Building Pro-Worker Artificial Intelligence (www.nber.org)

A new paper titled "Building Pro-Worker Artificial Intelligence" outlines a framework that defines pro-worker technologies, including AI, as those that enhance human skills by expanding worker capabilities rather than replacing them. The authors categorize technological changes into five types: labor-augmenting, capital-augmenting, automating, expertise-leveling, and new task-creating, asserting that only the last category unambiguously supports workers by creating demand for unique human expertise. They highlight examples across various sectors, revealing that while AI's potential for automation is significant, its role as a collaborative tool—enhancing human judgment and facilitating new tasks—remains largely untapped. The paper argues that current market dynamics, such as misaligned incentives between firms and developers and a prevailing pro-automation ideology, could curb investments in pro-worker AI solutions. To counteract this trend, the authors propose nine policy recommendations aimed at aligning incentives towards pro-worker outcomes. These include targeted investments in healthcare and education, tax reforms, stronger antitrust measures, and enhanced intellectual property protections for worker expertise. This work is significant for the AI/ML community as it challenges prevailing narratives about technology's role in the workforce and advocates for a paradigm that prioritizes worker collaboration and capability enhancement over mere automation.