“Fairwashing” and the Folly of ML Solutionism with Zachary Lipton

800 800 This Week in Machine Learning & AI

Today we’re joined by Zachary Lipton, Assistant Professor in the Tepper School of Business at Carnegie Mellon University and affiliate faculty in the Machine Learning Department (MLD) and Heinz school of Public Policy.

With an overarching theme of data quality and interpretation, Zachary’s research and work is focused on machine learning in healthcare, with the goal of not replacing doctors, but to assist through an understanding of the diagnosis and treatment process. Zachary is also working on the broader question of fairness and ethics in machine learning systems across multiple industries. We delve into these topics today, discussing supervised learning in the medical field, guaranteed robustness under distribution shifts, the concept of ‘fairwashing’, how there is insufficient language in machine learning to encompass abstract ethical behavior, and much, much more.

About Zachary

From the Interview

TWIMLcon Update

As we approach TWIMLcon: AI Platforms, I’d like to let you all in on our first major announcement from the conference. You all love this podcast for great guests and interviews, and we’re bringing that concept right to the TWIMLcon stage. I’m super excited to announce that Andrew Ng will be joining me on stage at TWIMLcon for a live Keynote Interview! Many of you know Andrew from his work at Stanford, Coursera or his many other efforts in the industry, including most recently founding Deeplearning.ai. Andrew and his work have been super impactful on my life and career and I know that that’s the case for many of you as well. In our conversation, we’ll be discussing the state of AI in the enterprise, the barriers to using deep learning in production and how to overcome them, his views on tooling and platforms for efficient AI delivery, and other topics from his recently published AI transformation playbook.

Be on the lookout for more great speaker announcements rolling out over the course of the next few weeks! You don’t want to miss this event! Get your ticket now at twimlcon.com/register!

Meetup Update!

Many of you are aware that we’ve been hosting a couple of paper-reading meetups in conjunction with the podcast. I’m excited to share that Matt Kenney, Duke staff researcher and long-time listener and friend of the show, has stepped up to help take this group to the next level. The paper reading meetup will now be meeting every other Sunday at 1 PM Eastern Time to dissect the latest and greatest academic research papers in ML and AI. If you want to take your understanding of the field to the next level, please join us on Sunday, July 28th, or check twimlai.com/meetup for more upcoming community events.

We’ve also got a couple of study groups currently running, one working through the fast.ai Deep Learning from the Foundations course, another on fast.ai [Natural Language Processing] (https://www.fast.ai/2019/07/08/fastai-nlp/), and another working through the Stanford cs224n Deep Learning for Natural Language Processing course. These study groups just started and will be working on these courses through October and November, so it’s not too late to join. Sign up on the meetup page at twimlai.com/meetup.

Check it out

“More On That Later” by Lee Rosevere licensed under CC By 4.0

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