Overview
Nearly 30 western state legislators convened in Sacramento for an intensive, non-partisan workshop on the opportunities, challenges, and policy implications of artificial intelligence (AI). Organized by CSG West and the AAAS EPI Center, the event aimed to strengthen lawmakers’ understanding of AI technologies and support evidence-based policymaking across sectors such as education, healthcare, workforce, and environmental regulation.
Over two days, participants engaged with national AI experts, examined case studies, and participated in hands-on exercises designed to translate technical understanding into actionable state policy strategies.
Major Takeaways
1. Transparency and Accountability Are Cornerstones of AI Governance
Legislators stressed the public’s right to know when and how AI is used in consequential decisions.
Action Implications:
- Require disclosure when AI tools influence hiring, healthcare, education, or public benefits decisions.
- Mandate audits and third-party testing to identify bias or malfunction.
- Introduce adverse event reporting systems for AI failures.
2. Human Oversight Must Remain Central
Consensus emerged that AI should augment, not replace human judgment.
Policy Actions:
- Require human sign-off on critical healthcare, education, and government decisions.
- Prohibit mandatory AI use in schools or public services without human review.
- Ensure accountability for outcomes remains with people, not algorithms.
3. Consumer and Citizen Protection Is Foundational
AI systems can perpetuate bias and discrimination without strong guardrails.
Policy Actions:
- Define and prohibit algorithmic discrimination in law.
- Create enforcement mechanisms for transparency and fairness.
- Protect children and vulnerable groups from harmful AI applications and misinformation.
4. Workforce Impacts Demand Immediate Attention
AI disproportionately affects younger and entry-level workers, particularly in technology and service sectors.
Action Implications:
- Invest in retraining and workforce transition programs.
- Partner with employers and educational institutions to identify emerging skill needs.
- Track AI’s labor market impacts to inform targeted interventions.
5. Environmental Sustainability Cannot Be Ignored
AI’s growth is driving unprecedented energy and water consumption through data centers.
Policy Actions:
- Standardize reporting on data centers’ water and energy use.
- Coordinate between energy and water agencies to address local impacts.
- Promote use of non-potable water and advanced cooling technologies.
6. States Are Leading the Way
With limited federal regulation, states are shaping the AI governance landscape.
- In 2024, 107 of 150–160 AI bills were enacted at the state level.
- 41 states have established 61 AI commissions.
- States like Colorado and Utah are setting contrasting but complementary models — one emphasizing consumer protection, the other innovation and governance infrastructure.
Next Step: Expand interstate collaboration to share model legislation and implementation lessons.
Highlights from Sessions
- Technical Foundations (Dr. Inioluwa Deborah Raji): Legislators learned how bias and “black box” systems create real-world harm — reinforcing the need for audits and accountability.
- Risk Mitigation (Dr. Sanmi Koyejo): Recommended safety testing, third-party evaluation, and continuous monitoring pre- and post-deployment.
- AI in Education (Dr. H. Chad Lane): AI can enhance instruction and reduce teacher burden but must preserve teacher control and student critical thinking.
- AI and Work (Dr. Bharat Chandar): Data show automation hits young workers hardest — calling for targeted retraining and data-driven labor policy.
- Data Center Sustainability (Dr. Shaolei Ren): Urged integrated energy-water management and community engagement in siting decisions.
- State Policy Models (Colorado Rep. Jennifer Bacon & Utah Rep. Doug Fiefia): Both emphasized bipartisan collaboration, expert advisory bodies, and public transparency.
- Practical Governance (Alan Fuller, CIO, Utah): Demonstrated real-world success — 48 AI projects improving efficiency while maintaining strict oversight.
Legislative Action Framework
| Focus Area | Recommended Actions |
| Governance & Oversight | Establish AI offices or commissions; create expert advisory panels; institutionalize oversight within committees. |
| Transparency & Accountability | Require disclosure of AI use; mandate audits and training data transparency; include public comment periods. |
| Consumer Protection | Define algorithmic discrimination; regulate sector-specific AI risks; prevent mandatory AI use without oversight. |
| Education & Workforce | Expand AI literacy; invest in retraining; support educators integrating AI responsibly. |
| Environment & Infrastructure | Require reporting of data center resource use; promote sustainable technologies and water reuse. |
| Interstate & International Collaboration | Share model policies; engage sovereign nations and tribes; monitor global AI regulatory trends. |
Impact
The workshop equipped legislators with:
- Practical tools to draft, debate, and refine AI legislation.
- Peer examples from leading states advancing AI policy.
- Connections to national experts for continued guidance.
- Frameworks for balancing innovation, ethics, and equity in state governance.
Next Steps
- CSG West and the AAAS EPI Center will conduct follow-up interviews with select participants.
- Additional materials and presentations are available at:
🔗 AAAS EPI Center Workshop Resources - Legislators are encouraged to share insights with colleagues and consider introducing or refining AI-related legislation in 2026 sessions.
Conclusion
This workshop reaffirmed that effective AI governance does not require deep technical expertise—but it does require leadership rooted in transparency, human oversight, consumer protection, equity, and sustainability. Western states are proving to be innovation laboratories for AI policy, modeling thoughtful approaches that safeguard citizens while encouraging responsible technological growth.