Presented By
O’Reilly + Cloudera
Make Data Work
29 April–2 May 2019
London, UK
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How to keep ethical with machine learning

11:1511:55 Thursday, 2 May 2019
Data Science, Machine Learning & AI, Expo Hall
Location: Expo Hall (Capital Hall N24)
Secondary topics:  Ethics
Average rating: *****
(5.00, 3 ratings)



Prerequisite knowledge

  • Familiarity of machine learning and its real-world applications

What you'll learn

  • Learn how to build AI forensics tools, use those tools to profile the algorithm, use the profile to anticipate behavior, and discuss the anticipated behavior with a diverse risk mitigation team


The current wave of artificial intelligence works by using computer models to simulate intelligent behavior. Machine learning algorithms are good at learning new behaviors but bad at identifying when those behaviors are harmful or don’t make sense. Companies deploying AI will need a workforce trained to ensure that the technology remains both useful and safe.

We creators have a lot of experience dealing with intelligent beings—one another. Much of the basic common sense that we have developed for such dealings is applicable to machine learning: observe the AI and understand it. Predict the most likely behavior and decide whether any risk is worth the benefit. And so on.

Jerry Overton uses this common sense to build a checklist for protecting against ethical violations with ML. Jerry shares best practices for building AI forensics tools, using those tools to profile the algorithm, using the profile to anticipate behavior, and discussing the anticipated behavior with a diverse risk mitigation team.

Jerry Overton


Jerry Overton is a data scientist and fellow in the Analytics Group and the global lead for artificial intelligence at DXC. Jerry is the author of Going Pro in Data Science: What It Takes to Succeed as a Professional Data Scientist from O’Reilly and teaches the live online training course Mastering Data Science at Enterprise Scale: How to Design and Implement Machine Learning Solutions That Improve Your Organization. In his blog, Doing Data Science, Jerry shares his experiences leading open research and transforming organizations using data science.

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Mark Madsen | FELLOW
4/05/2019 1:19 BST

Any chance you’ll post the slides?