Protests Shine Light On Facial Recognition Tech Problems

Monday, Jan 11, 2021

In a special extended interview, listen to Ruha Benjamin and Deborah Raji discuss practical steps for developing artificial intelligence technologies in a way that leads to more equity and equal justice—whether it’s tech companies being ready to slow down, or government standards that take racial justice into account.

Extended Cut

Earlier this month, three major tech companies publicly distanced themselves from the facial recognition tools used by police: IBM said they would stop all such research, while Amazon and Microsoft said they would push pause on any plans to give facial recognition technology to domestic law enforcement.

IBM CEO Arvind Krishna explained the move was because of facial recognition’s use in racial profiling and mass surveillance. Facial recognition algorithms built by companies like Amazon have been found to misidentify people of color, especially women of color, at higher rates—meaning when police use facial recognition to identify suspects who are not white, they are more likely to arrest the wrong person.

Nevertheless, companies have been pitching this technology to the government. Just this week, the American Civil Liberties Union (ACLU) uncovered documents showing Microsoft has been trying to sell facial recognition to the federal government’s Drug Enforcement Administration since at least 2017, calling into question exactly how to define ‘police.’ Beyond facial recognition, Amazon’s tech already helps power the databases of government agencies like ICE that are responsible for the recent crackdowns on immigration.

CEOs are calling for national laws to govern this technology, or programming solutions to remove the racial biases and other inequities from their code. But there are others who want to ban it entirely—and completely re-envisioning how AI is developed and used in communities.

SciFri producer Christie Taylor talks to Ruha Benjamin, a sociologist, and AI researcher Deborah Raji about the relationship between AI and racial injustice, and their visions for slower, more community-oriented processes for tech and data science.

Further Reading

[Originally published on June 16, 2020 via Science Friday]

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