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Facebook starts building AI with an ethical compass

The social network's engineers have a tool called Fairness Flow to find bias in their algorithms. Also: Facebook open-sourced an AI that plays StarCraft.

Facebook research scientist Isabel Kloumann, speaking at F8, discusses the company's efforts to ensure its AIs behave ethically.

Screenshot by Stephen Shankland/CNET

As Facebook's artificial intelligence technology gets smarter and more important to the social network's sprawling business, the company is working to keep its AI systems from ethical lapses.

The company has built a system called Fairness Flow that can measure for potential biases for or against particular groups of people, research scientist Isabel Kloumann said at Facebook's F8 conference on Wednesday.

"We wanted to ensure jobs recommendations weren't biased against some groups over others," Kloumann said, so it checks for differences in treating men versus women or people under 40 years old versus people older, she said. That's probably helpful given Silicon Valley's struggles to deal with sex and age discrimination.

It's a good time for Facebook to be working on its ethics smarts. The company is under fire for lapses of its own when it comes to protecting its 2 billion users' privacy and for letting Russians manipulate US elections through Facebook. Chief Executive Mark Zuckerberg on Tuesday pledged to do better, and on Wednesday, Facebook announced it's using AI to remove posts from its social network that involve nudity, graphic violence, terrorist content, hate speech, spam, fake accounts and suicide.

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Fairness Flow began with hiring, but it's available for other operations now.

Avoiding biased AIs

"Now we're working to scale the Fairness Flow to evaluate the personal and societal implications of every product that we build. As a step in that direction, we've integrated the Fairness Flow into our internal machine learning platform," Kloumann said. "Any engineer can plug in to this technology and evaluate their algorithms for bias."

Bias is a problem for today's artificial intelligence technology and the machine learning processes behind it. AIs learn from real-world data, a process that produces spectacular results for things like image recognition but can let in biases in the original source material. For example, if training data shows more photos with women in kitchens than with men in them, then AIs can pick up that signal.

AI is a curiously academic part of the computing industry, as evidenced by things like Apple researchers' insistence they be allowed to publish research papers.

Other Facebook AI projects

Facebook has one of the top AI programs in tech, and the company is starting to show more of what it's up to. At F8, it touted several projects, most of them open-source software so others can retrace Facebook's steps, learn from them and perhaps improve on them -- although without Facebook's massive computing resources, it can be tough to keep up.

Among the other projects:

Many of the projects are detailed on the new Facebook.ai site the company launched Wednesday.

First published May 2, 12:11 p.m. PT.
Update, 1:04 p.m.:
Adds details about other AI projects.

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