In this session hear from Dr. Lewis Baker, Director of Data Science Strategy at pymetrics, on the differences between unbiased and de-biased data and how to use them to build your best (most diverse) workforce. See examples of how you can measure certain attributes in de-biased ways and steps you can take to de-bias your existing data.
About the series
This is one part of our five part series: Reimagining People Data to Build a Workforce for the Future.
For HR leaders today, it’s clear now more than ever that what’s worked in the past won’t work for the future of acquiring and managing talent. Jobs and skills in
demand are changing rapidly and relying on past experience is no longer the best predictor of future success. Hiring diverse talent becomes more urgent
everyday and traditional ways of screening and assessing candidates include significant bias.
This series is meant to help you learn more about the data you need and how to harness it to build and maintain your best workforce.
For HR leaders today, it’s clear now more than ever that what’s worked in the past won’t work for the future of acquiring and managing talent. Jobs and skills in
demand are changing rapidly and relying on past experience is no longer the best predictor of future success. Hiring diverse talent becomes more urgent
everyday and traditional ways of screening and assessing candidates include significant bias.
This series is meant to help you learn more about the data you need and how to harness it to build and maintain your best workforce.
Prefer to read a summary of the session? Check out this blog post