MN HF3980

Requires online platforms operating in Minnesota that use algorithmic recommender systems based on personal data to publicly disclose a list of all algorithms used, descriptions of inputs and data sources, and algorithm weights categorized by importance quartiles

Mandates that algorithmic recommender systems be configured by default to maximize "long-term user value" (users' deliberate preferences and aspirations) rather than engagement metrics, with special protections for minors

Requires platforms to provide accessible interfaces allowing users to specify preferences for recommended and blocked content types, and prohibits platforms from degrading service quality for users who exercise these rights

Obligates covered platforms to maintain holdout groups for at least 12 months to assess algorithm design changes, publish annual disclosures of long-term user value metrics, and obtain independent audits of these assessments

Violations constitute unfair and deceptive trade practices enforceable by the Attorney General, with private right of action providing $5,000 per user per violation (or actual damages), $7,000 punitive damages for reckless/knowing violations, plus attorney fees and injunctive relief