Tag Archives: Tricia Bozyk Sherno

The Supreme Court’s Upcoming Affirmative Action Decision: Potential Implications for Private-Sector Employers

by Jyotin Hamid, Simone S. Hicks, Mary Beth Hogan, Arian M. June, Tricia Bozyk Sherno, Rachel Tennell, and Katelyn Masket

Photos of the authors

Top row from left to right: Jyotin Hamid, Simone S. Hicks, Mary Beth Hogan, and Arian M. June.
Bottom row from left to right: Tricia Bozyk Sherno, Rachel Tennell, and Katelyn Masket.
(Photos courtesy of Debevoise & Plimpton LLP)

The Supreme Court of the United States is expected to issue a widely anticipated decision next month concerning the permissibility of race-conscious affirmative action in higher education in the Harvard College and University of North Carolina cases.[1] Although these cases arise in the context of education, not employment, and do not formally concern laws governing private-sector employment, we expect that the decision may have far-reaching implications for how courts, lawmakers, employers, and employees address efforts to promote diversity in private-sector workplaces. In particular, the decision may have an impact on how employers navigate the line between permissible efforts to promote workplace diversity and avoiding so-called “reverse discrimination” lawsuits brought by employees who may claim that they are disadvantaged by such efforts.

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NYC’s AI Hiring Law Is Now Final and Effective July 5, 2023

by Avi Gesser, Anna Gressel, Jyotin Hamid, Tricia Bozyk Sherno, and Basil Fawaz

Photos of the authors

From left to right: Avi Gesser, Anna Gressel, Jyotin Hamid, and Tricia Bozyk Sherno (Photos courtesy of Debevoise & Plimpton LLP)

The New York City Department of Consumer and Worker Protection (the “DCWP”) has adopted final rules (the “Final Rules”) regulating the use of artificial intelligence for hiring practices. The DCWP’s Automated Employment Decision Tool Law (the “AEDT Law” or the “Law”) requires covered employers to conduct annual independent bias audits and to post public summaries of those results. To recap, the DCWP released an initial set of proposed rules on September 23, 2022, and held a public hearing on November 4, 2022. Due to the high volume of comments expressing concern over the Law’s lack of clarity, the DCWP issued a revised set of proposed rules on December 23, 2022, and held a second public hearing on January 23, 2023. After issuing the Final Rules, the DCWP delayed enforcement of the Law for the second time from April 15, 2023 to July 5, 2023.

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Regulators Should Treat AI Like Employees to Avoid Stifling Innovation

by Avi Gesser, Jehan A. Patterson, Tricia Bozyk Sherno, Frank Colleluori, and Anna R. Gressel

We recently wrote about how rights-based regulatory regimes for artificial intelligence (as opposed to risk-based frameworks) can lead to a misallocation of resources because compliance will require too much effort on low-risk AI (e.g., spam filters, graphics generation for games, inventory management, etc.) and not enough effort on AI that can actually pose a high risk of harm to consumers or the public (e.g., hiring, lending, underwriting, etc.). In this follow-up blog post, we discuss why regulators should view AI risk the same way as employee risk for large companies, and accordingly adopt risk-based regulatory frameworks for AI.

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Complying with New York’s AI Employment Law and Similar Regulations

by Avi Gesser, Jyotin Hamid, Tricia Bozyk Sherno, Anna Gressel, Scott M. Caravello, and Rachel Tennell

A growing number of employers are turning to artificial intelligence (“AI”) tools to assist  500 companies use talent-sifting software, and more than half of human resource leaders in the U.S. leverage predictive algorithms to support hiring. Widespread adoption of these tools has led to concerns from regulators and legislators that they may be inadvertently discriminating, for example, by:

  • Penalizing job candidates with gaps in their resumes, leading to a bias against older women who have taken time off for childcare;
  • Recommending candidates for interviews who resemble the company’s current leadership, which is not diverse; or
  • Using automated games that are unfairly difficult for individuals with disabilities to evaluate employees for promotions, even though they could do the job with a reasonable accommodation.

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Debevoise Coronavirus Checklists—Cybersecurity

by Luke Dembosky, Jeremy Feigelson, Avi Gesser, Jim Pastore, Lisa Zornberg, Tricia Bozyk Sherno, Hilary Davidson, and Christopher S. Ford

As companies dust off their Business Continuity Plans to prepare for possible disruptions and remote working due to COVID-19, here are 10 cybersecurity considerations to add to the list of preparations: Continue reading