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SUMMARY:Explanations for medical artificial intelligence - Rune Nyrup (Lev
 erhulme Centre for the Future of Intelligence\, Cambridge)
DTSTART:20181017T120000Z
DTEND:20181017T133000Z
UID:TALK111166@talks.cam.ac.uk
CONTACT:Matt Farr
DESCRIPTION:(Joint work with Diana Robinson)\n\nAI systems are currently b
 eing developed and deployed for a variety medical purposes. A common objec
 tion to this trend is that medical AI systems risk being 'black-boxes'\, u
 nable to explain their decisions. How serious this objection is remains un
 clear. As some commentators point out\, human doctors too are often unable
  to properly explain their decisions. In this paper\, we seek to clarify t
 his debate. We (i) analyse the reasons why explainability is important for
  medical AI\, (ii) outline some of the features that make for good explana
 tions in this context\, and (iii) compare how well humans and AI systems a
 re able to satisfy these. We conclude that while humans currently have the
  edge\, recent developments in technical AI research may allow us to const
 ruct medical AI systems which are better explainers than humans.
LOCATION:Seminar Room 2\, Department of History and Philosophy of Science
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