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

Once More, Without Feeling – Andreas Mogensen (Global Priorities Institute, University of Oxford)

I argue for a pluralist theory of moral standing, on which both welfare subjectivity and autonomy can confer moral status. I argue that autonomy doesn’t entail welfare subjectivity, but can ground moral standing in its absence. Although I highlight the existence of plausible views on which autonomy entails phenomenal consciousness, I primarily emphasize the need for philosophical debates about the relationship between phenomenal consciousness and moral standing to engage with neglected questions about the nature…

‘The only ethical argument for positive 𝛿’? – Andreas Mogensen (Global Priorities Institute, Oxford University)

I consider whether a positive rate of pure intergenerational time preference is justifiable in terms of agent-relative moral reasons relating to partiality between generations, an idea I call ​discounting for kinship​. I respond to Parfit’s objections to discounting for kinship, but then highlight a number of apparent limitations of this…

How effective is (more) money? Randomizing unconditional cash transfer amounts in the US – Ania Jaroszewicz (University of California San Diego), Oliver P. Hauser (University of Exeter), Jon M. Jachimowicz (Harvard Business School) and Julian Jamison (University of Oxford and University of Exeter)

We randomized 5,243 Americans in poverty to receive a one-time unconditional cash transfer (UCT) of $2,000 (two months’ worth of total household income for the median participant), $500 (half a month’s income), or nothing. We measured the effects of the UCTs on participants’ financial well-being, psychological well-being, cognitive capacity, and physical health through surveys administered one week, six weeks, and 15 weeks later. While bank data show that both UCTs increased expenditures, we find no evidence that…