HF1150

Purpose

• This bill requires Minnesota to study the environmental effects of artificial intelligence (AI) in the state. It looks at how AI models and the hardware that runs them affect energy use, pollution, water use, and other environmental factors across their full life cycle. The goal is to understand both positive and negative impacts and how they could vary by location or deployment.

Main Provisions

• By January 1, 2027, the commissioner of the Pollution Control Agency must submit a report on AI’s environmental impacts to the chairs and ranking minority members of the legislative committees with jurisdiction over environment policy and energy policy.
• The report must include: 1) An assessment of energy consumption and pollution across the full lifecycle of AI models (design, development, deployment, use). 2) An assessment of energy consumption and pollution across the full lifecycle of AI hardware (extraction of raw materials, manufacturing, and electronic waste). 3) An assessment of energy and water use for cooling data centers used in the design, development, deployment, and use of AI models. 4) An assessment of how design, development, deployment, and use choices (including model efficiency, location, power source, data center design, and hardware type) affect environmental impacts. 5) Identification of potential environmental impacts that could be acute at local scales (e.g., added power loads that stress the grid, water withdrawals causing water stress, or local noise). 6) Identification of positive environmental benefits from AI (e.g., improving energy efficiency, advancing renewable energy, enabling environmental monitoring, aiding discovery of new materials, and monitoring environmental changes automatically). 7) Identification of negative environmental impacts from AI (e.g., rebound effects, behavioral impacts, and accelerating high-pollution activities). 8) Identification of disparate or unequal impacts within the negative environmental effects of AI. 9) An estimate of Minnesota’s likely impact from the identified factors under different AI deployment scenarios. 10) Any other relevant environmental impacts the commissioner determines.
• The study must provide opportunities for engagement with stakeholders (including experts in relevant subjects) and with interested members of the general public.

Funding and Appropriation

• In fiscal year 2026, funds from the general fund are appropriated to the Pollution Control Agency to conduct the study and prepare the required report.

Process and Stakeholder Engagement

• The commissioner must involve stakeholders with relevant knowledge or expertise and must also engage interested members of the general public during the study and reporting process.

Significance and Policy Impact

• This bill creates a vetting process to understand AI’s environmental footprint before any policy changes. It does not immediately change existing environmental law, but it could inform future Minnesota policy decisions on AI and energy use, data centers, and sustainability.

Key Dates and Timelines

• Report due by January 1, 2027.
• Funding allocated for fiscal year 2026 to conduct the study.

Relevant Terms - Artificial intelligence, AI models, AI hardware, energy consumption, pollution, lifecycle, design, development, deployment, use, raw materials extraction, manufacturing, electronic waste, data centers, cooling, energy, water consumption, grid stress, water stress, noise, model efficiency, power source, data center design, disparate impacts, rebound effects, environmental monitoring, renewable energy, stakeholder engagement, general public, Pollution Control Agency, Environmental policy, Energy policy, Minnesota.