health information—including, as Roberts appropriately asks—whether to prioritize genomic information over information about social determinants of health, or how to integrate these and other forms of health information.  We also need to consider how to move forward towards greater forms of inclusion in the pursuit of health justice that respect all concerned. As one example, we must consider when it is unjust to make use of data from or about individuals (and, importantly with big data, these are not the same) if these uses fail to benefit or even harm the individuals concerned.  As another, we need far more work on the obligations of data users to data sources and sharers, even in circumstances in which efforts to gain useful knowledge flounder.

Much remains to be asked and learned about the genome project.  Roberts’ book is in some respects an illuminating start but it leaves largely unaddressed the critical questions about justice that she asks.

Leslie Francis

University of Utah

Salt Lake City, Utah

Editor's Pick

Editor’s Pick, September 2019: David M. Peña-Guzmán and Joel Michael Reynolds

The Editor’s Pick for our September 2019 Issue is David M. Peña-Guzmán and Joel Michael Reynolds’s paper, “The Harm of Ableism: Medical Error and Epistemic Justice.”

One of our guest editors for this special issue, Sandra L. Borden writes, “The authors argue for a specific kind of knowledge-based medical error originating in ableism. They characterize ableism as an epistemic schema that contributes to insidious schematic error. The issue is not only what providers know, but how they know within the dominant epistemology of medicine.”

This paper advances a clear, powerful argument about an urgent issue, and we are pleased to highlight it and offer the opportunity to download it at this link.

Editor's Pick

Editor’s Pick, June 2019: Jonathan Kaplan

The Editor’s Pick for our June 2019 issue is Jonathan Kaplan’s paper, “Self-Care as Self-Blame Redux: Stress as Personal and Political.” Kaplan’s article opens up an entirely new and clearly important topic for bioethicists: the concept and role of ‘self-care.’ It takes up popular imperatives to take care of oneself as care suggestions and considers them through a bioethical lens. Kaplan’s essay can be read as a strikingly original contribution to the exciting and growing new literature critiquing ‘healthism,’ placing self-care in the bioethical terrain.

Download a copy of Kaplan’s paper here.

Book Reviews

Rik Peels and Martijn Blaauw, The Epistemic Dimensions of Ignorance, Cambridge University Press, 2017.

The Epistemic Dimensions of Ignorance is a provocatively framed collection of essays dealing with a variety of epistemic issues related to the concept of ignorance. The first three essays in the volume have to do with the nature of ignorance itself. Le Morvan and Peels’ contribution provides an overview of some relevant literature, and distinguishes between two views on the nature of ignorance, which they call the Standard View and the New View. In both cases, ignorance is conceived of as a lack or absence of something; what distinguishes the two views is the issue of what is lacking. On the Standard View, the ignorant agent lacks knowledge, whereas on the New View, they lack true belief. Nottelmann and Brogaard, in their respective essays, consider different ways in which we might classify ignorance. Nottelmann outlines three dimensions along which we might classify a type of ignorance: first, the kind of thing about which the epistemic subject is ignorant, such as a fact, the existence of an entity, or the answer to a question; second, the degree of ignorance the subject displays, for instance, in practical ignorance; and last, the order of ignorance, since it is possible to be meta-ignorant – a point that is made by Medina, both in his contribution to this collection and in his earlier (2012) book on the subject. Brogaard’s essay can be seen as further clarifying the first of these dimensions, arguing on the basis of linguistic analysis that there are three types of ignorance: ignorance of facts, subject matter, and how to perform a particular activity. This linguistic analysis, however, has implications for the kind of thing that ignorance is, since it ultimately speaks against the Standard View in arguing for a difference between ignorance and a lack of knowledge.

The next several essays in the volume connect ignorance to other epistemic concepts. Olsson and Proietti consider treatments of ignorance and doubt in several possible worlds frameworks, ultimately concluding that ignorance and doubt are not simply negations of knowledge and belief, respectively. Blome-Tillmann, taking the Standard View as background, extends contextualism about knowledge to contextualism about ignorance. This allows him to provide an interesting contextualist response to standard skeptical arguments, say about the existence of the external world. Brown’s essay discusses two versions of an objection to anti-intellectualism which argues that it leaves us more ignorant than we would ordinarily take ourselves to be. On the anti-intellectualist view, a difference in stakes between hearer and speaker can undermine knowledge transmission through testimony; Brown argues that, even though there can be some conflicts, our frequent reliance on testimony and memory as sources of knowledge should not lead us to reject anti-intellectualism. Another interesting essay by Pritchard considers cases in which being ignorant has epistemic value. For instance, being ignorant of a misleading defeater might help us gain further true beliefs.

