Why Is Artificial Intelligence Biased Against Women?


With the rapid growth of machine learning, artificial intelligence and it’s related technologies, technologists are just beginning to reckon with the repercussions of our unconscious biases.

Amazon, for example, had to scrap a four-year-old recruitment matching tool because it had taught itself to favor male applicants over female ones. Equally qualified female candidates were ranked lower than their male counterparts, with some graduates of all-female colleges losing whole points due to their alma mater. The system was trained on data submitted by applicants over a 10-year period, who were overwhelmingly male (73% of Amazon’s leadership is male). Despite the company building the technology to be neutral, it still taught itself to be biased based on the data it was given by the people who built it, which reflected their reality – a (majority white) male-dominated industry.

AI’s race and gender biases are a result of who has the power in the backroom. Over 70% of all computer programmers are white males and despite our best attempts at neutrality, we were raised in a society that inherently devalues women and POC, teaching us both explicitly and implicitly that they are less capable than white men. This colors our worldview and in turn, the technology we create; we aren’t necessarily actively misogynistic or racist but our environment allows us to perpetuate the biases ingrained in us by society unchallenged.

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Acting Against the Passive Biases
It’s up to tech companies to do the work behind the scenes to make sure that AI and its relatives are as equitable as they can be. It’s not enough to simply acknowledge that there is a problem, especially when it’s a problem we can fix. We, including myself, a white male at the top of a rising AI-based recruitment platform, must amplify the voices of the women and POC, who are being actively disenfranchised by our passive biases. We must make conscious decisions to elevate the POC and women around us to roles where they are part of the decision making the process. We have to listen when they tell us about the ways our privilege is clouding our judgment and advocate for and work with them to fix the issues. We need to make sure our hiring strategies are deliberately diverse because right now, they’re passively biased and it’s not helping anyone.

Equality isn’t the same as equity. The balance of power in the field is too greatly shifted in one direction for us to simply wait for someone else to make the change – we need to work on eliminating the barriers altogether. Not just for the women and POC we know personally and tell us their stories, but so that we – the privileged – can be better ourselves. Isn’t that why we became technologists in the first place – to make the world a better place?

Source : https://www.hrtechnologist.com/articles/diversity/why-is-artificial-intelligence-biased-against-women/

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