The A.I. Incident Database is a prominent repository that allows users to search for incidents and glean valuable insights. When developing an ML system, consulting this resource is crucial.
Structured approaches outlined in the paper "Overcoming Failures of Imagination in AI-Infused System Development and Deployment" offer ways to hypothesize about these challenging future risks, in addition to considering aspects such as "who" (including investors, customers, and vulnerable nonusers), "what" (covering well-being, opportunities, and dignity), "when" (including immediate, frequent, and long
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