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

Longtermist political philosophy: An agenda for future research – Jacob Barrett (Global Priorities Institute, University of Oxford) and Andreas T. Schmidt (University of Groningen)

We set out longtermist political philosophy as a research field. First, we argue that the standard case for longtermism is more robust when applied to institutions than to individual action. This motivates “institutional longtermism”: when building or shaping institutions, positively affecting the value of the long-term future is a key moral priority. Second, we briefly distinguish approaches to pursuing longtermist institutional reform along two dimensions: such approaches may be more targeted or more broad, and more urgent or more patient.

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…

Is Existential Risk Mitigation Uniquely Cost-Effective? Not in Standard Population Models – Gustav Alexandrie (Global Priorities Institute, University of Oxford) and Maya Eden (Brandeis University)

What socially beneficial causes should philanthropists prioritize if they give equal ethical weight to the welfare of current and future generations? Many have argued that, because human extinction would result in a permanent loss of all future generations, extinction risk mitigation should be the top priority given this impartial stance. Using standard models of population dynamics, we challenge this conclusion. We first introduce a theoretical framework for quantifying undiscounted cost-effectiveness over…