In defence of fanaticism
Hayden Wilkinson (Australian National University)
GPI Working Paper No. 4-2020, published in Ethics
Which is better: a guarantee of a modest amount of moral value, or a tiny probability of arbitrarily large value? To prefer the latter seems fanatical. But, as I argue, avoiding such fanaticism brings severe problems. To do so, we must (1) decline intuitively attractive trade-offs; (2) rank structurally identical pairs of lotteries inconsistently, or else admit absurd sensitivity to tiny probability differences;(3) have rankings depend on remote, unaffected events (including events in ancient Egypt); and often (4) neglect to rank lotteries as we already know we would if we learned more. Compared to these implications, fanaticism is highly plausible
Other working papers
Estimating long-term treatment effects without long-term outcome data – David Rhys Bernard (Paris School of Economics)
Estimating long-term impacts of actions is important in many areas but the key difficulty is that long-term outcomes are only observed with a long delay. One alternative approach is to measure the effect on an intermediate outcome or a statistical surrogate and then use this to estimate the long-term effect. …
A bargaining-theoretic approach to moral uncertainty – Owen Cotton-Barratt (Future of Humanity Institute, Oxford University), Hilary Greaves (Global Priorities Institute, Oxford University)
This paper explores a new approach to the problem of decision under relevant moral uncertainty. We treat the case of an agent making decisions in the face of moral uncertainty on the model of bargaining theory, as if the decision-making process were one of bargaining among different internal parts of the agent, with different parts committed to different moral theories. The resulting approach contrasts interestingly with the extant “maximise expected choiceworthiness”…
The Shutdown Problem: An AI Engineering Puzzle for Decision Theorists – Elliott Thornley (Global Priorities Institute, University of Oxford)
I explain and motivate the shutdown problem: the problem of designing artificial agents that (1) shut down when a shutdown button is pressed, (2) don’t try to prevent or cause the pressing of the shutdown button, and (3) otherwise pursue goals competently. I prove three theorems that make the difficulty precise. These theorems suggest that agents satisfying some innocuous-seeming conditions will often try to prevent or cause the pressing of the shutdown button, even in cases where it’s costly to do so. I end by noting that…