'Challenges of Explainable AI' - David Danks@Phinance Online Seminars
Автор: Phinance - the Philosophy and Finance Network
Загружено: 2025-06-17
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As AI systems are becoming increasingly common in the finance sector, there is a growing need (including regulatory demands) for them to provide explanations of their model outputs. Explainable AI is also thought valuable because it can potentially help to reduce biases or increase trust. In this talk, I will first outline the reasons why people think that explainable AI might provide significant psychological, societal, and ethical benefits. However, I will then present a series of experiments that point towards a much more complicated cognitive picture than is standardly assumed in the field of explainable AI. I will argue that people are goal- and norm-directed in ways that fail to match most methods for deriving explanations for AI. We need a new, different type of approach to explainable, and justifiable, AI systems.
An open debate follows the meeting.
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