Counterfactuals in explainable AI: interview with Ulrike Kuhl

Objective task performance, measured as development of mean number of generated aliens per round per group. In their work For Better or Worse: The Impact of Counterfactual Explanations' Directionality on User Behavior in xAI, Ulrike Kuhl, and colleagues André Artelt and Barbara Hammer, have investigated counterfactual explanations in explainable artificial intelligence. In this interview, Ulrike tells us more about their study, and highlights some of their interesting and surprising findings. Counterfactual statements are something we as humans use every day. Phrases like "If I had gotten up earlier, I would have been on time" are counterfactuals, describing a hypothetical alternative to the current, factual state. In the realm of explainable AI (xAI), counterfactuals play a pivotal role by providing accessible and intuitive insights into the decision-making processes of AI models.