ACLU Comment on the Department of Labor’s AI Guidelines for Employers and Vendors

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WASHINGTON — Yesterday, the U.S. Department of Labor (DOL) released a roadmap for artificial intelligence (AI) best practices, designed to ensure that emerging technologies such as AI enhance job quality, benefit workers, and comply with existing employment laws when they are used in the workplace.

The best practices, pursuant to President Biden’s executive order on the development and use of AI, include recommendations for AI system developers and employers that prioritize workers’ experiences and empowerment throughout the entire AI lifecycle – from design to use and oversight. These practices also call on employers and developers to create standards and processes to identify and mitigate risks from AI systems, such as threats to health and safety, civil rights, privacy, fair labor rights, and labor organizing prior to a developer marketing them or an employer deploying them, and recommend turning to different systems when sufficient mitigation is not possible.

“We applaud DOL for issuing best practices for use of AI that center workers’ empowerment, civil rights, privacy, and safety protections and call on developers and employers to adopt critical guardrails in developing, procuring and using AI systems. Employers and developers should take note, as many have been burying their heads in the sand on their risk of legal liability with respect to AI tools,” said Olga Akselrod, senior staff attorney of the ACLU Racial Justice Program. “Following these best practices for AI can help employers and developers ensure that they do not violate existing civil rights and other employment laws that protect workers.”

The best practices also recommend transparency measures through conducting and publishing impact assessments, notice and recourse for impacted workers, and measures to minimize worker displacement. The DOL also stated that employers should minimize electronic monitoring and avoid unnecessary collection or retention of worker data.