AI News, Jeff Bezos is launching a new conference dedicated to AI, optimism artificial intelligence

Why you can’t solve the gender pay gap by focusing on pay

A special message from MSN: The UK's most vulnerable children and young people face unimaginable challenges.

This isn’t for lack of trying: Many companies and governments have gender equity high on their agendas and are making concrete efforts to solve it, launching pay reviews and implementing policies.

She has thought a lot about how to solve gender gaps in the workplace—and pay, she says, is merely the symptom of a problem that starts much, much earlier than in the room where annual salary decisions are made.

If an internal hire were to be made, for example, the system would assign each candidate a score based on their skills and experience, the text in their performance reviews, and the makeup of the team they’d be joining.

In recent years, there’s been a global awakening to the need to nurture female employees in male-dominated industries—to make sure they don’t drop away when caring for children, to promote them on a par with men, and to encourage them back into roles after career breaks.

And even before careers begin, the shortage of women studying in fields like engineering and math has led to calls and programs for encouraging study of subjects that will better equip girls for future jobs.

Pymetrics, another startup, combines tools based on neuroscience with machine learning, and says it tests its algorithms on a dataset of 50,000 previous candidate profiles to make sure the system itself doesn’t have bias—a problem that has hampered efforts by companies like Amazon to build intelligent tools for hiring.

Roy’s team put computers to work on the text of employees’ performance reviews (she didn’t want to give specific numbers but said they had done this process on “over a thousand” reviews), and found that given the same text, a male employee would be given a higher numerical score compared to a woman.

Peter Thiel Is Artificial Intelligence AI Over Hyped ?

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