A non-identity dilemma for person-affecting views

Elliott Thornley (Global Priorities Institute, University of Oxford)

GPI Working Paper No. 6-2024

Person-affecting views 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 is a dilemma over trilemmas. Narrow person-affecting views imply a trilemma in a case that I call ‘Expanded Non-Identity.’ Wide person-affecting views imply a trilemma in a case that I call ‘Two-Shot Non-Identity.’ One plausible practical upshot of my argument is as follows: we individuals and our governments should be doing more to reduce the risk of human extinction this century.

Other working papers

Intergenerational experimentation and catastrophic risk – Fikri Pitsuwan (Center of Economic Research, ETH Zurich)

I study an intergenerational game in which each generation experiments on a risky technology that provides private benefits, but may also cause a temporary catastrophe. I find a folk-theorem-type result on which there is a continuum of equilibria. Compared to the socially optimal level, some equilibria exhibit too much, while others too little, experimentation. The reason is that the payoff externality causes preemptive experimentation, while the informational externality leads to more caution…

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…

Estimating long-term treatment effects without long-term outcome data – David Rhys Bernard (Rethink Priorities), Jojo Lee and Victor Yaneng Wang (Global Priorities Institute, University of Oxford)

The surrogate index method allows policymakers to estimate long-run treatment effects before long-run outcomes are observable. We meta-analyse this approach over nine long-run RCTs in development economics, comparing surrogate estimates to estimates from actual long-run RCT outcomes. We introduce the M-lasso algorithm for constructing the surrogate approach’s first-stage predictive model and compare its performance with other surrogate estimation methods. …