The editorial framing, however, of the last three essays is curious:

We have included these essays, even though they are not confined to the epistemic dimensions of ignorance. This is because religious epistemology is typically part of epistemology, the epistemology of race has interesting things to say on collective ignorance in its relation to individual ignorance, and group belief and group knowledge have recently become big issues in epistemology (9).

What this seems to mean is that these final three essays, as with much of the epistemology of ignorance literature they draw on (at the very least, the Fricker and Medina draw on that literature), incorporate the social and political dimensions of ignorance. That is, they discuss ignorance as it occurs in our non-ideal world, and as it is produced in agents who are all socially situated in some way. But the acknowledgement of such traditions and bodies of work in epistemology is in tension with the initial, and indeed motivating, claims of the book. The first sentence of the book’s back blurb is, “Ignorance is a neglected issue in philosophy.” In light of the Fricker and Medina essays, this seems obviously false, given the rich contributions by philosophers of race and gender to the development of epistemologies of ignorance. In their introduction to the volume, the editors make a more precise claim—though still one that bears further consideration—that epistemologists have hardly paid attention to ignorance, as they acknowledge that areas of philosophy other than epistemology have dealt with the issue of ignorance. The one exception they note within epistemology is in the area of radical skepticism (1). Given, however, that Linda Martín Alcoff’s contribution to the collection Race and Epistemologies of Ignorance (2007) provides a typology of existing arguments in the epistemology of ignorance, the claim, even, that it has been neglected in epistemology is puzzling.

Before drawing out the issues with the framing of this volume, I should note that none of this should be taken as a criticism of its individual essays, as contributions to epistemology, and to the epistemology of ignorance in particular. I think that there might have been some cases in which greater (or some) consideration of the more explicitly social literature might have been beneficial, however, and we might see this as a missed opportunity. For instance, the several essays discussing classifications of ignorance tend to consider it primarily as an absence or lack of something, where the nature of the thing lacking is up for disagreement. But those writing on ignorance in the philosophy of race tradition often write about it as something produced or cultivated. It might have been helpful to see how this would play a role in the taxonomies of ignorance discussed in some of the earlier essays in the volume. Similarly, the work on epistemic value might also have considered ways in which being racially ignorant could potentially have epistemic as well as social benefits, for instance, by allowing agents to take advantage of knowledge-granting opportunities that they might cede if they were more socially responsible.

To return to the initial editorial claim, though, that epistemology has generally ignored the phenomenon of ignorance, note that it could be interpreted in several different ways. It could mean that the well-developed literature in epistemologies of ignorance that draws from the philosophy of race has generally been ignored by a lot of mainstream epistemologists. This seems true (and to the detriment of much of mainstream epistemology), but, given that most of the essays in the book do not engage with this literature either, it is not clear that this is what the editors meant. Moreover, there seems to be some general inattentiveness to the potential social impact of this work. The front cover art, entitled “Spring’s Landfall” features a pink-clad young woman, blindfolded, attempting, it seems, to row a flower-filled boat with two sticks through a field. Ignorance, illustrated, is feminine, hapless, and blinded.

Instead, there seem to be two other ways in which this claim could be interpreted. One is that “epistemologists” refers to epistemologists whose work does not consider the social situatedness of agents. So this would exclude those who work on epistemology in a way that is fundamentally attentive to factors such as gender, race, or disability. Second, there is the possibility that the editors themselves are ignorant of the fact that the literature on epistemology and ignorance is substantial, despite its lack of inclusion in many anthologies and collections. Both of these interpretations are disappointing, but provide interesting case studies for applications of epistemologies of ignorance. So I will use the tools from the Fricker and Medina essays in the volume to analyze this.

In the first case, in which epistemology is construed in such a way that it excludes many philosophers who would self-describe as epistemologists, we might wonder whether there is a kind of hermeneutical marginalization. As Fricker’s essay describes such a situation, we might think that “some social groups have less than a fair crack at contributing to the shared pool of concepts and interpretive tropes that we use to make generally shareable sense of our social experiences” (163).

It might be difficult to make the case that groups of philosophers working on ignorance from particular non-mainstream perspectives are sufficiently cohesive to count as social groups. But we might also note that a lot of work done in anti-oppressive philosophy generally is done by people who experience at least some form of oppression, whether it be in terms of gender identity, race, or disability. But if such work is not counted as epistemology proper, then we have a situation in which, say, feminist epistemology does not have a fair crack at contributing to the shared pool of epistemic concepts that we use to engage in dialogue about the nature of knowledge.

