Counterfactuals in Explainable Artificial Intelligence (XAI): Evidence from Human Reasoning

Counterfactuals in Explainable Artificial Intelligence (XAI): Evidence from Human Reasoning

Ruth M. J. Byrne

Proceedings of the Twenty-Eighth International Joint Conference on Artificial Intelligence
Survey track. Pages 6276-6282. https://doi.org/10.24963/ijcai.2019/876

Counterfactuals about what could have happened are increasingly used in an array of Artificial Intelligence (AI) applications, and especially in explainable AI (XAI). Counterfactuals can aid the provision of interpretable models to make the decisions of inscrutable systems intelligible to developers and users. However, not all counterfactuals are equally helpful in assisting human comprehension. Discoveries about the nature of the counterfactuals that humans create are a helpful guide to maximize the effectiveness of counterfactual use in AI.
Keywords:
Machine Learning: Explainable Machine Learning
Humans and AI: Cognitive Modeling