How to neglect the long term
Hayden Wilkinson (Global Priorities Institute, University of Oxford)
GPI Working Paper No. 11-2023
Consider longtermism: the view that, at least in some of the most important decisions facing agents today, which options are morally best is determined by which are best for the long-term future. Various critics have argued that longtermism is false—indeed, that it is obviously false, and that we can reject it on normative grounds without close consideration of certain descriptive facts. In effect, it is argued, longtermism would be false even if real-world agents had promising means of benefiting vast numbers of future people. In this paper, I develop a series of troubling impossibility results for those who wish to reject longtermism so robustly. It turns out that, to do so, we must incur severe theoretical costs. I suspect that these costs are greater than simply accepting longtermism. If so, the more promising route to denying longtermism would be by appeal to descriptive facts.
Other working papers
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…
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…
Heuristics for clueless agents: how to get away with ignoring what matters most in ordinary decision-making – David Thorstad and Andreas Mogensen (Global Priorities Institute, Oxford University)
Even our most mundane decisions have the potential to significantly impact the long-term future, but we are often clueless about what this impact may be. In this paper, we aim to characterize and solve two problems raised by recent discussions of cluelessness, which we term the Problems of Decision Paralysis and the Problem of Decision-Making Demandingness. After reviewing and rejecting existing solutions to both problems, we argue that the way forward is to be found in the distinction between procedural and substantive rationality…