When responsible AI research needs to meet reality

Intervenant(s) : Marcin DETYNIECKI (AXA)
Abstract: Responsible AI topics are now firmly established in the research community, with explainable AI or AI fairness as flagships. On the other end of the spectrum, those topics are now seriously attracting attention in organizations and companies, especially through the lens of AI governance, a discipline that aims to analyze and address the challenges arising from a widespread use of AI in practice, as AI regulations are around the corner. This leads companies to focus on the compliance aspects of AI projects. In practice, data scientists and organizations are in a fog, missing adequate guidance and solutions from research to achieve responsible AI. In this talk, we will discuss how large companies, like AXA, currently see the responsible AI topic and why the current research output only provides partially actionable methodologies and solutions. We will discuss and illustrate with some concrete examples how the research community could better address the scientific challenges of this new applied responsible AI practice.
Bio: Marcin Detyniecki is Group Chief Data Scientist & Head of AI Research and Thought Leadership at insurance global leader AXA. He leverages his expertise to help AXA deliver value and overcome AI and ML-related business challenges and enable the group to achieve its transformation as a tech-led company. He leads the artificial intelligence R&D activity at group level. His team works on setting a framework enabling fair, safe and explainable ML to deliver value. Marcin is also active in several think and do tanks, including a role of vice-president and board member of Impact AI, member of the Consultative Expert Group on Digital Ethics in Insurance for EIOPA and technical expert at Institut Montaigne. He has been involved in several academic roles including Research Scientist at both CNRS and Sorbonne University. He holds a Ph.D. in Computer Science from Université Pierre et Marie Curie.
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