Understanding Bias in Data

Combat Injustice with Just Data (On-Demand)

Free Online Bootcamp

On-Demand Recording

Examples of injustice will often make the news, but the roots of the sensational have their foundation in the mundane.

Increasingly, the technology we create and the decisions we make are grounded in data. From healthcare to economics to facial recognition to self-driving cars, the who and how of the underlying code and analysis has an instrumental impact on our everyday lives. Too often, that impact can be disproportionately harmful to vulnerable and marginalized people.

Join Princeton University’s Dr. Ruha Benjamin, Data Society’s Merav Yuravlivker and Harvard’s Matthew Finney for an insightful two day Bootcamp:

  • Unlock an understanding of the kinds of bias that exist in data and artificial intelligence
  • Understand the impact that unconscious bias can have
  • Take action by grasping the role you can play as a technologist to identify and tackle bias.

Day 1: Keynote


In this talk, Ruha presents the concept of the “New Jim Code" to explore a range of discriminatory designs that encode inequity: by explicitly amplifying racial hierarchies, by ignoring but thereby replicating social divisions, or by aiming to fix racial bias but ultimately doing quite the opposite.

Ruha Benjamin

Dr. Ruha Benjamin
Associate Professor of African American Studies, Princeton University

Dr. Ruha Benjamin is an Associate Professor in the Department of African American Studies at Princeton University, where she studies the social dimensions of science, technology, and medicine, race and citizenship, knowledge, and power. She is also the founder of the IDA B. WELLS Just Data Lab, and a Faculty Associate in the Center for Information Technology Policy, Program on History of Science, Center for Health and Wellbeing, Program on Gender and Sexuality Studies, and Department of Sociology. She serves on the Executive Committees for the Program in Global Health and Health Policy and Center for Digital Humanities.

Day 2: Workshop with Merav Yuravlivker and Matthew Finney

  • What is the impact of biased data? Use cases and examples
  • What are the different types of biased data? How can we recognize it?
  • How can we identify bias in data, and what can we do about it
Merav Yuravlivker
CEO and Co-Founder, Data Society

The CEO and Co-Founder of Data Society, a Washington, D.C.-based analytics training and advisory firm. Data Society delivers customized corporate data science training programs and consulting services to transform the way that businesses and government agencies operate. Built on real-world use cases and practical data science solutions, Data Society works with staff at every level from executives to analysts to bridge the data communication gap and empower professionals to solve tough challenges.
Matthew Finney
Matthew Finney
Data Scientist, Harvard

Matthew applies data to advise and implement strategic decisions that enhance human outcomes. His current research focuses on statistical methods and computation at scale, as well as practical mitigation strategies for the ethical challenges these tools present. Previously, he has led advanced analytics consulting teams, introduced quantitative hypothesis-testing to executive decision making, and researched and developed AI/ML applications. He is currently pursuing his M.S. in Data Science at Harvard.

Our Day 2 workshop is presented in conjunction with Data Society.

Headshot photo

Data Society has been recognized by Forbes as a top ten EdTech company and has won numerous awards for their innovation in the training space. Their clients include NASA, Discover, Amtrak, CapitalOne, US Air Force, U.S. Army, U.S. State Department, and more. Learn more at

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