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If Done Right, AI Could Make Policing Fairer

By Wired

July 23, 2020

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A decade ago, Fei-Fei Li, a professor of computer science at Stanford University, helped demonstrate the power of a new generation of powerful artificial intelligence (AI) algorithms. She created ImageNet, a vast collection of labeled images that could be fed to machine learning programs. Over time, that process helped machines master certain human skills remarkably well when they have enough data to learn from.

Since then, AI programs have taught themselves to do more and more useful tasks, from voice recognition and language translation to operating warehouse robots and guiding self-driving cars. But AI algorithms have also demonstrated darker potential, for example as a means of automated facial recognition that can perpetuate race and gender bias. Recently, the use of facial recognition software in law enforcement has drawn condemnation and prompted some companies to swear off selling to police.

Li herself has ridden the ups and downs of the AI boom. In 2017 she joined Google to help, in her words, "democratize" the technology. Not long after, the company, and Li herself, became embroiled in a controversy over supplying AI to the military through an effort known as Maven, and attempting to keep the project quiet.

A few months after the blowup, Li left Google and returned to Stanford to colead its new Human-Centered Artificial Intelligence (HAI) institute. She also cofounded AI4All, a nonprofit dedicated to increasing diversity in AI education, research, and policy. In May, she joined the board of Twitter.

Li spoke with WIRED senior writer Will Knight over Zoom from her home in Palo Alto. This transcript has been edited for length and clarity.

 

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