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
Imperfect Recall and AI Delegation – Eric Olav Chen (Global Priorities Institute, University of Oxford), Alexis Ghersengorin (Global Priorities Institute, University of Oxford) and Sami Petersen (Department of Economics, University of Oxford)
A principal wants to deploy an artificial intelligence (AI) system to perform some task. But the AI may be misaligned and aim to pursue a conflicting objective. The principal cannot restrict its options or deliver punishments. Instead, the principal is endowed with the ability to impose imperfect recall on the agent. The principal can then simulate the task and obscure whether it is real or part of a test. This allows the principal to screen misaligned AIs during testing and discipline their behaviour in deployment. By increasing the…
Will AI Avoid Exploitation? – Adam Bales (Global Priorities Institute, University of Oxford)
A simple argument suggests that we can fruitfully model advanced AI systems using expected utility theory. According to this argument, an agent will need to act as if maximising expected utility if they’re to avoid exploitation. Insofar as we should expect advanced AI to avoid exploitation, it follows that we should expected advanced AI to act as if maximising expected utility. I spell out this argument more carefully and demonstrate that it fails, but show that the manner of its failure is instructive…
The asymmetry, uncertainty, and the long term – Teruji Thomas (Global Priorities Institute, Oxford University)
The Asymmetry is the view in population ethics that, while we ought to avoid creating additional bad lives, there is no requirement to create additional good ones. The question is how to embed this view in a complete normative theory, and in particular one that treats uncertainty in a plausible way. After reviewing…