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House committee considers bills limiting AI use in Minnesota
Bills aim to prevent AI-driven denial of medical care and ban AI tools creating non-consensual sexual images, addressing systemic bias and exploitation risks, lawmakers say.
- Amid rising concern about AI, Minnesota House Commerce Finance and Policy Committee met Wednesday, Feb. 19, 2026, to review bills on AI harms, including nudification and insurance practices.
- Survivors testifying at the Capitol described harms, with Molly Kelley saying she deleted nearly all photos of her children after AI-generated nudification exploitation created systemic barriers for women and children.
- Plaintiffs allege insurer automation had serious errors, claiming a 90% error rate, medical residents reported AI denied glaucoma medications to patients 85 or older, and Rep. Alex Falconer shared a case where a high-school athlete with diabetes was hospitalized after an insurer denied an insulin refill.
- Business representatives cautioned that vague language could hamper beneficial AI, while Anne Neu Brindley, Minnesota Business Partnership representative, warned the bill may hinder AI that improves health outcomes and reduce costs.
- Hanson pressed for speedy action, saying `can't really afford to wait` as advocates said legislative action aims to curb exploitative deepfake tools and reform insurer prior‑authorization systems.
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House committee considers bills limiting AI use in Minnesota
ST. PAUL — Artificial intelligence has been getting a lot of attention lately, both for its increasing abilities and its risks of exploitation. Its downfalls dominated the conversation Wednesday, Feb. 19, during a House Commerce Finance and Policy Committee hearing. Rep. Alex Falconer, DFL-Minnetonka, led discussion of HF 2500, a bill that would prohibit the use of AI and algorithms in reviewing prior authorization requests for health insurance.…
·Cherokee County, United States
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Total News Sources11
Leaning Left0Leaning Right8Center3Last UpdatedBias Distribution73% Right
Bias Distribution
- 73% of the sources lean Right
73% Right
C 27%
R 73%
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