Will AI Avoid Exploitation?
Adam Bales (Global Priorities Institute, University of Oxford)
GPI Working Paper No. 16-2023, published in Philosophical Studies
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: in exploring the argument, we gain insight into how to model advanced AI systems.
Other working papers
The weight of suffering – Andreas Mogensen (Global Priorities Institute, University of Oxford)
How should we weigh suffering against happiness? This paper highlights the existence of an argument from intuitively plausible axiological principles to the striking conclusion that in comparing different populations, there exists some depth of suffering that cannot be compensated for by any measure of well-being. In addition to a number of structural principles, the argument relies on two key premises. The first is the contrary of the so-called Reverse Repugnant Conclusion…
Strong longtermism and the challenge from anti-aggregative moral views – Karri Heikkinen (University College London)
Greaves and MacAskill (2019) argue for strong longtermism, according to which, in a wide class of decision situations, the option that is ex ante best, and the one we ex ante ought to choose, is the option that makes the very long-run future go best. One important aspect of their argument is the claim that strong longtermism is compatible with a wide range of ethical assumptions, including plausible non-consequentialist views. In this essay, I challenge this claim…
Calibration dilemmas in the ethics of distribution – Jacob M. Nebel (University of Southern California) and H. Orri Stefánsson (Stockholm University and Swedish Collegium for Advanced Study)
This paper presents a new kind of problem in the ethics of distribution. The problem takes the form of several “calibration dilemmas,” in which intuitively reasonable aversion to small-stakes inequalities requires leading theories of distribution to recommend intuitively unreasonable aversion to large-stakes inequalities—e.g., inequalities in which half the population would gain an arbitrarily large quantity of well-being or resources…