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April 29-30, 2018: Training
April 30-May 2, 2018: Tutorials & Conference
New York, NY

Avoiding biased algorithms: Lessons from the hiring space

Lindsey Zuloaga (HireVue)
11:05am–11:45am Wednesday, May 2, 2018
Models and Methods
Location: Nassau East/West
Average rating: *****
(5.00, 1 rating)

Who is this presentation for?

  • Data scientists, AI practitioners, and anyone interested in AI fairness

What you'll learn

  • Understand the factors that contribute to bias in machine learning algorithms
  • Learn techniques for checking for and mitigating bias
  • Explore how machine learning algorithms that are held to high standards are currently used in hiring to overcome human biases


There have been many headlines of algorithms gone wrong: racist bots, failing financial markets, and unfair practices in law enforcement, loan approval, and hiring. Not only are these outcomes harmful; they’re a PR nightmare for the people who built the algorithms behind them. So how can these situations be avoided? Lindsey Zuloaga shares experiences and lessons learned in the hiring space to help others prevent unfair modeling and explains how to establish best practices. Lindsey demonstrates how, contrary to these examples, AI can actually help us overcome bias and improve diversity and explains how her team uses machine learning algorithms to overcome implicit and explicit bias in hiring.

To give one example, algorithms that predict job performance from video interviews have input features that make them essentially blind to many of the characteristics humans unfairly use to evaluate others (age, race, gender, etc.). Still, as we have seen in many of the examples of algorithms gone wrong, features that are correlated to a protected class may persist. In these cases, there are systematic ways to isolate and mitigate bias. These practices should be standard in any situation where algorithms are being used to score or evaluate people.

Photo of Lindsey Zuloaga

Lindsey Zuloaga


Lindsey Anderson-Zuloaga is director of data science at HireVue. She is very interested in how AI can help humans make better decisions. Lindsey holds a PhD in experimental physics.