The Significance, Persistence, Contingency Framework
William MacAskill, Teruji Thomas (Global Priorities Institute, University of Oxford) and Aron Vallinder (Forethought Foundation for Global Priorities Institute)
GPI Technical Report No. T1-2022
The world, considered from beginning to end, combines many different features, or states of affairs, that contribute to its value. The value of each feature can be factored into its significance—its average value per unit time—and its persistence—how long it lasts. Sometimes, though, we want to ask a further question: how much of the feature’s value can be attributed to a particular agent’s decision at a particular point in time (or to some other originating event)? In other words, to what extent is the feature’s value contingent on the agent’s choice? For this, we must also look at the counterfactual: how would things have turned out otherwise?
Other working papers
Intergenerational equity under catastrophic climate change – Aurélie Méjean (CNRS, Paris), Antonin Pottier (EHESS, CIRED, Paris), Stéphane Zuber (CNRS, Paris) and Marc Fleurbaey (CNRS, Paris School of Economics)
Climate change raises the issue of intergenerational equity. As climate change threatens irreversible and dangerous impacts, possibly leading to extinction, the most relevant trade-off may not be between present and future consumption, but between present consumption and the mere existence of future generations. To investigate this trade-off, we build an integrated assessment model that explicitly accounts for the risk of extinction of future generations…
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…
Three mistakes in the moral mathematics of existential risk – David Thorstad (Global Priorities Institute, University of Oxford)
Longtermists have recently argued that it is overwhelmingly important to do what we can to mitigate existential risks to humanity. I consider three mistakes that are often made in calculating the value of existential risk mitigation: focusing on cumulative risk rather than period risk; ignoring background risk; and neglecting population dynamics. I show how correcting these mistakes pushes the value of existential risk mitigation substantially below leading estimates, potentially low enough to…