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
Maximal cluelessness – Andreas Mogensen (Global Priorities Institute, Oxford University)
I argue that many of the priority rankings that have been proposed by effective altruists seem to be in tension with apparently reasonable assumptions about the rational pursuit of our aims in the face of uncertainty. The particular issue on which I focus arises from recognition of the overwhelming importance…
Prediction: The long and the short of it – Antony Millner (University of California, Santa Barbara) and Daniel Heyen (ETH Zurich)
Commentators often lament forecasters’ inability to provide precise predictions of the long-run behaviour of complex economic and physical systems. Yet their concerns often conflate the presence of substantial long-run uncertainty with the need for long-run predictability; short-run predictions can partially substitute for long-run predictions if decision-makers can adjust their activities over time. …
Estimating long-term treatment effects without long-term outcome data – David Rhys Bernard (Rethink Priorities), Jojo Lee and Victor Yaneng Wang (Global Priorities Institute, University of Oxford)
The surrogate index method allows policymakers to estimate long-run treatment effects before long-run outcomes are observable. We meta-analyse this approach over nine long-run RCTs in development economics, comparing surrogate estimates to estimates from actual long-run RCT outcomes. We introduce the M-lasso algorithm for constructing the surrogate approach’s first-stage predictive model and compare its performance with other surrogate estimation methods. …