Is There a Process Level Approach to Regulating Machine Learning?

Corporate governance of AI doesn’t sound like a sexy topic, but it’s rapidly becoming one of the most important challenges for big companies that rely on machine learning models to deliver value for their customers. More and more, they’re expected to develop and implement governance strategies to reduce the incidence of bias, and increase the transparency of their AI systems and development processes. Those expectations have historically come from consumers, but governments are starting impose hard requirements, too.

So for today’s episode, I spoke to Anthony Habayeb, founder and CEO of Monitaur, a startup focused on helping businesses anticipate and comply with new and upcoming AI regulations and governance requirements. Anthony’s been watching the world of AI regulation very closely over the last several years, and was kind enough to share his insights on the current state of play and future direction of the field.

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Intro music:

➞ Artist: Ron Gelinas

➞ Track Title: Daybreak Chill Blend (original mix)

➞ Link to Track: https://youtu.be/d8Y2sKIgFWc

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Chapters:

- 0:00 Intro

- 1:45 Anthony’s background

- 6:20 Philosophies surrounding regulation

- 14:50 The role of governments

- 17:30 Understanding fairness

- 25:35 AI’s PR problem

- 35:20 Governments’ regulation

- 42:25 Useful techniques for data science teams

- 46:10 Future of AI governance

- 49:20 Wrap-up