Blog2020-03-11T00:16:44+00:00
24Jan, 2020

Top 10 ways your Machine Learning models may have leakage

Jan 24, 2020|

Top 10 ways your Machine Learning models may have leakage Rayid Ghani, Joe Walsh, Joan Wang If you’ve ever worked on a real-world machine learning problem, you’ve probably introduced (and hopefully discovered and fixed) leakage into your system at some point. [...]

21Mar, 2018

Why what Cambridge Analytica did was Unacceptable

Mar 21, 2018|

Why what Cambridge Analytica did was Unacceptable And how we can future-proof against it The last few days, we’ve all been hearing about Cambridge Analytica, the Trump Campaign, and their use of Facebook data in the 2016 campaign. Some of you [...]

29Apr, 2016

You Say You Want Transparency and Interpretability?

Apr 29, 2016|

You Say You Want Transparency and Interpretability? We keep hearing and saying that in order to implement and correctly use machine learning and predictive models, they must be transparent and interpretable. That makes sense. You don’t want a black box model making [...]

22Aug, 2013

One-to-One (Personalized) Public Policy

Aug 22, 2013|

One-to-One (Personalized) Public Policy One of the primary reasons I joined University of Chicago was the chance to be at the intersection of Computation, Data, and Policy, and work on large-scale social problems that lead to an impact on public policy. [...]