BOKISSONTHRONE: Meet the 5 Women Advocating for Inclusive and Unbiased For AI, a real-world reality check

An intelligent computer is only as well-rounded as the people who teach it.

“When you have a diverse range of future technologists, they really care that technology is being used for the good of humanity.”

—Fei-Fei Li, Google & Stanford

For the past three summers, around two dozen would-be computer scientists have come to Stanford University to learn about artificial intelligence from some of the field’s brightest. The attendees, culled from hundreds of applicants, take day trips to nearby tech companies, interact with social robots and hexacopters, and learn about computational linguistics (what machines do when words have multiple meanings, say) and the importance of time management (very). They play Frisbee. But if your mental picture of AI is a bunch of guys creating wilier enemies for their favorite videogames, well, this isn’t that. All the students here at the Stanford Artificial Intelligence Laboratory’s Outreach Summer (SAILORS) program are girls who have just completed ninth grade, and their studies focus on finding ways to improve lives, not enhance their game play: How do we use AI to keep jumbo jets from careening into one another? To ensure that doctors wash their hands before hitting the OR? “Our goal was to rethink AI education in a way that encourages diversity and students from all walks of life,” says Fei-Fei Li, director of Stanford’s AI lab and a founder of the SAILORS program. “When you have a diverse range of future technologists, they really care that technology is being used for the good of humanity.”

SAILORS was created in 2015 by Li and former student Olga Russakovsky (now an assistant professor at Princeton University) to help bring greater gender equality to the tech industry. The cause is both noble and urgent. According to a recent survey, the number of women seeking computer science degrees is dropping; in the AI sector, women hold less than 20 percent of executive positions. It’s an enormous field to be left out of, considering that, every day, more and more people use AI to make their lives easier and more efficient: AI is how photo apps recognize your face among everyone else's, not to mention the beach where you took the picture. It's how your devices understand you when you ask what the weather will be tomorrow. Then there are the lesser-known applications, like diagnosing diabetic retinopathy (which often leads to blindness) or sending a drone on a search-and-rescue mission to the most remote reaches of the world.

With AI becoming ever more ubiquitous, the need for gender balance in the field grows beyond just the rightness of the cause—diversity is a crucial piece of AI due to the nature of machine learning. A goal of AI is to prod machines to complete tasks that humans do naturally: recognize speech, make decisions, tell the difference between a burrito and an enchilada. To do this, machines are fed vast amounts of information—often millions of words or conversations or images—just as all of us absorb information, every waking moment, from birth (in essence, this is machine learning). The more cars a machine sees, the more adept it is at identifying them. But if those data sets are limited or biased (if researchers don’t include, say, images of Trabants), or if the folks in AI don’t see or account for those limits or biases (maybe they’re not connoisseurs of obscure East German automobiles), the machines and the output will be flawed. It’s already happening. In one case, image recognition software identified photographs of Asian people as blinking.

“It’s not just about having transparency in data. We actually need to make the numbers move in the right direction.”

—Tracy Chou, Project Include

“Making these AI tools really easy to use, and making these techniques possible for everyone to apply, is just so critical.”

—Christine Robson, Google

“Start them young and get them strong in their confidence, so that when they walk into the room and they’re the only ones there, they don’t turn around.”

—Diana Williams, Lucasfilm