- Insurance Regulations by State (Nearmap)
Nearmap, an aerial imagery provider, tracks how US states regulate insurers’ use of aerial images in underwriting and nonrenewal. More than a dozen states now have rules, and a recurring theme is that imagery should be one input among several, never the sole basis for dropping a policy. It’s a useful reference from a geospatial firm mapping the limits placed on its own product.
https://www.nearmap.com/solutions/insurance-regulations-by-state
2. SB 5928: Concerning wildfire risk models and score disclosure (Washington State Legislature)
A 2026 Washington bill, requested by the state’s insurance commissioner. It would require insurers that use a wildfire risk score to tell policyholders their score, the range of possible scores, who created it and when, and to give them a right to appeal. Similar bills were introduced this year in Hawaii, Oregon and New Mexico.
https://lawfilesext.leg.wa.gov/biennium/2025-26/Pdf/Bills/Senate%20Bills/5928.pdf
3. New Records Obtained by EFF Expose More Problems with Medicare’s AI Experiment (Electronic Frontier Foundation, 27 October 2026)
More than 800 pages of records on Medicare’s AI prior-authorisation pilot. They show CMS privately flagging problems with four of its six AI vendors, including denials that appeared inaccurate. The key section argues that a human in the loop only protects anyone if the reviewer has the time and practical authority to override the AI.
https://www.eff.org/deeplinks/2026/10/new-records-obtained-eff-expose-more-problems-medicares-ai-experiment
4. California’s “No Robo Bosses Act” (SB 947): What Employers Need to Know (Sweta Patel, Potomac Law Group, 23 October 2026)
A clear guide to California’s new law on AI in discipline and termination. Patel makes the point that corroboration isn’t a rubber stamp: a reviewer who finds no support for an output has disqualified it. She advises giving reviewers written authority to reject a result, and notes that monitoring flags and quality scores may be covered.
https://www.potomaclaw.com/news-PLG-Californias-No-Robo-Bosses-Act-SB-947-What-Employers-Need-to-Know
5. California to Require Human Corroboration of AI-Driven Discipline and Termination (Nicholas Spencer, AALRR, 23 October 2026)
Spencer opens with a scenario every manager will recognise: a dashboard ranks an employee bottom of the team, a manager acts, and “the system identified the problem” becomes the explanation. From July 2027 that won’t be enough in California. He also notes that the law gives no percentage or safe harbour for when an employer has “primarily relied” on the system.
https://www.aalrr.com/Labor-Employment-Law-Blog/california-to-require-human-corroboration-of-ai-driven-discipline-and-termination
Where this is heading
These five pieces come from different industries, and they point the same way: when a score feeds a decision about a person, someone has to be able to overrule it, and show that they could.
I track each new law on automated decisions for one thing: what the human reviewer actually has to do. You’ll find it in Who Decides: Machine or Human, updated monthly: https://spatialnext.io/who-decides-us-laws-on-automated-decisions/
If your organisation, or one of your customers, is facing one of these deadlines, I’d like to hear what it looks like from the inside. Email me at mattsheehan@spatialnext.io.