How explainable AI affects human performance: A systematic review of the behavioural consequences of saliency maps

Understand

Saliency maps can explain how deep neural networks classify images.

• But are they actually useful for humans? The present systematic review of 68 user studies found that while saliency maps can enhance human performance, null effects or even costs are quite common.
• To investigate what modulates these effects, the empirical outcomes were organised along several factors related to the human tasks, AI performance, XAI methods, images to be classified, human participants and comparison conditions.
• In image-focused tasks, benefits were less common than in AI-focused tasks, but the effects depended on the specific cognitive requirements.