This seems to be detrimental to members of social groups whose lived experience is better captured by the tools of feminist epistemologies, and those other excluded epistemologies of ignorance. It can also serve to signal to those interested in doing that kind of work that such pursuits are less inherently philosophical, or perhaps that considering epistemic practices that are more familiar to them is a question of ethics rather than epistemology. But it also seems epistemically detrimental to the philosophical community as a whole, since the hermeneutical resources for talking about epistemology generally are unequally distributed among its members.

The second situation, in which working epistemologists can be unaware of the extent of the literature on epistemologies of ignorance, might also be a case study, perhaps as a case of meta-ignorance. But we might also worry about the extent to which such meta-ignorance might be structurally reinforced. Meta-ignorance is extremely similar to the higher-order ignorance that Nottelmann considers (54-5), but as Medina describes it, is often associated with privilege and a lack of epistemic friction. Not only is it ignorance at the object level, but it is also ignorance of one’s own epistemic limitations (183). Moreoever, meta-ignorance is not always culpable. It might be culpable if it is also active ignorance, meaning ignorance that resists correction. This might be a matter of individual epistemic vice or bad faith, but can also be structurally produced, as Charles Mills notes in writing about white ignorance. As such, it might be worth considering what structural factors might contribute to the marginalization of particular bodies of philosophical literature.

In general, this book collects together some well-formulated and clear essays on the various epistemic topics related to ignorance. Its principal problem is not the quality of its contributions, but its motivating conceit. It purports to fill a gap in the epistemic literature, though it is not clear that the identified gap exists. Also, claiming that there is such a gap can contribute to the marginalization of philosophical work written by philosophers from underrepresented groups. But at the very least, the claim that there is such a gap allows for an interesting application of the conceptual tools of the epistemic literature that the editorial framing largely neglects.

Audrey Yap

University of Victoria

Victoria, B.C.

References

Fricker, Miranda. 2007. Epistemic Injustice. New York, NY: Oxford University Press.

Medina, José. 2012. The Epistemology of Resistance. New York, NY: Oxford University Press.

Sullivan, Shannon, and Nancy Tuana (Eds.) 2007. Race and Epistemologies of Ignorance. Albany, NY: SUNY Press.

Book Reviews

Sean Valles, Philosophy of Population Health: Philosophy for a New Public Health Era, Routledge, 2018

Sean Valles’ Philosophy of Population Health marks an important contribution to the analysis of philosophical issues relevant to a broad range of issues at the interface of population and public health. The book exemplifies the constructive contributions scholars from philosophy of science and ethics can make to advance our understanding core issues in this area, historically dominated by concern for medicine and the delivery of health care to individuals. Professor Valles’ contribution joins the work of Alex Broadbent and the philosophy of epidemiology, and the work of Angus Dawson and Marcel Verweij and Ruth Faden and Madison Powers and others in public health ethics.

The stated purpose of the book is to advance a population health framework and spark a dialogue between philosophy and population health. The book succeeds in achieving both aims. In the introduction, Professor Valles notes that unlike in previous philosophical work where “we typically find a combination of individually avoidable errors dubious shortcuts and ill designed methods. All the while philosophers of science and medicine still tend to have an abiding respect and appreciation for the science/medicine, critiquing in the hopes of making things better. When scrutinizing the philosophical underpinnings of a new interdisciplinary program such as in my previous work on evolutionary medicine and personalized genomic medicine I’ve come to expect extensive, if not fatal, problems. Imagine my surprise at encountering population health science and finding nothing really fundamentally broken. What I found instead was a field that has many debates and unsettled theoretical and practical questions that remain to be sorted out.” (3) This optimistic perspective pervades the book which is quite useful in sorting out some of the philosophical issues at the interface of the philosophy of medicine, philosophy of science and ethics relevant population health.

The book is well organized and laid out. The introductory chapter provides a blueprint of a philosophy of and for population health. A brief overview commences with a broad definition of public health and population health and explains how the aims and methods of these are distinct from clinical medicine and healthcare. The core philosophical issues and arguments to be addressed in each chapter are outlined, as are the methodological and normative commitments of the author.

