Quantifying Harm

Authors
Publication date 2023
Host editors
  • E. Elkind
Book title Proceedings of the Thirty-Second International Joint Conference on Artificial Intelligence
Book subtitle IJCAI 2023, Macao, S.A.R, 19-25 August 2023
ISBN
  • 9781713884606
ISBN (electronic)
  • 9781956792034
Event 32nd International Joint Conference on Artificial Intelligence, IJCAI 2023
Volume | Issue number 1
Pages (from-to) 363-371
Publisher International Joint Conferences on Artificial Intelligence
Organisations
  • Interfacultary Research - Institute for Logic, Language and Computation (ILLC)
Abstract
In a companion paper (Beckers et al. 2022), we defined a qualitative notion of harm: either harm is caused, or it is not. For practical applications, we often need to quantify harm; for example, we may want to choose the lest harmful of a set of possible interventions. We first present a quantitative definition of harm in a deterministic context involving a single individual, then we consider the issues involved in dealing with uncertainty regarding the context and going from a notion of harm for a single individual to a notion of "societal harm", which involves aggregating the harm to individuals. We show that the "obvious" way of doing this (just taking the expected harm for an individual and then summing the expected harm over all individuals can lead to counterintuitive or inappropriate answers, and discuss alternatives, drawing on work from the decision-theory literature.
Document type Conference contribution
Note In print proceedings pp. 360-368.
Language English
Published at https://doi.org/10.24963/ijcai.2023/41
Other links https://www.proceedings.com/71821.html
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