The intersection of evolutionary computation and explainable AI.

Bacardit, Jaume; Brownlee, Alexander E.I.; Cagnoni, Stefano; Iacca, Giovanni; McCall, John; Walker, David

Abstract

In the past decade, Explainable Artificial Intelligence (XAI) has attracted a great interest in the research community, motivated by the need for explanations in critical AI applications. Some recent advances in XAI are based on Evolutionary Computation (EC) techniques, such as Genetic Programming. We call this trend EC for XAI. We argue that the full potential of EC methods has not been fully exploited yet in XAI, and call the community for future efforts in this field. Likewise, we find that there is a growing concern in EC regarding the explanation of population-based methods, i.e., their search process and outcomes. While some attempts have been done in this direction (although, in most cases, those are not explicitly put in the context of XAI), we believe that there are still several research opportunities and open research questions that, in principle, may promote a safer and broader adoption of EC in real-world applications. We call this trend XAI within EC. In this position paper, we briefly overview the main results in the two above trends, and suggest that the EC community may play a major role in the achievement of XAI.

Citation

BACARDIT, J., BROWNLEE, A.E.I., CAGNONI, S., IACCA, G., MCCALL, J. and WALKER, D. 2022. The intersection of evolutionary computation and explainable AI. In Fieldsend, J. (ed.) GECCO'22 companion: proceedings of 2022 Genetic and evolutionary computation conference companion, 9-13 July 2022, Boston, USA, [virtual event]. New York: ACM [online], pages 1757-1762. Available from: https://doi.org/10.1145/3520304.3533974

• Presentation Conference Type: Conference Paper (published)
• Conference Name: 2022 Genetic and evolutionary computation conference (GECCO '22)
• Start Date: Jul 9, 2022
• End Date: Jul 13, 2022
• Acceptance Date: Mar 22, 2022
• Online Publication Date: Jun 19, 2022
• Publication Date: Jul 31, 2022
• Deposit Date: Dec 13, 2022
• Publicly Available Date: Dec 13, 2022
• Publisher: Association for Computing Machinery (ACM)
• Peer Reviewed: Peer Reviewed
• Pages: 1757-1762
• Book Title: GECCO '22 companion: proceedings of the genetic and evolutionary computation conference
• ISBN: 9781450392686
• DOI: https://doi.org/10.1145/3520304.3533974
• Keywords: Explainable artificial intelligence; Evolutionary computation; Optimization; Machine learning
• Public URL: https://rgu-repository.worktribe.com/output/1742118