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
Dispelling the Anthropic Shadow – Teruji Thomas (Global Priorities Institute, University of Oxford)
There are some possible events that we could not possibly discover in our past. We could not discover an omnicidal catastrophe, an event so destructive that it permanently wiped out life on Earth. Had such a catastrophe occurred, we wouldn’t be here to find out. This space of unobservable histories has been called the anthropic shadow. Several authors claim that the anthropic shadow leads to an ‘observation selection bias’, analogous to survivorship bias, when we use the historical record to estimate catastrophic risks. …
Economic growth under transformative AI – Philip Trammell (Global Priorities Institute, Oxford University) and Anton Korinek (University of Virginia)
Industrialized countries have long seen relatively stable growth in output per capita and a stable labor share. AI may be transformative, in the sense that it may break one or both of these stylized facts. This review outlines the ways this may happen by placing several strands of the literature on AI and growth within a common framework. We first evaluate models in which AI increases output production, for example via increases in capital’s substitutability for labor…
A non-identity dilemma for person-affecting views – Elliott Thornley (Global Priorities Institute, University of Oxford)
Person-affecting views in population ethics state that (in cases where all else is equal) we’re permitted but not required to create people who would enjoy good lives. In this paper, I present an argument against every possible variety of person- affecting view. The argument takes the form of a dilemma. Narrow person-affecting views must embrace at least one of three implausible verdicts in a case that I call ‘Expanded Non- Identity.’ Wide person-affecting views run into trouble in a case that I call ‘Two-Shot Non-Identity.’ …