Beyond Explainability: A Practical Guide to Managing Risk in Machine Learning Models

Beyond Explainability Webinar
October 15, 2018, 3:00 PM EST

Register Now

Join Immuta and Future of Privacy Forum to learn best practices on safely deploying ML across your organization. In June, Immuta and FPF released the first-ever standard for managing risk in AI and machine learning (download the white paper below). In this webinar, experts from Immuta and FPF will present lessons learned from that white paper. In addition, we will feature Walid Mehanna, Head of Data & Analytics for Mercedes-Benz, to provide first-hand expert commentary on the Immuta and FPF framework, drawing on his deep experience deploying ML across a range of contexts and production environments.

Andrew Burt Chief Privacy Officer and Legal Engineer,
Immuta
Brenda Leong Senior Counsel and Director of Strategy,
Future of Privacy Forum
Walid Mehanna Head of Data & Analytics,
Mercedes-Benz
Stuart Shirrell Legal Engineer,
Immuta
George Wang 2018 Immuta Scholar; J.D. Candidate, Yale Law School

“How can we govern a technology its creators can’t fully explain?”

Download the Paper

Can Enterprises Govern Machine Learning At Scale?

Traditional approaches to governing artificial intelligence (AI) and machine learning (ML) focused on explaining how models function internally. But these approaches are currently preventing the adoption of ML across the enterprise. In this whitepaper, Immuta and the Future of Privacy Forum provide the first-ever standard for managing risk in AI and ML, focusing on both practical processes and technical best practices “beyond explainability” alone. The ultimate goal of this whitepaper is to enable the safe, ethical, and high-impact use of ML.

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Managing Risk in Machine Learning on The O’Reilly Data Show Podcast

Immuta CTO Steve Touw and CPO Andrew Burt joined Ben Lorica, Chief Data Scientist at O'Reilly Media, on The O’Reilly Data Show Podcast to talk about on how companies can manage models they cannot fully explain. Click here to listen.