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EPISODE · Apr 12, 2019 · 39 MIN

Algorithmic Bias

from Cognitive Engineering

What happens when algorithms learn to be biased? What does that even mean? We talk to special guest Dr Jess Whittlestone from the Leverhulme Centre for the Future of Intelligence about whether algorithmic bias is something to worry about, and whether anything can be done about it? Things mentioned in this podcast Danks and London (2017): A taxonomy of types and sources of algorithmic bias Jess Whittlestone (https://jesswhittlestone.com/), and at the Leverhulme Centre for the Future of Intelligence - http://www.csap.cam.ac.uk/network/jess-whittlestone/ The Equality Act 2010 - https://www.gov.uk/guidance/equality-act-2010-guidance For more information on Aleph Insights visit our website https://alephinsights.com or to get in touch about our podcast email [email protected] This podcast uses the following third-party services for analysis: Podtrac - https://analytics.podtrac.com/privacy-policy-gdrp

Episode metadata supplied by the publisher feed · Published Apr 12, 2019

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What happens when algorithms learn to be biased? What does that even mean? We talk to special guest Dr Jess Whittlestone from the Leverhulme Centre for the Future of Intelligence about whether algorithmic bias is something to worry about, and whether anything can be done about it? Image: CBS Television via Wikipedia Things mentioned in this podcast Danks and London (2017): A taxonomy of types and sources of algorithmic bias - https://www.cmu.edu/dietrich/philosophy/docs/london/IJCAI17-AlgorithmicBias-Distrib.pdf Jess Whittlestone (https://jesswhittlestone.com/), and at the Leverhulme Centre for the Future of Intelligence - http://www.csap.cam.ac.uk/network/jess-whittlestone/ The Equality Act 2010 - https://www.gov.uk/guidance/equality-act-2010-guidance For more Cognitive Engineering episodes find us on iTunes, Google Play or wherever you get your podcasts, or add this RSS feed to your preferred player: http://feeds.soundcloud.com/users/soundcloud:users:219479129/sounds.rss

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Algorithmic Bias

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