Technical Barriers to the Adoption of Post-hoc Explanation Methods for Black Box AI models

Abstract	We examine two key technical barriers to the adoption of post hoc methods for explaining the outputs of black box AI models: their lack of robustness, and the difficulty in assessing explanation fidelity.
Authors	Eunjin Lee (IBM UK) Harrison Taylor (Cardiff) Liam Hiley (Cardiff) Richard Tomsett (IBM UK)
Date	Apr-2021
Venue	AISB 2021 Symposium, Overcoming Opacity in Machine Learning