The City of New York passed Local Law 144, which requires yearly “bias audits” of automated employment decision tools (AEDTs). The NYC Department of Consumer and Worker Protection held a public hearing today to accept testimony on the law prior to enacting new rules for penalties associated with violations. BABL […]
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How can test publishers and EdTech vendors use AI in their products “while still upholding fairness and avoiding discrimination and bias?” Shea Brown participates in ATP Global’s 2021 Security Summit: Assessment Excellence & Transparency with AI, on a panel entitled Using AI to Ethically Enhance the Security of Systems and Intellectual […]
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BABL is a proud associate sponsor of ForHumanity’s AT->GO conference, where the community is coming together to discuss the future of AI Governance. Our CEO Shea Brown will be speaking on two panels: “Practitioners’ corner – Audit”: 8 Sept. at 11 am EST “Plugging in AT->GO Ecosystem”: 9 Sept. at 1 pm […]
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Our own Shea Brown I had a great time talking with Demetrios Brinkmann about auditing AI and machine learning systems on the Are You A Robot? podcast. https://www.areyouarobot.co.uk/season-three/s3e6-how-to-create-an-ethical-ai-system
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What is an “algorithm audit”? Is it the same for every algorithm in every context? What metrics are important, and how do you connect these metrics to the interests of real people? Three years ago when Jovana Davidovic, Ali Hasan, and I were confronted with the prospect of doing one of these […]
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BABL CEO Shea Brown recently participated in an RMDS panel on “Data Science and AI in Government: Challenges & Applications”. The video will be posted soon.
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The rapid development of artificial intelligence (AI) and machine-learning has led to powerful algorithms that have the potential to improve lives on an unprecedented scale. However, with greater capabilities comes greater potential for harm to civil liberties. This past year was a bad year for AI, with public scandals emerging […]
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Shea Brown takes a closer look at what the recent SAT cheating scandal tells us about the future of AI transparency and accountability in EdTech. Published in Toward Data Science.
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