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Machine Learning Pitfalls and the Perils of Big Data Hiring Analytics

Complimentary webinar: Machine Learning Pitfalls and the Perils of Big Data Hiring Analytics

Mark Girouard, JD, a litigation-tested employment defense attorney and Eric Sydell, PhD, Shaker’s vice president of research and innovation

Tuesday, December 13, 2016 at 1:00 p.m. EDT

Employers are increasingly turning to big data solutions to find, recruit, and hire job candidates. These tools have the potential to greatly reduce recruiting costs while streamlining hiring processes. But they present a host of legal and other business risks. One example of such significant risk includes a seemingly neutral algorithm that may create or perpetuate discrimination based on race, sex, or other protected characteristics. A more fundamental peril would be that conclusions drawn from statistical correlations unearthed in big data may not, in fact, provide employers with meaningful information about an applicant's future job performance.

In this webinar, we will explore how big data is influencing the world of pre-employment selection, including how traditional assessment validation methods can be leveraged to enhance the legal defensibility of big data solutions and what hurdles need to be cleared to realize their promise.

Webinar topics include:

  • What is big data and how is it changing the employment selection landscape?
  • What are the legal risks and other challenges to big data selection tools?
  • What questions should you be asking big data vendors to ensure they are addressing these risks?
  • How can you use job analysis and related techniques to improve the validity and reduce the risks of these tools?
  • What predictions can we make about future hiring trends in a big data world?

Save your seat today!