I was recently asked why I got into my research area. I can trace the exact
moment to a 2nd-year political philosophy module at Manchester University
by Stephen de Wijze. It was a lecture on Rawls’
theory of justice that had a lasting effect on me. Rawls produced an
interesting thought experiment by asking what sort of society you would want to
live in. But the kicker is that you don’t know where you will be in that
society, you are under what he calls the veil of ignorance. If you picked one
of extreme inequality, you could end up being really rich or extremely poor: it
would be a gamble. He then goes on to argue that you would end up choosing a
society where you would tolerate some inequality, as long as it doesn’t make
the poorest in society worse off.
There are a number of criticisms about this theory but there was one thing that really got me thinking. His idea of what society we would choose rested on what I think is an empirical claim: the relationship between inequality and development. This is why I have spent most of my life trying to look at the relationship between the two.
Many moral questions are reliant on empirical claims. Is it morally wrong to push someone off a cliff? The empirical question which this all rests on is what happens if we push someone off a cliff. Most of us (hopefully) would all agree that the person would fall. We don’t have to spend time talking about this. But what if moral questions rest on more difficult to prove empirical claims?
There are a number of Covid sceptics that come
from libertarian backgrounds. They dislike lockdowns as it takes away from their
individual liberties. It is, however, a separate question from how the virus
evolves, which is an empirical claim. The problem with this is the two often get
conflated. Many libertarians also claim that lockdowns are ineffective in combatting
the virus. But why should this be the case?
This is usually what we refer to when we say people are biased. We search for evidence that helps us support our own belief. But this something we find so easy to see in others, yet so hard to see in ourselves. There is a danger in thinking that you are the only objective person in the room. I do, however, believe that we should at least try and fight against our internal biases and aim towards this when looking at empirical questions. So what can we do?
We could try a very simple thought experiment which I will call the face mask of certainty. When you put on the face mask, you instantly know the probability of something working.* Let's say now, the face mask of certainty tells us that there is a 90% chance that lockdowns will suppress the virus, 10% it doesn’t work. Given the trade-offs, do you think we should go into a lockdown? Some of you reading this will think that lockdown sceptics would still choose not to lockdown. So what about if the probabilities were reversed, what if there was only a 10% chance that lockdowns work, and 90% it doesn’t? I am willing to bet some people will still think we should still go into lockdown.
You may find that you agree with people you otherwise thought you disagreed with. For example, some Covid sceptics may actually agree with you that IF lockdowns were X% effective then they would support lockdowns. They just don't think lockdowns work very well empirically. Most libertarians, however, will probably need a higher percentage of certainty for lockdowns to work than others. Which is a reasonable position to hold given that lockdowns have real trade-offs. It is important to argue about these sorts of moral questions, and I believe we should argue over them. But we don’t want the moral debate to spill over into the question of how empirically effective lockdowns are.
*By working I mean to suppress the virus with some known effectiveness over a specific time frame etc. This of course will affect peoples decisions but I am trying to keep the problem tractable.