Causal Reasoning and Computation
Please join us at the next MSSP Social Policy Speaker Series event featuring Dr. M. Beatrice Fazi, Reader in Digital Humanities in the School of Media, Arts and Humanities at the University of Sussex, United Kingdom. Her research focuses on the ontologies and epistemologies produced by contemporary technoscience, particularly in relation to issues in artificial intelligence and computation and to their impact on culture and society. 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.
This talk will explore causality as an abstraction that could be established within contemporary computational spaces produced by artificial intelligence (AI). It will consider whether causality is part of thinking and ask whether the machines that are said to simulate human cognition should address causal reasoning. Most AI researchers would agree that, in the past decade, AI techniques focusing on data-driven automated learning (for instance, deep neural networks) have been successful in performing tasks that were once difficult to achieve computationally. While there has been a lot of progress, the same researches behind this success also express that there is still much to do. Importantly, they tend to agree that the learning performance of these AI techniques does not match that of human brains. Would the inclusion of causality help these computational systems to return better learning results? This talk will signpost some of the philosophical implications of this prospect, connecting these implications to considerations about the future of AI and of abstractive procedures of computational representation.
Please register for this event here.