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

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

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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.

Does your company use machine learning? Here’s how to think about the risks

If you’re using machine learning in your organization, you probably should be thinking about how to manage the ethical, legal, and business risks involved if something goes wrong. But according to a new paper from the Future of Privacy Forum and the College Park, Maryland, data management platform startup Immuta, there simply isn’t an industry…

Machine Learning’s Dirty Secret

Underneath all the hype and the headlines and the money pouring into artificial intelligence and machine learning, there’s a dirty secret. That secret? Almost no one knows how to utilize the technology at scale. More precisely, only a very small handful of organizations truly understand how to manage the risks of machine learning (ML) when…

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.