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Navigate the road to Responsible AI

Deploying AI ethically and responsibly will involve cross-functional team collaboration, new tools and processes, and proper support from key stakeholders. Find out how to implement AI responsibly—join our free webinar Responsible AI in Practice on December 15 to learn about fairness, AI in the law, and AI security from experts. The use of machine learningContinue reading “Navigate the road to Responsible AI”

Gradient Flow #22: AI Security, Time-series Databases, Concept Drift

Subscribe • Previous Issues This edition has 482 words which will take you about 3 minutes to read. “They beat me up unjustly, but since they did the same thing to everyone else, it was not unfair.”  – Sydney Morgenbesser Data Exchange podcast Securing machine learning applications  Ram Shankar is a Berkman Klein Center affiliate, and aContinue reading “Gradient Flow #22: AI Security, Time-series Databases, Concept Drift”

Gradient Flow #21: Detecting Fake News, AutoBI, Feature Stores

Subscribe • Previous Issues This edition has 459 words which will take you about 3 minutes to read. “Any figure that looks interesting or different is usually wrong.” – W.A. Twyman. Data Exchange podcast The Computational Limits of Deep Learning   Neil Thompson is a research scientist at the Computer Science and Artificial Intelligence Lab (CSAIL) andContinue reading “Gradient Flow #21: Detecting Fake News, AutoBI, Feature Stores”

Responsible AI in Practice: A virtual event

Register Can’t make it to the live webinar? Register so you can watch it on-demand. As interest in machine learning and AI continues to grow, companies are realizing the complexities inherent not only in the technology itself, but in the responsible implementation of the technology. Responsible AI is a framework that brings together best practicesContinue reading “Responsible AI in Practice: A virtual event”

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