The lecture series takes place as an online-event. The zoom link for the lecture will be made available in good time via the SFB’s mailing list. Guests can register with Damaris Lehmann by email. Send an email
M. Beatrice Fazi (University of Sussex): “Causality and the Future of Deep Learning”
This talk will offer a philosophical perspective on the future of deep learning. In the past decade, the successes of deep neural networks have brought the cognitive aspects of learning to the fore of artificial intelligence (AI) research. While the learning performance of artificial neural networks has been discussed in various ways, researchers tend to agree that this performance does not match that of human brains. The talk will consider how AI researchers are addressing the limitations and shortcomings of current state-of-the-art deep learning: it will focus on arguments claiming that more efficient, flexible and versatile deep learning can be achieved if and when these computational systems will learn to understand causal relations and cause-effect questions. The talk will address the issue of causality in AI and the concept of causation in philosophy to analyse how learning is linked to generalisation, reasoning, inference and to diverse modes of agency.
M. Beatrice Fazi is Reader in Digital Humanities in the School of Media, Arts and Humanities at the University of Sussex (United Kingdom). Her primary areas of expertise are the philosophy of computation, the philosophy of technology and the emerging field of media philosophy. Her research focuses on the ontologies and epistemologies produced by contemporary technoscience, particularly in relation to issues in artificial intelligence and computation. She has published extensively on the limits and potentialities of the computational method, on digital aesthetics and on the automation of thought. Her monograph Contingent Computation: Abstraction, Experience, and Indeterminacy in Computational Aesthetics was published by Rowman & Littlefield International in 2018.
