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{"id":134501,"date":"2022-10-11T23:44:46","date_gmt":"2022-10-11T23:44:46","guid":{"rendered":"https:\/\/aijourn.com\/?p=134501"},"modified":"2022-10-24T13:17:06","modified_gmt":"2022-10-24T13:17:06","slug":"racist-chatbots-sexist-robo-recruiters-decoding-algorithmic-bias","status":"publish","type":"post","link":"https:\/\/aijourn.com\/racist-chatbots-sexist-robo-recruiters-decoding-algorithmic-bias\/","title":{"rendered":"Racist Chatbots & Sexist Robo-Recruiters: Decoding Algorithmic Bias"},"content":{"rendered":"\n

By Omar Haroun, Relativity\u2019s Head of AI Strategy<\/p>\n\n\n\n

(The author would like to thank his colleague Apoorv Agarwal, Ph.D., CEO and Cofounder of Text IQ for providing some of the central ideas anchoring this article. Apoorv\u2019s deconstruction of the fundamental ways in which bias can percolate into AI models and his examples of systemic bias prior to the advent of AI, were particularly valuable in drafting this piece).<\/p>\n\n\n\n

When the markets were in the middle of a historic correction a few months ago, Cathie Wood, noted investor and CEO of ARK Invest, made a bold prediction:<\/a> AI could accelerate the annual global GDP rate<\/a> to 50% over the next decade. Even though Wood’s projections may seem exaggerated, we cannot deny that AI is the most significant technological breakthrough of our time. Indeed, AI is becoming ubiquitous as organizations across every sector of the economy seize upon its power to maximize productivity and automate decision-making at a scale and accuracy that is historically unprecedented.<\/p>\n\n\n\n

We may not be aware of AI\u2019s impact at an individual level, but the complex web of decision points inside an algorithm can influence both the personal and professional facets of our lives \u2014 from where we work (AI-run tools used to screen job candidates) and the mortgage we qualify for (AI-driven risk-scoring on loan applications) to who we date (AI-driven matching on dating apps), the content that we are nudged to consume (AI-powered recommendations on streaming platforms) and the medical care we receive (risk assessment algorithms used to gauge needs for referrals and specialized medical care).<\/p>\n\n\n\n

Bias: AI\u2019s Achilles Heel<\/h2>\n\n\n\n

In recent years, AI researchers, policymakers, journalists and ethicists have studied the impact of AI on individuals and societies. They have uncovered a panoply of cases where AI models made decisions that are biased and discriminatory against individuals based on their gender, racial and other demographic attributes. Here is a sampling of these cases:<\/p>\n\n\n\n