The book is divided into three parts: Part 1: What should health mean in population health science; Part 2: What causes and effects matter most in population health; Part 3: How can population health science better promote equity health equity. Each section contains chapters which systematically address key concepts and engage deeply with the current literature. The chapters explore key epistemological, ethical and metaphysical issues related to the concept of health, a social concept of health, health as a life course trajectory and how accounts of causation expand the boundaries of population health and how causation can be understood in population health. Part 3 brings things together through the lens of ethics and evidence. Each of the chapters ends with a case study that illustrates the issues that are raised in the chapter. The case studies are exceptionally well chosen as they are drawn from contemporary events and touch on Indigenous health, environmental issues, communicable disease and migrant health.

What is most notable about this book is the way that the author skillfully and with great nuance explicates and distils the arguments of the many debates about population health and the determinants of health. He successfully and clearly lays out some of the key boundary issues concerning the scope and range of population health, summarizes and brings coherence to the many debates concerning the nature of causation, and sympathetically navigates the sometimes bitter arguments between public health and health care. The discussion of health equity is noteworthy in bringing clarity to the discussions of how equity is defined in health and its relationship to theories of justice.

Professor Valles is committed to an expansive concept of health and argues for the irreducible role that social forces play in the creation of health. He also argues for a life course trajectory concept of health. He is unabashedly supportive of pluralism in our metaphysical, empirical, ethical and methodological engagement with population health. Professor Valles provides an update and spirited defense of the 1946 World Health Organization definition of health, which has come under significant criticism in recent years. His reconstructed argument yields a new definition of health as a life course trajectory of complete well-being in a social context.

This concluding chapter argues for the overarching need for a spirit of humility and collaboration. As Valles notes, power relationships take on a special importance for population health science. He argues further that humility is key to population health sciences success: “Humility is needed in three areas: an overarching epistemic humility recognizing that no single person or perspective can have a full understanding of population health; intersectoral humility recognizing that no sector of society (government, health care etc) is elevated above the others; and a disciplinary humility recognizing that no contributing discipline in interdisciplinary population health science is elevated above the others.” (181)

Professor Valles has skillfully drawn together and woven into a coherent framework a diverse set of literature dating back to the 19th century and the origins of social medicine. He does justice to the literature and acknowledges the importance of integrating elements of modern preventive medicine with a sustained explication of the work of Geoffrey Rose. He also highlights the significance of modern frameworks such as the WHO Social Determinants of Health Commission.

I believe that some readers, no doubt wed to a particular theory, may take issue with arguments raised in the discussion of causation. Professor Valles contrasts his approach with that of Alex Broadbent’s as set out in his book Philosophy of Epidemiology. Professor Valles endorses the notion of fundamental cause theory as a particularly promising contribution to population health science. His endorsement of this theory should stimulate significant debate. Similarly, I think there may be scholars committed to a particular theory of justice and of particular interpretations of health equity that may resist the pluralism that he endorses.

I highly recommend this book to scholars, public health and health care practitioners, policy makers and the general reader interested in population health. The book is an excellent complimentary source to Population Health Science by Keyes and Galea, for those interested in a more technical approach to population health. Few books I know of so skillfully and effortlessly employ concepts form the philosophy of science, philosophy of medicine, and ethics. I hope this book finds its way into undergraduate and graduate courses in schools of public health, faculties of medicine, and into graduate courses in philosophy of science and philosophy of medicine. I hope that this book stimulates the creation of new courses in philosophy of population and public health. Many curricula at schools of public health leave little room for engagement with the wide range of diverse philosophical views relevant to their field. I believe that this book would help provide a sound foundation for early 21st century graduate students struggling with the deeper concepts raised by the practice of public health and population health.

Ross Upshur

Dalla Lana School of Public Health

Bridgepoint Collaboratory for Research and Innovation

Lunenfeld Tanenbaum Research Institute, Sinai Health Systems

University of Toronto

Toronto, Canada

Editor's Pick, Uncategorized

Editor’s Pick, December 2018: Alison Reiheld

Our Editor’s Pick for our December 2018 issue is Alison Reiheld’s paper, “Rightly or for Ill: The Ethics of Individual Memory.” This paper takes up a rich issue that has yet to receive significant philosophical attention: the ethics of memory. The paper asks questions such as: when are we morally blameworthy or praiseworthy for remembering, forgetting, or encoding a memory in a specific way, and what are the ethical principles that should govern our practices of remembering and forgetting? By understanding remembering and forgetting as constructive activities involving agency and choices, Reiheld examines and answers these questions with admirable philosophical clarity.

Download a copy of Reiheld’s paper here.