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'The Reach of Fairness' - Ethics in AI Annual Lecture with Professor Joshua Cohen
Discussions of fairness and machine learning have been painting on too small a canvass. My talk aims to broaden the scope of normative discourse about machine learning and algorithmic decision making. Beginning from an understanding of fair cooperation among free and equal persons as a fundamental political value, I argue that concerns about fairness and machine learning need to be expanded in three ways. First, unfairness and discrimination are not only a matter of group subordination. I consider forms of anti-discrimination that are not about disadvantaged groups but about removing barriers to opportunity, and suggest practical implications for algorithmic decisions. Secondly, I underscore the limits of a focus on fair organizational decisions in advancing equality of opportunity. Finally, drawing on Rawls, I present aspects of a fair society that are not simply matters of equal opportunity, and consider some broader, under-explored ramifications of algorithms and AI on societal fairness. Specifically, I suggest the implications that AI deployment at scale has for fair distribution of wealth and resources and fair political liberties.
Date:
6 June 2024, 17:00
Venue:
Cheng Kar Shun Digital Hub, Jesus College, Oxford
Speaker:
Professor Joshua Cohen (Apple University)
Organiser contact email address:
aiethics@philosophy.ox.ac.uk
Host:
Professor John Tasioulas (University of Oxford)
Booking required?:
Required
Booking url:
https://www.oxford-aiethics.ox.ac.uk/event/ethics-ai-annual-lecture-professor-joshua-cohen-cheng-kar-shun-digital-hub-jesus-college
Booking email:
aiethicsevents@philosophy.ox.ac.uk
Cost:
Free
Audience:
Public
Editors:
Marie Watson,
Lauren Czerniawska
