Manage AI bias instead of trying to eliminate it to remediate the bias built into AI data, companies can take a three-step approach

The negative effects of bias in artificial intelligence models’ underlying data has made headlines, and companies need to find ways to address it. But it’s impossible to completely abolish bias in AI data to equitably account for diverse populations — so instead, companies should remediate it to del...

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Bibliographic Details
Main Author: Townson, Sian
Format: eBook
Language:English
Published: [Cambridge, Massachusetts] MIT Sloan Management Review 2022
Edition:[First edition]
Subjects:
Online Access:
Collection: O'Reilly - Collection details see MPG.ReNa
Description
Summary:The negative effects of bias in artificial intelligence models’ underlying data has made headlines, and companies need to find ways to address it. But it’s impossible to completely abolish bias in AI data to equitably account for diverse populations — so instead, companies should remediate it to deliberately compensate for unfairness. The author describes a three-step process that can yield positive results for leaders looking to reduce the impact of AI bias
Item Description:Reprint 64321
Physical Description:5 pages