The unexpected value of the future 

Hayden Wilkinson (Global Priorities Institute, University of Oxford)

GPI Working Paper No. 17-2022, forthcoming in Ergo

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Various philosophers accept moral views that are impartial, additive, and risk-neutral with respect to betterness. But, if that risk neutrality is spelt out according to expected value theory alone, such views face a dire reductio ad absurdum. If the expected sum of value in humanity’s future is undefined—if, e.g., the probability distribution over possible values of the future resembles the Pasadena game, or a Cauchy distribution—then those views say that no real-world option is ever better than any other. And, as I argue, our evidence plausibly supports such a probability distribution. Indeed, it supports a probability distribution that cannot be evaluated even if we extend expected value theory according to one of several extensions proposed in the literature. Must we therefore reject all impartial, additive, risk-neutral moral theories? It turns out that we need not. I provide a potential solution: by adopting a strong enough extension of expected value theory, we can evaluate that problematic distribution and potentially salvage those moral views.

Other working papers

Moral uncertainty and public justification – Jacob Barrett (Global Priorities Institute, University of Oxford) and Andreas T Schmidt (University of Groningen)

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…

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. …