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In his seminal book `The Inmates are Running the Asylum: Why High-TechProducts Drive Us Crazy And How To Restore The Sanity' [2004, SamsIndianapolis, IN, USA], Alan Cooper argues that a major reason why software isoften poorly designed (from a user perspective) is that programmers are incharge of design decisions, rather than interaction designers. As a result,programmers design software for themselves, rather than for their targetaudience, a phenomenon he refers to as the `inmates running the asylum'. Thispaper argues that explainable AI risks a similar fate. While the re-emergenceof explainable AI is positive, this paper argues most of us as AI researchersare building explanatory agents for ourselves, rather than for the intendedusers. But explainable AI is more likely to succeed if researchers andpractitioners understand, adopt, implement, and improve models from the vastand valuable bodies of research in philosophy, psychology, and cognitivescience, and if evaluation of these models is focused more on people than ontechnology. From a light scan of literature, we demonstrate that there isconsiderable scope to infuse more results from the social and behaviouralsciences into explainable AI, and present some key results from these fieldsthat are relevant to explainable AI.

Explainable AI: Beware of Inmates Running the Asylum Or: How I Learnt to Stop Worrying and Love the Social and Behavioural Sciences