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
The evidentialist’s wager – William MacAskill, Aron Vallinder (Global Priorities Institute, Oxford University) Caspar Österheld (Duke University), Carl Shulman (Future of Humanity Institute, Oxford University), Johannes Treutlein (TU Berlin)
Suppose that an altruistic and morally motivated agent who is uncertain between evidential decision theory (EDT) and causal decision theory (CDT) finds herself in a situation in which the two theories give conflicting verdicts. We argue that even if she has significantly higher credence in CDT, she should nevertheless act …
The paralysis argument – William MacAskill, Andreas Mogensen (Global Priorities Institute, Oxford University)
Given plausible assumptions about the long-run impact of our everyday actions, we show that standard non-consequentialist constraints on doing harm entail that we should try to do as little as possible in our lives. We call this the Paralysis Argument. After laying out the argument, we consider and respond to…
Imperfect Recall and AI Delegation – Eric Olav Chen (Global Priorities Institute, University of Oxford), Alexis Ghersengorin (Global Priorities Institute, University of Oxford) and Sami Petersen (Department of Economics, University of Oxford)
A principal wants to deploy an artificial intelligence (AI) system to perform some task. But the AI may be misaligned and aim to pursue a conflicting objective. The principal cannot restrict its options or deliver punishments. Instead, the principal is endowed with the ability to impose imperfect recall on the agent. The principal can then simulate the task and obscure whether it is real or part of a test. This allows the principal to screen misaligned AIs during testing and discipline their behaviour in deployment. By increasing the…