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Thursday, March 24 • 10:00am - 10:45am
Understanding the Risks of Data Science

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This session highlights the opportunities and potential pitfalls for general counsel in using big data, artificial intelligence and predictive analytics to help manage their workforce and enhance employment litigation strategies. It offers examples and best practices for legal departments interested in taking advantage of all that AI and predictive analytics have to offer, but are concerned with running afoul of the various laws triggered by their applications. Topics to be covered include:
  • How big data may be used in workforce management, including: improving the process of selecting and hiring employees, creating a more objective method for conducting performance evaluations and making promotion decisions, identifying which employees are most likely to leave the company (i.e. via data scraping of publically available data sources) and testing the impact of new employment policies (such as allowing employees to work more flexible schedules).
  • The benefits of collecting and analyzing data on legal matters to spot trends and proactively manage risk. For instance, if a certain employment policy is found to be involved in lawsuits more often than others, this signals a need for additional training on the policy or changes to the policy itself.
  • How to use predictive modeling to anticipate the hard costs (such as legal fees and the settlement/award amount) and soft costs (such as the impact on personnel and brand reputation) at the onset of a case.
  • The U.S. legal system has few guideposts that translate seamlessly into the world of big data. As a result, there are a variety of laws to keep in mind in such areas as privacy, discrimination, background checks and data security.

avatar for Zev Eigen, JD, PhD

Zev Eigen, JD, PhD

Global Director of Data Analytics, Littler Mendelson

Thursday March 24, 2016 10:00am - 10:45am CDT
1) SCH127 (Schulze 1st)