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Meet the Expert: Aileen Nielsen on Fairness in AI

Topic: Data
Aileen Nielsen

Unfairness often—and unintentionally—occurs in data-driven machine learning models. While practitioners recognize this problem, organizations and individual practitioners alike lack formal training or guidelines to identify and remove unfairness.

Join us for this edition of Meet the Expert with Aileen Nielsen to learn how to recognize and cope with unfairness in AI. You’ll explore opportunities to assess fairness at all stages of the machine learning pipeline and dive into state-of-the-art algorithmic approaches that will help you enhance fairness in your machine learning products.

O'Reilly Meet the Expert explores emerging business and technology topics and ideas through a series of one-hour interactive events. You’ll engage in a live conversation with experts, sharing your question

What you'll learn-and how you can apply it

By the end of this live show, you’ll better understand:

  • What fairness and unfairness in AI look like
  • How unfairness comes about
  • How you can address unfairness in AI

This Discussion is for you because...

  • You want to enhance fairness in your machine learning products.
  • You want to learn about the fundamental shifts that are transforming the business landscape and customer needs.


  • Come with your questions for Aileen Nielsen
  • Have a pen and paper handy to capture notes, insights, and inspiration

Recommended follow-up:

About our guest

  • Aileen Nielsen is a software engineer who has analyzed data in a variety of settings from a physics laboratory to a political campaign to a healthcare startup. She also has a law degree and splits her time between a deep learning startup and research as a Fellow in Law and Technology at ETH Zurich. She’s given talks around the world on fairness issues in data and modeling.


The timeframes are only estimates and may vary according to how the class is progressing

Monday, December 7, 2020, at 9:00am PT / 12:00pm ET

  • Introduction and presentation (15 minutes)
  • Interactive discussion and Q&A (45 minutes)