Thursday, March 7

11:00 am - 11:40 am

Nathaniel M. Glasser

Partner
Epstein Becker & Green, P.C.

As predictive analytics have revolutionized marketing practices in corporate America, companies increasingly apply predictive analytical processes to Human Resources functions. These “people analytics” techniques promise to efficiently and effectively identify the best candidates for open positions, reduce turnover, and eliminate subjectivity and bias from HR processes.  There are, however, several legal risks.  For example, these techniques may perpetuate stereotypes and disparately impact certain populations, pose thorny issues for people with disabilities, and must be compliant with emerging domestic and international privacy regulations.  Before adopting any particular predictive analytical tool, companies should assess the pros and cons of incorporating people analytics into employment decisions, identify the associated legal and practical implications, and address the potential for regulatory review.

In this session you will:

  • Get a comprehensive survey of employment law landscape and how people analytics are impacting it.
  • Learn the factors to consider and potential pitfalls to avoid when deploying people analytics in your organization.
  • Get answers to your questions about the legal implications of people analytics.

About Nathaniel M. Glasser

NATHANIEL M. GLASSER is a Member of the Firm in the Employment, Labor & Workforce Management practice, office of Epstein Becker Green, a national law firm that represents employers in all aspects of employment law compliance and litigation.  Nathaniel is a member of the Firm’s Artificial Intelligence and Technology, Media & Telecommunications practice groups, and he also co-leads the Health Employment and Labor (HEAL) strategic industry group.  In addition to representing clients in complex employment litigation and counseling employers on human resources compliance issues, Nathaniel focuses his time advising clients on novel issues of employee relations, such as the impact of big data on the employment life cycle, the implementation of people (or predictive) analytics in the workplace, and creating effective training programs to address #MeToo and harassment, workplace violence prevention, and other key issues.


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