Longtermism, aggregation, and catastrophic risk
Emma J. Curran (University of Cambridge)
GPI Working Paper No. 18-2022
Advocates of longtermism point out that interventions which focus on improving the prospects of people in the very far future will, in expectation, bring about a significant amount of good. Indeed, in expectation, such long-term interventions bring about far more good than their short-term counterparts. As such, longtermists claim we have compelling moral reason to prefer long-term interventions. In this paper, I show that longtermism is in conflict with plausible deontic scepticism about aggregation. I do so by demonstrating that, from both an ex-ante and ex-post perspective, longtermist interventions – and, in particular, those which aim to mitigate catastrophic risk – typically generate extremely weak claims of assistance from future people.
Other working papers
Choosing the future: Markets, ethics and rapprochement in social discounting – Antony Millner (University of California, Santa Barbara) and Geoffrey Heal (Columbia University)
This paper provides a critical review of the literature on choosing social discount rates (SDRs) for public cost-benefit analysis. We discuss two dominant approaches, the first based on market prices, and the second based on intertemporal ethics. While both methods have attractive features, neither is immune to criticism. …
What power-seeking theorems do not show – David Thorstad (Vanderbilt University)
Recent years have seen increasing concern that artificial intelligence may soon pose an existential risk to humanity. One leading ground for concern is that artificial agents may be power-seeking, aiming to acquire power and in the process disempowering humanity. A range of power-seeking theorems seek to give formal articulation to the idea that artificial agents are likely to be power-seeking. I argue that leading theorems face five challenges, then draw lessons from this result.
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. …