Aggregating Small Risks of Serious Harms
Tomi Francis (Global Priorities Institute, University of Oxford)
GPI Working Paper No. 21-2024
According to Partial Aggregation, a serious harm can be outweighed by a large number of somewhat less serious harms, but can outweigh any number of trivial harms. In this paper, I address the question of how we should extend Partial Aggregation to cases of risk, and especially to cases involving small risks of serious harms. I argue that, contrary to the most popular versions of the ex ante and ex post views, we should sometimes prevent a small risk that a large number of people will suffer serious harms rather than prevent a small number of people from certainly suffering the same harms. Along the way, I object to the ex ante view on the grounds that it gives an implausible degree of priority to preventing identified over statistical harms, and to the ex post view on the grounds that it fails to respect the separateness of persons. An insight about the nature of claims emerges from these arguments: there are three conceptually distinct senses in which a person’s claim can be said to have a certain degree of strength. I make use of the distinction between these three senses in which a claim can be said to have strength in order to set out a new, more plausible, view about the aggregation of people’s claims under risk.
Other working papers
Moral uncertainty and public justification – Jacob Barrett (Global Priorities Institute, University of Oxford) and Andreas T Schmidt (University of Groningen)
Moral uncertainty and disagreement pervade our lives. Yet we still need to make decisions and act, both in individual and political contexts. So, what should we do? The moral uncertainty approach provides a theory of what individuals morally ought to do when they are uncertain about morality…
Will AI Avoid Exploitation? – Adam Bales (Global Priorities Institute, University of Oxford)
A simple argument suggests that we can fruitfully model advanced AI systems using expected utility theory. According to this argument, an agent will need to act as if maximising expected utility if they’re to avoid exploitation. Insofar as we should expect advanced AI to avoid exploitation, it follows that we should expected advanced AI to act as if maximising expected utility. I spell out this argument more carefully and demonstrate that it fails, but show that the manner of its failure is instructive…
It Only Takes One: The Psychology of Unilateral Decisions – Joshua Lewis (New York University) et al.
Sometimes, one decision can guarantee that a risky event will happen. For instance, it only took one team of researchers to synthesize and publish the horsepox genome, thus imposing its publication even though other researchers might have refrained for biosecurity reasons. We examine cases where everybody who can impose a given event has the same goal but different information about whether the event furthers that goal. …