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The AI experts at Monitaur explain the foundations of safe and resilient modeling systems behind the AI that impacts our lives and our businesses in our podcast, The AI Fundamentalists.
Part 2 of this series could have easily been renamed "AI for science: The expert’s guide to practical machine learning.” We continue our discussion with Christoph Molnar and Timo Freiesleben to look at how scientists can apply supervised machine learning techniques from the previous episode into their research.
What if privacy could be as dynamic and socially aware as the communities it aims to protect? Sebastian Benthall, a senior research fellow from NYU’s Information Law Institute, shows us how privacy is complex.
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Episode 19. Explore the basics of differential privacy and its critical role in protecting individual anonymity. The hosts explain the latest guidelines and best practices in applying differential privacy to data for models such as AI. Learn how this method also makes sure that personal data remains confidential, even when datasets are analyzed or hacked.
Dr. Andrew Clark is Monitaur’s co-founder and Chief Technology Officer. A trusted domain expert on the topic of ML auditing and assurance, Andrew built and deployed ML auditing solutions at Capital One. He has contributed to ML auditing education and standards at organizations including ISACA and ICO in the UK. He currently serves as a key contributor to ISO AI Standards and the NIST AI Risk Management framework. Prior to Monitaur, he also served as an economist and modeling advisor for several very prominent crypto-economic projects while at Block Science.
Andrew received a B.S. in Business Administration with a concentration in Accounting, Summa Cum Laude, from the University of Tennessee at Chattanooga, an M.S. in Data Science from Southern Methodist University, and a Ph.D. in Economics from the University of Reading. He also holds the Certified Analytics Professional and American Statistical Association Graduate Statistician certifications. Andrew is a professionally trained concert trumpeter and Team USA triathlete.
Sid Mangalik is a Ph.D. candidate in natural language processing at Stony Brook University working with Andy Schwartz. His previous studies focused on the intersection of artificial intelligence and psychology, where he worked with Ritwik Banerjee on language use in scientific writing and among abusers. Sid's previous experience also includes a role at Capital One as a Data Engineer.
His current research is working on identifying connections between community-level language and psychological outcomes. He is a Research Scientist at Monitaur, a start-up focused on making machine learning models fairer, safer, and more transparent.
