Longtermism in an Infinite World
Christian J. Tarsney (Population Wellbeing Initiative, University of Texas at Austin) and Hayden Wilkinson (Global Priorities Institute, University of Oxford)
GPI Working Paper No. 4-2023, forthcoming in Essays on Longtermism
The case for longtermism depends on the vast potential scale of the future. But that same vastness also threatens to undermine the case for longtermism: If the future contains infinite value, then many theories of value that support longtermism (e.g., risk-neutral total utilitarianism) seem to imply that no available action is better than any other. And some strategies for avoiding this conclusion (e.g., exponential time discounting) yield views that are much less supportive of longtermism. This chapter explores how the potential infinitude of the future affects the case for longtermism. We argue that (i) there are reasonable prospects for extending risk- neutral totalism and similar views to infinite contexts and (ii) many such extension strategies still support standard arguments for longtermism, since they imply that when we can only affect (or only predictably affect) a finite part of an infinite universe, we can reason as if only that finite part existed. On the other hand, (iii) there are improbable but not impossible physical scenarios in which our actions can have infinite predictable effects on the far future, and these scenarios create substantial unresolved problems for both infinite ethics and the case for longtermism.
Other working papers
When should an effective altruist donate? – William MacAskill (Global Priorities Institute, Oxford University)
Effective altruism is the use of evidence and careful reasoning to work out how to maximize positive impact on others with a given unit of resources, and the taking of action on that basis. It’s a philosophy and a social movement that is gaining considerable steam in the philanthropic world. For example,…
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…
Tough enough? Robust satisficing as a decision norm for long-term policy analysis – Andreas Mogensen and David Thorstad (Global Priorities Institute, Oxford University)
This paper aims to open a dialogue between philosophers working in decision theory and operations researchers and engineers whose research addresses the topic of decision making under deep uncertainty. Specifically, we assess the recommendation to follow a norm of robust satisficing when making decisions under deep uncertainty in the context of decision analyses that rely on the tools of Robust Decision Making developed by Robert Lempert and colleagues at RAND …