As companies commercialize novel applications of AI in areas such as finance, hiring, and public policy, there’s concern that these automated decision-making systems may unconsciously duplicate social biases, with unintended societal consequences. Drawing on her legal and engineering experience working for and with companies engaging in AI innovation, Laila Paszti shares practical advice for companies to counteract such prejudices through a legal- and ethics-based approach to innovation.
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Laila Paszti is a lawyer practicing technology and privacy law at GTC Law Professional Corp. She’s also a software applications engineer. She previously held positions at ExxonMobil and Capstone Technology, where she designed and implemented machine learning (AI) software solutions to optimize industrial processes. She routinely advises both Fortune 100 and startup clients on all aspects of the development and commercialization of their technology solutions (including big data, predictive modeling, and machine learning) in diverse industries including fintech, healthcare, and the automotive industry. She’s a steering committee member of the Toronto Machine Learning Symposium and will be a panel member discussing responsible AI innovation in November. She has spoken most recently at the Global Blockchain Conference, the Healthcare Blockchain in Canada conference, and the Linux FinTech Forum. Laila will be a faculty member for the upcoming Osgoode Certificate in Blockchains, Smart Contracts, and the Law (November 2018). She holds a BASc in chemical engineering from the University of Toronto, an MASc in chemical engineering from the University of Waterloo, and a JD from the University of Toronto, where she was a law review editor. She is admitted to practice in New York and Ontario. She’s also a Certified Information Privacy Professional (Canada) (CIPP/C).
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I really enjoyed the great discussion I had with attendees of my session. Please do keep in touch and best of luck with your machine learning algorithms!