Incident 163: Facebook’s Hate Speech Detection Algorithms Allegedly Disproportionately Failed to Remove Racist Content towards Minority Groups

Description: Facebook’s hate-speech detection algorithms was found by company researchers to have under-reported less common but more harmful content that was more often experienced by minority groups such as Black, Muslim, LGBTQ, and Jewish users.


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Alleged: Facebook developed and deployed an AI system, which harmed Facebook users of minority groups and Facebook users.

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Sean McGregor, Khoa Lam
How Facebook Hides How Terrible It Is With Hate Speech · 2021

In public, Facebook seems to claim that it removes more than 90 percent of hate speech on its platform, but in private internal communications the company says the figure is only an atrocious 3 to 5 percent. Facebook wants us to believe tha…

Facebook’s race-blind practices around hate speech came at the expense of Black users, new documents show · 2021

Last year, researchers at Facebook showed executives an example of the kind of hate speech circulating on the social network: an actual post featuring an image of four female Democratic lawmakers known collectively as “The Squad.”

The poste…


A "variant" is an incident that shares the same causative factors, produces similar harms, and involves the same intelligent systems as a known AI incident. Rather than index variants as entirely separate incidents, we list variations of incidents under the first similar incident submitted to the database. Unlike other submission types to the incident database, variants are not required to have reporting in evidence external to the Incident Database. Learn more from the research paper.