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
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 …
Exceeding expectations: stochastic dominance as a general decision theory – Christian Tarsney (Global Priorities Institute, Oxford University)
The principle that rational agents should maximize expected utility or choiceworthiness is intuitively plausible in many ordinary cases of decision-making under uncertainty. But it is less plausible in cases of extreme, low-probability risk (like Pascal’s Mugging), and intolerably paradoxical in cases like the St. Petersburg and Pasadena games. In this paper I show that, under certain conditions, stochastic dominance reasoning can capture most of the plausible implications of expectational reasoning while avoiding most of its pitfalls…
Measuring AI-Driven Risk with Stock Prices – Susana Campos-Martins (Global Priorities Institute, University of Oxford)
We propose an empirical approach to identify and measure AI-driven shocks based on the co-movements of relevant financial asset prices. For that purpose, we first calculate the common volatility of the share prices of major US AI-relevant companies. Then we isolate the events that shake this industry only from those that shake all sectors of economic activity at the same time. For the sample analysed, AI shocks are identified when there are announcements about (mergers and) acquisitions in the AI industry, launching of…