If you think about artificial intelligence and the core components of what makes an AI, you have the fact that it’s given a goal and then will find a way to reach that goal. It’s then often very un-transparent as to how it reached that goal. If you’re building into a machine some unconscious bias, you might not know that it’s there; the output could be detrimental to women and it’s very tough to work out exactly why that has happened.
In traditional technology, you can see [what has happened]: women dying in car crashes because the crash-test dummies were the shape of a man rather than the shape of a woman. [With AI there could be] similar life-or-death situations, in drug trials or in autonomous vehicles and things like that.
There are some examples of [gender bias in AI today]: Google ads displaying higher-earning [job] ads to men than women. We can hypothesize other types of situations that would happen—what if women weren’t as able to get loans or mortgages or insurance?
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