[A version of this post appears on the O’Reilly Radar.] The O’Reilly Data Show Podcast: Sharad Goel and Sam Corbett-Davies on the limitations of popular mathematical formalizations of fairness. In this episode of the Data Show, I spoke with Sharad Goel, assistant professor at Stanford, and his student Sam Corbett-Davies. They recently wrote a surveyContinue reading “Why it’s hard to design fair machine learning models”
Tag Archives: ethics
Data regulations and privacy discussions are still in the early stages
[A version of this post appears on the O’Reilly Radar.] The O’Reilly Data Show Podcast: Aurélie Pols on GDPR, ethics, and ePrivacy. In this episode of the Data Show, I spoke with Aurélie Pols of Mind Your Privacy, one of my go-to resources when it comes to data privacy and data ethics. This interview tookContinue reading “Data regulations and privacy discussions are still in the early stages”
Managing risk in machine learning models
[A version of this post appears on the O’Reilly Radar.] The O’Reilly Data Show Podcast: Andrew Burt and Steven Touw on how companies can manage models they cannot fully explain. 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.Continue reading “Managing risk in machine learning models”
How to build analytic products in an age when data privacy has become critical
Privacy-preserving analytics is not only possible, but with GDPR about to come online, it will become necessary to incorporate privacy in your data products. In this post, I share slides and notes from a talk I gave in March 2018 at the Strata Data Conference in California, offering suggestions for how companies may want to buildContinue reading “How to build analytic products in an age when data privacy has become critical”
The importance of transparency and user control in machine learning
[A version of this post appears on the O’Reilly Radar.] The O’Reilly Data Show Podcast: Guillaume Chaslot on bias and extremism in content recommendations. In this episode of the Data Show, I spoke with Guillaume Chaslot, an ex-YouTube engineer and founder of AlgoTransparency, an organization dedicated to helping the public understand the profound impact algorithms have on ourContinue reading “The importance of transparency and user control in machine learning”
We need to build machine learning tools to augment machine learning engineers
We need to build machine learning tools to augment our machine learning engineers. In this post, I share slides and notes from a talk I gave in December 2017 at the Strata Data Conference in Singapore offering suggestions to companies that are actively deploying products infused with machine learning capabilities. Over the past few years,Continue reading “We need to build machine learning tools to augment machine learning engineers”