Pandemic Ethics: Covid-19 Shows Just How Much of Ethics Depends on (Good) Data

Written by Hazem Zohny

In times of crises, the archetypal ethicist sits in the proverbial armchair and hums and haws, testing out intuitions about an action or policy against a jumble of moral theories. Covid-19 shows why the archetypal ethicist is as useless as antibiotics are for viral infections.

This is because virtually all the difficult ethical questions this pandemic raises boil down to having access to the relevant data, rather than the relevant intuitions or theories.

Consider these questions, all sourced from recent blogs in this Pandemic Ethics Series:

But also: Should isolation have started earlier? How draconian is too draconian? Should we aim for herd immunity? What criteria should determine who gets the ventilator if they start to run out? Etc. Etc.

These all seem like meaty moral questions – and they are. But their meatiness does not really stem from the values or principles they call into question. Instead, it is the uncertainty of the empirical data surrounding all aspects of the pandemic that should incite all the humming and hawing.

For instance, what infectious pathogen control measures are justified during a pandemic? Ethicists can appeal to theories that strive at, say, maximizing the good, or minimizing the bad, or protecting the most fundamental rights of people. And we may indeed get different answers from these theories if we ask this question in the abstract.

But once we get down to specifics and ask what measures are justified during this pandemic, at this time, and in this particular location, suddenly questions of value are dominated by questions in science, sociology and economics: how transmissible is the pathogen, what is its fatality rate, when is a vaccine likely to be widely available, what is the likely compliance rate of self-isolating, what are its likely economic impacts , and how much suffering might arise from such impacts?

Appealing to intuitions and moral theories at this level of concreteness would seem effete. This is all the more so because, when the answers to such questions are clear, different intuitions and moral theories tend to converge anyway. Any plausible non-consequentialist moral theory still takes into account consequences, and once the consequences are sufficiently grave – as in the case of pandemics – deontological conclusions about actions at the level of society tend to align with consequentialist ones, at least when the data are compelling.

The same holds for other questions: different ethical theories will tend to converge the clearer the data are on, say, the full scope of costs, trade-offs and risks posed to social care workers, or the actual risk a cough poses to others at a particular time and in a particular location. This is not to deny the role of value judgements here in deliberations, but it is to suggest they play a far smaller one in comparison to the data, at least for the purposes of policies.

This holds even for questions like whether medics on the frontlines of the pandemic should receive preferential treatments if they catch the virus. Here, we could debate things like reciprocity or desert (whether we owe these doctors more), but any such debate is ultimately at the mercy of other data. For instance, if the evidence strongly points to a significant diminishment to the morale of medics on the frontline if they do not receive preferential treatment, and if the impact of that is sufficiently costly (i.e. in terms of otherwise preventable deaths or suffering), then questions about egalitarianism or reciprocity largely fade to the background.

What about questions like whether a 1/1000 chance of survival is worth the discomfort of a month on a ventilator – one that many doctors and patients may well have to contend with in the coming months? Answering this question for oneself entails a value judgment, but the value judgement is quickly overrun by empirical questions once we start debating whether to instill a policy that answers it for hundreds or thousands of people. Suddenly, it’s largely a data game: What are the preferences of most people on this matter, and what would the trade-offs and externalities be if most thought it worthwhile (i.e would there be enough ventilators and hospital beds etc.)?

Of course, we rarely do have such data at hand, and so it might be that ethics becomes particularly important in times of uncertainty, as with this pandemic. And yet, ethical theories also tend to converge when faced with great uncertainty, adopting a somewhat cautious common-sense morality. Non-consequentialism tends to be conservative in that it seeks to protect the most fundamental rights of individuals, and perhaps especially of those who are most vulnerable to having them infringed. While consequentialism tends to apply consequentialism to its decision-making procedure, adopting a similarly conservative quasi-commonsense morality that is likely to be adhered to by most when things are shrouded in uncertainty.

Perhaps then ethics becomes most useful when the data related to a matter is clear in some respects but not others. Collating that data systematically, being clear on where the evidence is lacking, and ensuring all relevant questions of value are raised when looking at the implications of that evidence, is when ethics becomes most valuable.

This may be a fairly “duh!” concluding observation. But it’s worth noting that such a task looks much closer to doing science than pursuing some arcane equilibrium between intuitions and theories. Abstract generalisations about what is permissible and impermissible can only go so far.

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