Always an issue with complex models, especially ones that are not very transparent. We always did risk models in parallel. Managing risk in machine learning models The O'Reilly Data Show Podcast: Andrew Burt and Steven Touw on how companies can manage models they cannot fully explain. Hurry--early price ends July 27. Subscribe to the O'Reilly Data Show Podcast to explore the opportunities and techniques driving big data, data science, and AI.

On April 12, at offices of the healthcare incubator MATTER at the Merchandise Mart in downtown Chicago, as well as streamed live online, Andrew Burt, chief privacy officer and legal engineer at the data management company Immuta, delivered a lecture entitled "Regulating Artificial Intelligence: How to Control the Unexplainable" in which he focused on the ethical, legal, and regulatory issues surrounding the deployment of machine learning systems. Sponsored by all three UChicago Graham School Professional Masters degree programs--Biomedical Informatics (MScBMI), Analytics (MScA), and Threat and Response Management (MScTRM)--the catalyst for the occasion was Sam Volchenboum, MD, PhD, MS, director of the Center for Research Informatics at UChicago, and faculty director for the BMI program, whose encounter with Burt at a recent South by Southwest conference led to an exchange of ideas he saw as immediately relevant to the Graham School programs. "As a physician, I'm seeing the use of machine learning algorithms all over the hospital and all over medicine," Dr. Volchenboum said. "We just plow ahead with developing our models and our predictions. But it wasn't until I spoke with Andrew that I really stopped and thought about the implications of these algorithms and how they can be used in both good and also bad ways. It was an eye-opening experience and I've been really excited about bringing Andrew here to talk ever since."

Check out Andrew Burt's talk "Beyond Explainability: Regulating Machine Learning In Practice" at the Strata Data Conference in New York, September 11-13, 2018. Hurry--early price ends July 27. Subscribe to the O'Reilly Data Show Podcast to explore the opportunities and techniques driving big data, data science, and AI. Find us on Stitcher, TuneIn, iTunes, SoundCloud, RSS. In this episode of the Data Show, I spoke with Andrew Burt, chief privacy officer at Immuta, and Steven Touw, co-founder and CTO of Immuta.

As a lawyer on the staff of the FBI Cyber Division, Andrew Burt spent a good deal of time looking at the intersection of national security and technology. That meant looking at policy in an organization charged to look at massive amounts of sensitive data. Now, as chief privacy officer and legal engineer at startup Immuta Inc., he is one among a new cadre working to bring more data governance to machine learning, the artificial intelligence-style technology that is moving from laboratories into mainstream computing. Machine learning algorithms are something of a black box for governance, as the technology does not necessarily disclose how it reached its decisions. To cast some light on this black box and what it means to data governance, we recently connected with Burt to discuss sensitive data processing at scale.