AI alignment vs AI ethical treatment: Ten challenges
Adam Bradley (Lingnan University) and Bradford Saad (Global Priorities Institute, University of Oxford)
GPI Working Paper No. 19-2024
A morally acceptable course of AI development should avoid two dangers: creating unaligned AI systems that pose a threat to humanity and mistreating AI systems that merit moral consideration in their own right. This paper argues these two dangers interact and that if we create AI systems that merit moral consideration, simultaneously avoiding both of these dangers would be extremely challenging. While our argument is straightforward and supported by a wide range of pretheoretical moral judgments, it has far-reaching moral implications for AI development. Although the most obvious way to avoid the tension between alignment and ethical treatment would be to avoid creating AI systems that merit moral consideration, this option may be unrealistic and is perhaps fleeting. So, we conclude by offering some suggestions for other ways of mitigating mistreatment risks associated with alignment.
Other working papers
Population ethical intuitions – Lucius Caviola (Harvard University) et al.
Is humanity’s existence worthwhile? If so, where should the human species be headed in the future? In part, the answers to these questions require us to morally evaluate the (potential) human population in terms of its size and aggregate welfare. This assessment lies at the heart of population ethics. Our investigation across nine experiments (N = 5776) aimed to answer three questions about how people aggregate welfare across individuals: (1) Do they weigh happiness and suffering symmetrically…
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…
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…