AI needs Diversity to reduce Gender and Racial Bias!

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Kamal Das
SME
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Artificial Intelligence is the new electricity, powering the technological revolution just like electricity enabled, believes Coursera co-founder Andrew. However, AI has a significant gender and racial bias.

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MIT discusses how computer vision is great at recognizing light-skinned males but not good at recognizing darker females. The ability of computer vision algorithms to recognize dark-skinned females is 20%- 34% poorer than its ability to recognize light-skinned males.

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Research by the University of Colorado Boulder highlights the difficulty in identifying transwomen and transmen. 

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In the research paper, Diversity in Faces by IBM Research AI, the authors highlight that most computer vision training datasets are predominantly focused on light-skinned males. Light-skinned people constitute between 80% to 95% of the images in most training databases. The datasets are also predominantly male. Historically as well, camera manufacturers have focused on light-skinned people and paid less emphasis on capturing other skin tones appropriately. 

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These results in computer vision algorithms inappropriately classify a throwback image of the former First Lady of the US (FLOTUS) as “a young man wearing a black shirt”! Why? A mere 2.5% of Google employees are Black, as per its 2018 report! Women are also under-represented, comprising around 20% of the workforce in big tech companies as per a report by Bloomberg.

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Source: MIT, 6. SI9I. Introduction to Deep Learning

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Like many other spheres in life, we need more diversity in AI. We need to actively promote people from diverse and under-represented backgrounds to join and share their views on the development of AI. Otherwise, needless to say, AI will remain biased in terms of culture, race and gender. And like a recent pop song, we’ll be left complaining “Tuada Kutta Tommy Sada Kutta Kutta.” 

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