The USDA says 700,000 were removed from SNAP. Here's what counts as fraud.

[Yo_Mama_Been_Loggin]

Last week, the U.S. Department of Agriculture (USDA) and officials in Ohio announced a joint takedown of fraudulent Supplemental Nutrition Assistance Program (SNAP) retailers across the state, issuing formal violation notices to 19 businesses.

Multiple studies have found that SNAP fraud is rare, yet the Trump administration continues to place heavy focus on the issue.

The ongoing issue of states refusing the USDA's request for data about food aid recipients was also reignited last week, when Republican Sen. Rick Scott introduced the SNAP Fraud Reporting Act on June 10. The bill, if passed, would mandate that states submit comprehensive fraud data.

"By passing this legislation, we will create a pathway to identify and crack down on fraud so taxpayers don't get ripped off," Sen. Scott said.

https://www.yahoo.com/news/article/the-usda-says-700000-were-removed-from-snap-heres-what-counts-as-fraud-122350825.html

Rick Scott knows all about fraud.

[pat_k]

1. What they are calling fraud" is error data -- with the errors generally having nothing to do with qualifications.

[AltairIV]

2. fraud indeed

Rick Scott spoke, check your wallet.

[2naSalit]

3. rick scott sure...

Does know fraud, it's his claim to fame and riches.

[HappyH]

4. Rick is one of the best Medicare fraudsters.

[pat_k]

5. P.S. AI systems being used are also subject to "hallucinations"

Minor, inadvertent errors on the part of a case worker or applicant are all being classified as "fraud," instead of what they are, errors.

Also, when they report "fraud rates" they include errors that resulted in underpayments. I suppose that could be considered discovering a fraud the system perpetrated on the recipient, but no one notes the fact that those cases are included in the reported rates.

And worse, AI being deployed to detect this so-called "fraud" are subject to "hallucinations."

A bit from Gemini (view with the skepticism you apply to all AI)

When AI systems are used to detect welfare or benefit errors, the term "hallucination" refers to algorithmic fabrications—where the system invents non-existent evidence, misinterprets data, or confuses honest administrative and paperwork mistakes with deliberate fraud.

These inaccuracies have severe real-world consequences for individuals and governments:

Misapplied Penalties: Algorithms often fail to distinguish between clerical errors and active deceit, punishing vulnerable groups for simple mistakes.

High False-Positive Rates: In many automated welfare systems, improper payments or "fraud" determinations have alarmingly high error rates.

For example, in previous automated systems, independent reviews determined that up to 93% of fraud determinations were incorrect.

Systemic Examples: Automated anti-fraud systems have caused massive financial and personal hardship, most notably in Australia’s unlawful "Robodebt" scheme and in widespread false accusations across the US, UK, and Europe.

Legal and Reputational Blowback: Using flawed AI systems can lead to legal action and required multi-billion dollar payouts from governments and major consulting firms. For instance, a court ordered the Dutch government to repay thousands of dollars to families falsely accused of child welfare fraud.

Experts continually stress that because these systems lack true contextual understanding, they require strict human-in-the-loop oversight to verify flags and prevent automated discrimination.

[orthoclad]

6. I have to respectfully wonder

how many megaWatthours and how much water it took to create that analysis, which has unknown accuracy and still requires human research to verify it. This would include the electricity and cooling needed to train the AI, but as an external cost, it's hard to trace.

[pat_k]

7. 0.24 watt-hours per median query--might seem small at first (about the same as running your microwave for one second)...

https://www.energysage.com/news/google-ai-energy-use-electric-bill-impact/

Google just pulled back the curtain on one of tech's best-kept secrets: exactly how much energy its Gemini AI uses with every prompt. The answer—0.24 watt-hours (Wh) per median query—might seem small at first (about the same as running your microwave for one second). But multiply that by billions of daily interactions, and it suddenly becomes clear just how much energy AI is really using every day.

Perhaps my attitude sucks, but until there is a global boycott that includes Gemini, I don't feel compelled to refrain from the dozen or so queries a week that yield a result from Gemini.

I have refrained from using AI for any other purpose and caution other members of my Woman-owned business group on the downside of jumping on the AI bandwagon in more intensive applications. FWIW, I've also promoted QuitGPT within the group.