{"id":194936,"date":"2021-07-19T18:23:34","date_gmt":"2021-07-19T12:53:34","guid":{"rendered":"https:\/\/www.jigsawacademy.com\/?p=194936"},"modified":"2022-03-28T11:04:53","modified_gmt":"2022-03-28T05:34:53","slug":"ai-needs-diversity-to-reduce-gender-and-racial-bias","status":"publish","type":"post","link":"https:\/\/www.jigsawacademy.com\/blogs\/expert-speak\/ai-needs-diversity-to-reduce-gender-and-racial-bias\/","title":{"rendered":"AI needs Diversity to reduce Gender and Racial Bias!"},"content":{"rendered":"

Artificial Intelligence is the new electricity<\/a>, powering the technological revolution just like electricity enabled, believes Coursera co-founder\u00a0Andrew<\/span>. However, AI has a significant gender and racial bias.<\/span><\/p>\n

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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%<\/a> poorer than its ability to recognize light-skinned males<\/span>.<\/span><\/p>\n

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Research by the University of Colorado Boulder<\/span><\/a> highlights the difficulty in identifying transwomen and transmen.\u00a0<\/span><\/p>\n

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In the research paper, Diversity in Faces by IBM Research AI<\/a><\/span>, 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<\/a><\/span> and paid less emphasis on capturing other skin tones appropriately.\u00a0<\/span><\/p>\n

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These results<\/a> in computer vision algorithms inappropriately classify a throwback image of the former First Lady of the US (FLOTUS) as \u201ca young man wearing a black shirt\u201d<\/span>! Why? A mere 2.5% of Google employees are Black, as per its 2018 report<\/a><\/span>! Women are also under-represented, comprising around 20% of the workforce in big tech companies as per a report by Bloomberg.<\/span><\/p>\n

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\u00a0<\/span><\/p>\n

Source: MIT, 6. SI9I. Introduction to Deep Learning<\/span><\/p>\n

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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\u2019ll be left complaining \u201cTuada Kutta Tommy Sada Kutta Kutta.\u201d\u00a0<\/span><\/p>\n

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Artificial Intelligence is the new electricity, powering the technological revolution just like electricity enabled, believes Coursera co-founder\u00a0Andrew. However, AI has a significant gender and racial bias. 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 […]<\/p>\n","protected":false},"author":168,"featured_media":194954,"comment_status":"open","ping_status":"open","sticky":false,"template":"","format":"standard","meta":[],"categories":[1496,1262,1126],"tags":[],"form":[],"acf":[],"_links":{"self":[{"href":"https:\/\/www.jigsawacademy.com\/wp-json\/wp\/v2\/posts\/194936"}],"collection":[{"href":"https:\/\/www.jigsawacademy.com\/wp-json\/wp\/v2\/posts"}],"about":[{"href":"https:\/\/www.jigsawacademy.com\/wp-json\/wp\/v2\/types\/post"}],"author":[{"embeddable":true,"href":"https:\/\/www.jigsawacademy.com\/wp-json\/wp\/v2\/users\/168"}],"replies":[{"embeddable":true,"href":"https:\/\/www.jigsawacademy.com\/wp-json\/wp\/v2\/comments?post=194936"}],"version-history":[{"count":7,"href":"https:\/\/www.jigsawacademy.com\/wp-json\/wp\/v2\/posts\/194936\/revisions"}],"predecessor-version":[{"id":224186,"href":"https:\/\/www.jigsawacademy.com\/wp-json\/wp\/v2\/posts\/194936\/revisions\/224186"}],"wp:featuredmedia":[{"embeddable":true,"href":"https:\/\/www.jigsawacademy.com\/wp-json\/wp\/v2\/media\/194954"}],"wp:attachment":[{"href":"https:\/\/www.jigsawacademy.com\/wp-json\/wp\/v2\/media?parent=194936"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"https:\/\/www.jigsawacademy.com\/wp-json\/wp\/v2\/categories?post=194936"},{"taxonomy":"post_tag","embeddable":true,"href":"https:\/\/www.jigsawacademy.com\/wp-json\/wp\/v2\/tags?post=194936"},{"taxonomy":"form","embeddable":true,"href":"https:\/\/www.jigsawacademy.com\/wp-json\/wp\/v2\/form?post=194936"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}