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MPWMost Powerful Women

Artificial Intelligence Needs Empathy and Regulation

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McKenna Moore
McKenna Moore
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By
McKenna Moore
McKenna Moore
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December 12, 2018, 7:17 PM ET
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The AI revolution is upon us.

Machine learning, one of key artificial intelligence technologies, has already been deployed within more companies than you would expect. As it gains even greater adoption, regulation and empathy should be at the forefront.

Rana el Kaliouby, co-founder and CEO of emotional AI company Affectiva, said at Fortune’s Most Powerful Women Next Gen 2018 in Laguna Niguel, Calif. on Wednesday that EQ is just as important in technology as IQ. Because of the frequency with which people interact with technology and its growing impact on our lives, it’s important that empathy be built into it, she said.

One way to do that, el Kaliouby said, is to have diverse teams work on the technology. In a example of the problem, she said that middle-aged white men usually create and train face recognition AI using images of people who look like themselves, which means the technology often doesn’t work as well, if at all, on women of color.

“It goes back to the teams designing these algorithms, and if your team isn’t diverse they aren’t going to be thinking about how this will work on a woman wearing hijab,” she said. “You solve for the problems you know.”

Navrina Singh, principal product lead of Microsoft AI, said that a perfect example of building technology with empathy in mind came to her during a project with an e-commerce site that trying to make it easier for customers in India to buy it products. Due to the low literacy rate in the country, the company built speech-to-text functionality for users who couldn’t read. Beforehand, the company made a concerted effort to train its AI in dialects and cultures from all around India, because the intent and meaning of speech varies based on background. Deciphering intent is one of the greatest challenges and opportunities in AI right now, Inhi Cho Suh, general manager of customer engagement at IBM Watson, said.

Regulation is another big topic in machine learning at the moment. With bots and other related technology becoming more sophisticated, laws are necessary to check that power, the panelists agreed. Suh said that technology and regulation should be used to prevent misuse, while el Kaliouby stressed the need for mandatory ethics training for college computer science and engineering majors.

Singh shared the acronym F.A.T.E., which stands for fairness, accountability, transparency and ethics, to sum up the key ideas to keep in mind when creating and regulating this technology. Although there is a lot of bad news about technology, like the Cambridge Analytica scandal, in which a British political firm accessed personal data on up to 87 million Facebook users, we must not let fear guide the debate, said Vidhya Ramalingham, founder of counter-terrorism technology company Moonshot CVE.

“Policy should not be written out of fear, it should be written in an educated and informed manner,” she said.

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