The U.S. Department of Labor’s “Artificial Intelligence and Worker Well-being: Principles and Best Practices for Developers and Employers” provides a roadmap for workplace AI use that centers job quality and worker voice in the rollout and use of new technologies. This resource is highly relevant for employers and AI developers seeking a framework to ethically design and deploy AI. It outlines eight core principles: centering worker empowerment; ethically developing AI, establishing AI governance and human oversight, ensuring transparency in AI use, protecting labor and employment rights, using AI to enable workers, supporting workers impacted by AI, and ensuring responsible use of worker data.The principles aim to help organizations counteract risks like algorithmic discrimination and job displacement, while using AI for purposes such as augmentation of work tasks and improving worker safety.
For all readers, this document offers a shared set of guidelines for promoting an inclusive, worker-centered approach to AI adoption. The best practices emphasize transparency about AI use, human oversight for significant employment decisions (like hiring, promotion, and discipline), and the responsible use of worker data.
This is part of a collection of resources created by the Department of Labor and other federal agencies, relating to job quality and implementing good jobs priorities through federal investments and beyond. Many of these resources are no longer publicly available on government websites, though they were all at one point public and shared with the intent of preserving these resources for public use.
Please note that we cannot guarantee that information contained in these resources related to specific programs, policies, and processes remains accurate, though many best practices and examples remain useful. In addition, many of these resources link out to government websites that do not exist anymore. You may be able to find these linked resources in the archive itself by searching the Overview document. For more resources, please visit the Data Rescue Project website, at https://www.datarescueproject.org/
