Moral uncertainty and public justification

Jacob Barrett (Global Priorities Institute, University of Oxford) and Andreas T Schmidt (University of Groningen)

GPI Working Paper No. 15-2021, forthcoming at Philosophers' Imprint

Moral uncertainty and disagreement pervade our lives. Yet we still need to make decisions and act, both in individual and political contexts. So, what should we do? The moral uncertainty approach provides a theory of what individuals morally ought to do when they are uncertain about morality. Public reason liberals, in contrast, provide a theory of how societies should deal with reasonable disagreements about morality. They defend the public justification principle: state action is permissible only if it can be justified to all reasonable people. In this article, we bring these two approaches together. Specifically, we investigate whether the moral uncertainty approach supports public reason liberalism: given our own moral uncertainty, should we favor public justification? We argue that while the moral uncertainty approach cannot vindicate an exceptionless public justification principle, it gives us reason to adopt public justification as a pro tanto institutional commitment. Furthermore, it provides new answers to some intramural debates among public reason liberals and new responses to some common objections.

Other working papers

The weight of suffering – Andreas Mogensen (Global Priorities Institute, University of Oxford)

How should we weigh suffering against happiness? This paper highlights the existence of an argument from intuitively plausible axiological principles to the striking conclusion that in comparing different populations, there exists some depth of suffering that cannot be compensated for by any measure of well-being. In addition to a number of structural principles, the argument relies on two key premises. The first is the contrary of the so-called Reverse Repugnant Conclusion…

The Shutdown Problem: An AI Engineering Puzzle for Decision Theorists – Elliott Thornley (Global Priorities Institute, University of Oxford)

I explain and motivate the shutdown problem: the problem of designing artificial agents that (1) shut down when a shutdown button is pressed, (2) don’t try to prevent or cause the pressing of the shutdown button, and (3) otherwise pursue goals competently. I prove three theorems that make the difficulty precise. These theorems suggest that agents satisfying some innocuous-seeming conditions will often try to prevent or cause the pressing of the shutdown button, even in cases where it’s costly to do so. I end by noting that…

On two arguments for Fanaticism – Jeffrey Sanford Russell (University of Southern California)

Should we make significant sacrifices to ever-so-slightly lower the chance of extremely bad outcomes, or to ever-so-slightly raise the chance of extremely good outcomes? Fanaticism says yes: for every bad outcome, there is a tiny chance of of extreme disaster that is even worse, and for every good outcome, there is a tiny chance of an enormous good that is even better.