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Make Data Work
September 11, 2018: Training & Tutorials
September 12–13, 2018: Keynotes & Sessions
New York, NY

Beyond explainability: Regulating machine learning in practice

Andrew Burt (Immuta)
2:55pm–3:35pm Wednesday, 09/12/2018
Law, ethics, governance, Strata Business Summit
Location: 1E 12/13 Level: Non-technical
Secondary topics:  Data preparation, governance and privacy, Ethics and Privacy
Average rating: *****
(5.00, 2 ratings)

Who is this presentation for?

  • Anyone with an interest in governing AI and controlling risk in ML

What you'll learn

  • Explore a few key regulations geared toward complex software systems, such as credit scoring regulations like the Equal Credit Opportunity Act in the US and the GDPR in the EU
  • Learn key recommendations for governing ML in practice

Description

Machine learning (ML) is is becoming increasingly prevalent across industries, creating new types and new levels of risk. Managing this risk is quickly becoming the central challenge of major organizations, one that strains data science teams, legal personnel, and the C-suite alike. How organizations approach manage this risk will determine their ability to fully make use of ML and in some cases, their long-term success or failure.

However, the current approach to managing risk in ML is extremely limited and will only get organizations so far. Currently, attempts to address risk in ML are approached through the lens of explainability, with a focus on understanding the “black box” of ML models. But the future of ML risk management is going to be focused on much more than explaining the inner workings of these models.

Andrew Burt shares key lessons from past regulations focused on complex, opaque technology along with a proposal for new ways to effectively manage risk in ML.

Photo of Andrew Burt

Andrew Burt

Immuta

Andrew Burt is chief privacy officer and legal engineer at Immuta, the data management platform for the world’s most secure organizations. He is also a visiting fellow at Yale Law School’s Information Society Project. Previously, Andrew was a special advisor for policy to the head of the FBI Cyber Division, where he served as lead author on the FBI’s after-action report on the 2014 attack on Sony. The leading authority on the intersection between machine learning, regulation and law, Andrew has published articles on technology, history, and law in the New York Times, the Financial Times, Slate, and the Yale Journal of International Affairs. His book, American Hysteria: The Untold Story of Mass Political Extremism in the United States, was called “a must-read book dealing with a topic few want to tackle” by Nobel laureate Archbishop Emeritus Desmond Tutu. Andrew holds a JD from Yale Law School and a BA from McGill University. He is a term-member of the Council on Foreign Relations, a member of the Washington, DC, and Virginia State Bars and a Global Information Assurance Certified (GIAC) cyber incident response handler.