Sometime around 1 am on a warm night last June, Fei-Fei Li was sitting in her pajamas in a Washington, DC, hotel room, practicing a speech she would give in a few hours. Before going to bed, Li cut a full paragraph from her notes to be sure she could reach her most important points in the short time allotted. When she woke up, the 5'3" expert in artificial intelligence put on boots and a black and navy knit dress, a departure from her frequent uniform of a T-shirt and jeans. Then she took an Uber to the Rayburn House Office Building, just south of the US Capitol.

Before entering the chambers of the US House Committee on Science, Space, and Technology, she lifted her phone to snap a photo of the oversize wooden doors. (“As a scientist, I feel special about the committee,” she said.) Then she stepped inside the cavernous room and walked to the witness table.

The hearing that morning, titled “Artificial Intelligence—With Great Power Comes Great Responsibility,” included Timothy Persons, chief scientist of the Government Accountability Office, and Greg Brockman, cofounder and chief technology officer of the nonprofit ­OpenAI. But only Li, the sole woman at the table, could lay claim to a groundbreaking accomplishment in the field of AI. As the researcher who built ImageNet, a database that helps computers recognize images, she’s one of a tiny group of scientists—a group perhaps small enough to fit around a kitchen table—who are responsible for AI’s recent remarkable advances.

That June, Li was serving as the chief AI scientist at Google Cloud and was on leave from her position as director of the Stanford Artificial Intelligence Lab. But she was appearing in front of the committee because she was also the cofounder of a nonprofit focused on recruiting women and people of color to become builders of artificial intelligence.

It was no surprise that the legislators sought her expertise that day. What was surprising was the content of her talk: the grave dangers brought on by the field she so loved.

December 2018. Subscribe to WIRED. Axis of Strength

The time between an invention and its impact can be short. With the help of artificial intelligence tools like ImageNet, a computer can be taught to learn a specific task and then act far faster than a person ever could. As this technology becomes more sophisticated, it’s being deputized to filter, sort, and analyze data and make decisions of global and social consequence. Though these tools have been around, in some way or another, for more than 60 years, in the past decade we’ve started using them for tasks that change the trajectory of human lives: Today artificial intelligence helps determine which treatments get used on people with illnesses, who qualifies for life insurance, how much prison time a person serves, which job applicants get interviews.

Those powers, of course, can be dangerous. Amazon had to ditch AI recruiting software that learned to penalize résumés that included the word “women.” And who can forget Google’s 2015 fiasco, when its photo identification software mislabeled black people as gorillas, or Microsoft’s AI-powered social chatbot that started tweeting racial slurs. But those are problems that can be explained and therefore reversed. In the pretty near future, Li believes, we will hit a moment when it will be impossible to course-correct. That’s because the technology is being adopted so fast, and far and wide.

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Li was testifying in the Rayburn building that morning because she is adamant her field needs a recalibration. Prominent, powerful, and mostly male tech leaders have been warning about a future in which artificial-intelligence-driven technology becomes an existential threat to humans. But Li thinks those fears are given too much weight and attention. She is focused on a less melodramatic but more consequential question: how AI will affect the way people work and live. It’s bound to alter the human experience—and not necessarily for the better. “We have time,” Li says, “but we have to act now.” If we make fundamental changes to how AI is engineered—and who engineers it—the technology, Li argues, will be a transformative force for good. If not, we are leaving a lot of humanity out of the equation.