“Explanatory Pragmatism and Philosophy for the Science of Explainable AI”
AI systems are often accused of being ‘opaque’, ‘uninterpretable’ or ‘unexplainable’. Explainable AI (XAI) is a subfield of AI research that seeks to develops tools for overcoming this challenge. To guide this field, philosophers and AI researchers alike have looked to the philosophy of explanation and understanding. In this talk, I examine the relation between philosophy and this new Science of Explainable AI. I argue that there is a gap between typical philosophical theories of explanation and understanding and the motivations underlying XAI research: such theories are either too abstract, or else to too narrowly focused on specific scientific contexts, to address the varied ethical concerns that motivate XAI. I propose an alternative model for how philosophers can contribute to XAI, focused on articulating “mid-level” theories of explainability, i.e., theories which specify what kinds of understanding are important to preserve and promote in specific contexts involving AI-supported decision making. This programme, which I call philosophy for the science of XAI, is conceived as an inherently interdisciplinary endeavour, integrating normative, empirical and technical research on the nature and value of explanation and understanding.
Research Associate at Leverhulme Centre for the Future of Intelligence (CFI)
University of Cambridge
Further information
Ticketing
Open
Cost
Free
Open to
UCL staff
Availability
Yes