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ARTICLE · 10 JANUARY 2024

A Framework For Assessing AI Risk

Mayer Brown
Mayer Brown
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Mayer Brown

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Dominique Shelton Leipzig is featured in this story.

United StatesTechnology
Dominique Shelton Leipzig
Dominique Shelton Leipzig
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Dominique Shelton Leipzig is featured in this story.

While it's easy to get swept up in the many promises of artificial intelligence, there are mounting concerns about its safety and bias. Medical algorithms have exhibited bias that impacts disadvantaged populations, as have AI-enabled recruiting tools. AI facial recognition has led to wrongful arrests, and generative AI has the tendency to "hallucinate," or make things up.

These scenarios highlight the importance of taking a proactive approach to AI governance to set the stage for positive results. While some technologies can be implemented and revisited periodically, responsible AI requires a more hands-on governance approach, according to Dominique Shelton Leipzig, a partner at Mayer Brown, who leads the law firm's global data innovation practice. AI governance should start at the earliest stages of development and be reinforced with constant tending and evaluation.

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This Mayer Brown article provides information and comments on legal issues and developments of interest. The foregoing is not a comprehensive treatment of the subject matter covered and is not intended to provide legal advice. Readers should seek specific legal advice before taking any action with respect to the matters discussed herein.

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