References

Towards a rigorous science of interpretable machine learning

Finale Doshi-Velez & Been Kim (2017)

arXiv preprint.

URL: https://arxiv.org/abs/1702.08608

Abstract. Survey paper proposing a taxonomy of interpretability research — application-grounded vs human-grounded vs functionally-grounded evaluation — with explicit attention to which user populations benefit from each. The framing reference for XAI evaluation methodology before CHI took over the area.

Tags: ai-usability xai methodology

This site is currently in Beta. Contact: Chris Paton

Textbook of AI · Textbook of Digital Health

Auckland Maths and Science Tutoring