In a world increasingly shaped by algorithmic decisions, ensuring that artificial intelligence (AI) systems are explainable and trustworthy has never been more urgent. Dr. John Dorsch from CETE-P argues that we've been looking at this the wrong way.
Martin Krutský
Martin is a Ph.D. student at the Intelligent Data Analysis lab, where he studies explainable AI with emphasis on neuro-symbolic and structured geometric models. Through his interest in explainability, he started exploring the interdisciplinary field of responsible AI, spanning from AI ethics to AI safety.
Martin cooperates with members of AIC through research projects and the Responsible AI discussion group.
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