‘Explainable AI’ is an umbrella term that covers research on methods designed to provide human-understandable explanations of the decisions made/knowledge captured by AI models. Within the AI field this is currently a very active research area. Evolutionary Computation (EC) draws from concepts found in nature to drive development in evolution-based systems such as genetic algorithms and evolution systems. Alongside other nature-inspired metaheuristics, such as swarm intelligence, the path to a solution is driven by stochastic processes. This creates barriers to explainability: algorithms may return different solutions when re-run from the same input and technical descriptions of these processes are often a barrier to end-user understanding and acceptance. On the other hand, very often XAI methods require the fitting of some kind of model, and hence EC methods have the potential to play a role in this area. This workshop will focus on the bidirectional interplay between XAI and EC. That is, how XAI can help EC research, and how EC can be used within XAI methods.

Recent growth in the adoption of black-box solutions including EC-based methods into domains such as medical diagnosis, manufacturing and transport & logistics has led to greater attention being given to the generation of explanations and their accessibility to end-users. This increased attention has helped create a fertile environment for the application of XAI techniques in the EC domain for both end-user and researcher focused explanation generation. Furthermore, many approaches to XAI in machine learning are based on search algorithms (e.g., Local Interpretable Model-Agnostic Explanations / LIME) that have the potential to draw on the expertise of the EC community; and many of the broader questions (such as what kinds of explanation are most appealing or useful to end users) are faced by XAI researchers in general.

GECCO 2024 Workshop

The third ECXAI workshop will be held at GECCO 2024 on this topic. More details to follow!

ACM TELO Special Issue

A special issue of the ACM TELO journal for explainability and evolutionary computation has been announced. Details here.

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