The scope of longtermism
David Thorstad (Global Priorities Institute, University of Oxford)
GPI Working Paper No. 6-2021
Longtermism holds roughly that in many decision situations, the best thing we can do is what is best for the long-term future. The scope question for longtermism asks: how large is the class of decision situations for which longtermism holds? Although longtermism was initially developed to describe the situation of cause-neutral philanthropic decisionmaking, it is increasingly suggested that longtermism holds in many or most decision problems that humans face. By contrast, I suggest that the scope of longtermism may be more restricted than commonly supposed. After specifying my target, swamping axiological strong longtermism (swamping ASL), I give two arguments for the rarity thesis that the options needed to vindicate swamping ASL in a given decision problem are rare. I use the rarity thesis to pose two challenges to the scope of longtermism: the area challenge that swamping ASL often fails when we restrict our attention to specific cause areas, and the challenge from option unawareness that swamping ASL may fail when decision problems are modified to incorporate agents’ limited awareness of the options available to them.
Other working papers
Existential risk and growth – Leopold Aschenbrenner (Columbia University)
Human activity can create or mitigate risks of catastrophes, such as nuclear war, climate change, pandemics, or artificial intelligence run amok. These could even imperil the survival of human civilization. What is the relationship between economic growth and such existential risks? In a model of directed technical change, with moderate parameters, existential risk follows a Kuznets-style inverted U-shape. …
The unexpected value of the future – Hayden Wilkinson (Global Priorities Institute, University of Oxford)
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…
The Shutdown Problem: An AI Engineering Puzzle for Decision Theorists – Elliott Thornley (Global Priorities Institute, University of Oxford)
I explain and motivate the shutdown problem: the problem of designing artificial agents that (1) shut down when a shutdown button is pressed, (2) don’t try to prevent or cause the pressing of the shutdown button, and (3) otherwise pursue goals competently. I prove three theorems that make the difficulty precise. These theorems suggest that agents satisfying some innocuous-seeming conditions will often try to prevent or cause the pressing of the shutdown button, even in cases where it’s costly to do so. I end by noting that…