Input to UN Interim Report on Governing AI for Humanity

This document was written by Bradford Saad, with assistance from Andreas Mogensen and Jeff Sebo. Jakob Lohmar provided valuable research assistance. The document benefited from discussion with or feedback from Frankie Andersen-Wood, Adam Bales, Ondrej Bajgar, Thomas Houlden, Jojo Lee, Toby Ord, Teruji Thomas, Elliott Thornley and Eva Vivalt.

Other papers

How should risk and ambiguity affect our charitable giving? – Lara Buchak (Princeton University)

Suppose we want to do the most good we can with a particular sum of money, but we cannot be certain of the consequences of different ways of making use of it. This paper explores how our attitudes towards risk and ambiguity bear on what we should do. It shows that risk-avoidance and ambiguity-aversion can each provide good reason to divide our money between various charitable organizations rather than to give it all to the most promising one…

Can an evidentialist be risk-averse? – Hayden Wilkinson (Global Priorities Institute, University of Oxford)

Two key questions of normative decision theory are: 1) whether the probabilities relevant to decision theory are evidential or causal; and 2) whether agents should be risk-neutral, and so maximise the expected value of the outcome, or instead risk-averse (or otherwise sensitive to risk). These questions are typically thought to be independent – that our answer to one bears little on our answer to the other. …

Tough enough? Robust satisficing as a decision norm for long-term policy analysis – Andreas Mogensen and David Thorstad (Global Priorities Institute, Oxford University)

This paper aims to open a dialogue between philosophers working in decision theory and operations researchers and engineers whose research addresses the topic of decision making under deep uncertainty. Specifically, we assess the recommendation to follow a norm of robust satisficing when making decisions under deep uncertainty in the context of decision analyses that rely on the tools of Robust Decision Making developed by Robert Lempert and colleagues at RAND …