A NORA Webinar: The Epistemology of AI and Machine Vision
AI and machine learning have amazing potential across many fields, but they also represent a fundamentally new way of building knowledge. We have seen that there are pitfalls: there are many examples of AI being easily fooled, or making unexpected mistakes, or producing biased or discriminatory results. In this webinar Jill Walker Rettberg will show us examples of these failures of AI and machine learning. She will present different levels at which machine learning can fail, looking at datasets, proxies, objectives and more.
About Jill Walker Rettberg
Jill Walker Rettberg is Professor of Digital Culture at the University of Bergen, and leads the ERC project Machine Vision in Everyday Life: Playful Interactions with Visual Technologies in Digital Art, Games, Narratives and Social Media. She also leads the Digital Humanities Network at the University of Bergen, and has a keen interest in digital methods in the humanities, especially visualisations and network analysis. Rettberg also leads the Digital Culture Research Group, with around a dozen PhDs and postdocs in addition to several tenured members. She is a member of the Network for Games Research and Bergen Electronic Literature Research Group.
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