Yippee, newsletter number three!

Wrangling with ethical AI

Last week I spent a day at the Wrangle Conference in San Francisco, guest of the team at Cloudera who organizes the event. This was the third Wrangle conference ever, and the second I’ve been able to attend.

Wrangle is a pretty interesting conference. It aims to bring a diverse community of data scientists to an intimate and informal setting (think cowboy hats and BBQ) to discuss real data science projects and issues. It does a nice job at that. But what it does a GREAT job at is surfacing some of the ethical issues surrounding data science, machine learning & AI.

A standout example of this from last year’s event was Abe Gong’s Ethics for Powerful Algorithms talk, which suggested that attendees perform “ethics reviews” of their algorithms, and provided a framework for doing so.

This time around, the talks that moved me most were along the same lines. In particular, Drew Conway’s talk on the interplay between our cognitive biases and our roles as data scientists, strategists and consumers was great. Also great was Tyler Schnoebelen’s talk (picture below) on The Ethics of Everybody Else, which argued that to be ethical, systems that classify human beings must consider the goals of the people affected by the system, not just those of their builders.

Trust in Bias: Wrangling Ethical AI

The whole area of ethical AI is an important one that I’m looking forward to exploring further on the podcast. Please give me a shout if you’d like to hear more on this topic, or if there are particular people you’d like to hear from.

And stay tuned for interviews with Drew, Sharath Rao, and Erin Shellman. (Only Drew’s talk touched on ethical issues—Sharath’s and Erin’s talks were about building data products and pipelines, respectively.)

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