To enable the development and use of safe and equitable artificial intelligence (AI) systems, AI engineers must monitor deployed AI systems and learn from past AI incidents where failures have occurred. Around the world, public databases for cataloging AI systems and resulting harms are instrumental in promoting awareness of potential AI harms among policymakers, researchers, and the public. However, despite growing recognition of the potential of AI systems to produce harms, causes of AI systems failure remain elusive and AI incidents continue to occur. For example, incidents of AI bias are frequently reported and discussed, yet biased systems continue to be developed and deployed.
No takes yet. Share an insight, caveat, or question.
Turri et al. (2023) studied this question.
Synapse has enriched 5 closely related papers on similar clinical questions. Consider them for comparative context: