arXiv · 2306.01750
A Survey of Explainable AI and Proposal for a Discipline of Explanation Engineering
Abstract
In this survey paper, we deep dive into the field of Explainable Artificial Intelligence (XAI). After introducing the scope of this paper, we start by discussing what an "explanation" really is. We then move on to discuss some of the existing approaches to XAI and build a taxonomy of the most popular methods. Next, we also look at a few applications of these and other XAI techniques in four primary domains: finance, autonomous driving, healthcare and manufacturing. We end by introducing a promising discipline, "Explanation Engineering," which includes a systematic approach for designing explainability into AI systems.
Explore related subjects
Keep this discovery
Clive Gomes, Lalitha Natraj, Shijun Liu, Anushka Datta. 2023-05-20. A Survey of Explainable AI and Proposal for a Discipline of Explanation Engineering. https://arxiv.org/abs/2306.01750
Cite the original work for its findings. Save a collection to share your selection of sources.