For all their differences, big tech companies agree on where we’re heading: into a future dominated by smart machines. Google, Amazon, Facebook, and Apple all say that every aspect of our lives will soon be transformed by artificial intelligence and machine learning, through innovations such as self-driving cars and facial recognition. Yet the people whose work underpins that vision don’t much resemble the society their inventions are supposed to transform. WIRED worked with Montreal startup Element AI to estimate the diversity of leading machine learning researchers, and found that only 12 percent were women.

That estimate came from tallying the numbers of men and women who had contributed work at three top machine learning conferences in 2017. It suggests the group supposedly charting society’s future is even less inclusive than the broader tech industry, which has its own well-known diversity problems.

At Google, 21 percent of technical roles are filled by women, according to company figures released in June. When WIRED reviewed Google’s AI research pages earlier this month, they listed 641 people working on “machine intelligence,” of whom only 10 percent were women. Facebook said last month that 22 percent of its technical workers are women. Pages for the company’s AI research group listed 115 people earlier this month, of whom 15 percent were women.

A Google spokesperson told WIRED that the company’s research page lists only people who have authored research papers, not everyone who implements or researches AI technology, but declined to provide more information. Facebook also declined to provide details on the diversity of its AI teams. Joelle Pineau, who leads the Montreal branch of Facebook’s AI lab, said counting the research team’s publicly listed staff was “reasonable,” but that the group is small relative to everyone at Facebook involved in AI, and growing and changing through hiring.

Percent of men and women who contributed work to three leading machine learning conferences in 2017. Source: Element AI Hotlittlepotato

Pineau is part of a faction in AI research trying to improve the field’s diversity—motivated in part by fears that failing to do so increases the chance AI systems have harmful effects on the world. “We have more of a scientific responsibility to act than other fields because we’re developing technology that affects a large proportion of the population,” Pineau says.

Companies and governments are betting on AI because of its potential to let computers make decisions and take action in the world, in areas such as health care and policing. Facebook is counting on machine learning to help it fight fake news in places with very different demographics to its AI research lab, such as Myanmar, where rumors on the company's platform led to violence. Anima Anandkumar, a professor at the California Institute of Technology who previously worked on AI at Amazon, says the risks AI systems will cause harm to certain groups are higher when research teams are homogenous. “Diverse teams are more likely to flag problems that could have negative social consequences before a product has been launched,” she says. Research has also shown diverse teams are more productive.