AI3SD Video: How can explainable AI help scientific exploration?

Zednik, Carlos (2021) AI3SD Video: How can explainable AI help scientific exploration? Frey, Jeremy G., Kanza, Samantha and Niranjan, Mahesan (eds.) AI3SD Autumn Seminar Series 2021. 13 Oct - 15 Dec 2021. (doi:10.5258/SOTON/AI3SD0156).

Record type: Conference or Workshop Item (Other)

Abstract

Although models developed using machine learning are increasingly prevalent in scientific research, their opacity poses a threat to their utility. Explainable AI (XAI) aims to diminish this threat by rendering opaque models transparent. But, XAI is more than just the solution to a problem--it can also play an invaluable role in scientific exploration. In this talk, I will consider different techniques from Explainable AI to demonstrate their potential contribution to different kinds of exploratory activities. In particular, I argue that XAI tools can be used (1) to better understand what a "big data" model is a model of, (2) to engage in causal inference over high-dimensional nonlinear systems, and (3) to generate algorithmic-level hypotheses in cognitive science and neuroscience.

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Published date: 20 October 2021

Additional Information: My research centers on the explanation of natural and artificial cognitive systems. Many of my articles specify norms and best-practice methods for cognitive psychology, neuroscience, and explainable AI. Others develop philosophical concepts and arguments with which to better understand scientific and engineering practice. I am the PI of the DFG-funded project on Generalizability and Simplicity of Mechanistic Explanations in Neuroscience. In addition to my regular research and teaching, I do consulting work on the methodological, normative, and ethical constraints on artificial intelligence, my primary expertise being transparency in machine learning. In this context I have an ongoing relationship with the research team at neurocat GmbH, and have contributed to AI standardization efforts at the German Institute for Standardization (DIN). Before arriving in Eindhoven I was based at the Philosophy-Neuroscience-Cognition program at the University of Magdeburg, and prior to that, at the Institute of Cognitive Science at the University of Osnabrück. I received my PhD from the Indiana University Cognitive Science Program, after receiving a Master's degree in Philosophy of Mind from the University of Warwick and a Bachelor's degree in Computer Science and Philosophy from Cornell University. You can find out more about me on Google Scholar, PhilPapers, Publons, and Twitter.

Venue - Dates: AI3SD Autumn Seminar Series 2021, 2021-10-13 - 2021-12-15

Related URLs:

https://www.youtube.com/watch?...VdWw&t=10s

Keywords: AI, AI3SD Event, Artificial Intelligence, Chemistry, Data Science, Data Sharing, Machine Learning, ML, Responsible Research, Scientific Discovery

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