On March 31, 2026, a rather odd complaint arrived at the Bucks County, Pennsylvania District Attorney's Office.

It came from the local sheriff's office, and it concerned one of their own, Deputy Sheriff Ryan Gaffney. The allegation was unusual: Gaffney had used his iPhone to snap photos of nude prisoners he had encountered in his job—and he had then shared those photos with "several female civilian employees inside the Sheriff's Office."

The main claim involved a local man suffering a mental health crisis on the morning of January 30, 2026. Five fully uniformed deputies had arrived at the house and were in the upstairs bedroom. Their detainee was naked from the waist down and had just been persuaded to put on some pants.

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Kalshi is a high-tech prediction market that allows people to "forecast the future" (their term). It is about contracts and information, the company says, making its offerings more like a soybean futures contract than a round of blackjack or a pull on the one-armed bandit.

Still, prediction markets look a lot like betting if you squint, which is why states like New York have tried to regulate them under gambling laws. To head this off, Kalshi has sought federal protection under the Commodity Futures Trading Commission (CFTC). Yes, this means regulation for Kalshi, but it also means the CFTC will sue states like Kentucky, Minnesota, Illinois, and Rhode Island, trying to pre-empt their laws in favor of a single national standard that the CFTC controls.

While this battle plays out, government insiders continue to generate insider trading stories after using their work knowledge to place bets "forecast the future" and make huge sums of money. The classic example, of course, was Gannon Ken Van Dyke, a US soldier who participated in planning the capture of Venezuela's Nicolas Maduro and then made $410,000 from that knowledge on the prediction site Polymarket. Van Dyke was arrested in April.

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Ivy League college students are, by definition, intelligent. They don't need to use generative AI to cheat on exams; they could just learn the material. But they also tend to be competitive, ambitious, and overscheduled, so AI can look like an easy shortcut that makes more time in their lives for things that can't be done by a chatbot. When the pressure is on, which approach do they choose?

A new scandal at Brown University reveals that huge numbers of these students are likely to cheat.

Record scores

A recent survey of Princeton students found that 29.9 percent admitted to cheating with AI on at least one exam or assignment. But the situation at Brown gives us a better sense of what this kind of cheating looks like in one particular class—and just how much it may be substituting for actual learning. And we know all this because the blind economics professor at the center of it all, Roberto Serrano, is not letting it go.

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