Kevin Frazier in the Media

KXAN June 29, 2026

Central Texas leaders warn AI-driven layoffs could signal broader job losses

Lecturer Kevin Frazier proposes that, rather than taxing AI, policy makers should focus on rapid, public-private retraining and apprenticeship programs to prepare workers for a shifting, skills- based "portfolio economy."

Washington Examiner June 26, 2026

Trap is set: Job market is about to get crushed if Labor Department doesn’t act now

Lecturer Kevin Frazier co-authors an article arguing that AI is already transforming blue-collar work though automated management of schedules, pay, and performance, and urging policy makers to update laws to create a work environment with more fluid labor arrangements.

Fulcrum June 22, 2026

There’s No Easy Path Through the AI Transition

Lecturer Kevin Frazier argues that policy makers must take a more active role in preparing for AI-driven economic changes, advocating for stronger workforce training programs, local engagement, and practical policy solutions that help communities adapt to technological disruption.

Tech Policy Press June 15, 2026

Earning a Social License for Transformative AI

Lecturer Kevin Frazier discusses how AI labs use constitutions to guide powerful models and stressed the importance of a proposed "Peoples AI Constitution Council" to ensure public oversight and democratic control over AI models used by the government.

Marketplace June 9, 2026

Who would benefit from a U.S. wealth fund’s investment in AI?

Lecturer Kevin Frazier discusses proposals for a U.S. wealth fund to invest in artificial intelligence, emphasizing the importance of ensuring that the public shares in the benefits of AI-driven economic growth.      

The Fulcrum June 5, 2026

In Defense of “Crackpot Schemes” for AI Governance

AI Innovation and Law Fellow Kevin Frazier discusses the need for more concrete and inclusive approaches for AI governance, emphasizing that public engagement should play a larger role in shaping AI policy. He argues that citizen input can help identify both the benefits and the risks of emerging AI technologies.

Civitas Institute June 3, 2026

The Great U.S. Artificial Intelligence Jobs Transition

AI Innovation and Law Fellow Kevin Frazier argues that AI companies should help lead workforce policy experiments that Congress can later scale, especially to support younger workers affected by AI job disruption. He emphasizes that public-private partnerships, standardized metrics, and accountable training programs will be key to preparing jobs for the AI transitions.

KVUE June 1, 2026

Texas Congressman Casar proposes tax on AI companies to fund jobs program

Lecturer Kevin Frazier comments on Texas Rep. Greg Casar's proposal to tax AI tokens, explaining that token needs vary widely—from billions for Fortune 500 companies to far fewer for small businesses.

Deseret News May 31, 2026

Utah leaders are looking toward the future with optimism

In an op-ed piece, Lecturer Kevin Frazier argues that communities can address challenges related to AI, energy, housing, and infrastructure through innovation and an optimistic approach to the future.

The Fulcrum May 30, 2026

Fulcrum Roundtable: Moving From Aspirational Statements to Hands-On AI Policy

Lecturer Kevin Frazier discusses the need for more community-focused approaches to AI governance, emphasizing the importance of local engagement and policy making to help ensure that benefits of AI are broadly shared.

WSFA12 May 27, 2026

Commission on AI and kids online safety meets in Montgomery

Lecturer Kevin Frazier argues that AI shouldn't be viewed as a replacement for teachers, therapists, or parents, but rather as a tool that augments and improves the services those people already provide.

The Regulatory Review May 26, 2026

Data Privacy and AI Progress

Lecturer Kevin Frazier and Gillian Glover '27 co-author a piece arguing that outdated privacy laws in health care and education are holding back AI progress, calling on regulators to shift from data minimization to data stewardship to unlock AI's potential for improving diagnoses and learning outcomes.