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Dozens of Polymarket Bets Show Signs of Insider Trading, The Times Finds

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Dozens of Polymarket Bets Show Signs of Insider Trading, The Times Finds

On the evening of Thursday, June 12, a small group of internet gamblers made a highly specific prediction on Polymarket, the betting website that offers odds on virtually everything.

Thirteen users wagered a total of $140,000 that Israel would strike Iran by the end of that week, even as the odds suggested that an attack was unlikely. Seven of the accounts had been opened just days earlier. Another had a history of bets related to military action against Iran — and had won money on all of them.

Israel attacked Iran later that day, netting the accounts more than $600,000 in profits.

The explosive growth of prediction markets like Polymarket has rattled the political world over the last year, fueling concerns about a new kind of insider trading by military leaders and government officials with access to confidential plans. A military reservist was recently indicted in Israel for a scheme to bet on the June strike, while a U.S. Army Special Forces soldier was accused last month of wagering on the capture of Nicolás Maduro, the president of Venezuela.

Those bets represent only a slice of the suspicious activity on Polymarket. A New York Times examination found that more than 80 Polymarket users have placed bets with suspicious characteristics, including 38 whose well-timed wagers have drawn little or no public attention. They won money across nearly 30 topics dating back to at least 2024, from Israel’s strike on Iran last year to the regulatory debate over cryptocurrency trading.

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The Times’s examination also revealed previously unreported red flags in some of the high-profile bets that have drawn scrutiny. The findings were based on a series of warning signs that hint at insider trading without proving it definitively. Those signals include long-shot bets that pay off, well-timed wagers by recently opened accounts and bets by users who gamble on only a few related topics without ever losing, among other considerations.

The Times identified more than 11,000 Polymarket accounts that exhibited some combination of those characteristics, then manually reviewed the most striking cases, comparing the users’ trading histories against overall prediction market activity. Many of the examples involved military operations, which have attracted a surge of betting this year.

While the accounts The Times examined make up a small portion of Polymarket’s users, they show how suspicious wagers can unfold on the site and highlight the vulnerability of prediction markets to manipulation. Polymarket’s trading data is publicly visible, which makes it possible to reconstruct betting patterns with second-by-second accuracy.

One of the highest-profile cases occurred at the start of the year, when the idea that Mr. Maduro would soon be ousted as Venezuela’s leader seemed unlikely. The odds on Polymarket reflected that doubt, sitting at around 7 percent. Then something unexpected happened: The United States swept into Venezuela on Jan. 3 and arrested Mr. Maduro.

Somehow, one user appeared to know the arrest was coming. The account had placed large bets on Jan. 1 and Jan. 2 predicting that Mr. Maduro would be “out” as Venezuela’s leader before the end of the month. When Mr. Maduro was captured on Jan. 3, the user pocketed more than $400,000. Prosecutors later charged Master Sgt. Gannon Ken Van Dyke, the special forces soldier, with using classified information to make that bet.

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A similar betting pattern played out when Polymarket offered odds on whether the United States would announce a cease-fire in the war with Iran by April 7.

At least seven users placed bets in the hours before President Trump announced the agreement in a Truth Social post on April 7. Collectively, they won more than $1.4 million, including two users who each walked away with over $400,000 in profits.

The Times also found warning signs in areas unrelated to America’s foreign policy. In 2024, a user created a Polymarket account and placed a single long-shot bet that a financial product tied to the cryptocurrency Ether would be approved by the Trump administration. A month later, the user withdrew $50,000 in profits after regulators blessed the product.

Based on the public data alone, it is impossible to conclude whether these users were insiders who had access to nonpublic information. Many sophisticated bettors use automated bots to place well-timed wagers that may appear suspicious at first glance, while some prediction market traders pride themselves on making giant bets against the odds that occasionally pay off.

But The Times’s examination adds to evidence suggesting that Polymarket has been exploited by users with information that is not publicly available.

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Last month, the nonprofit Anti-Corruption Data Collective released a report about Polymarket that found heavy bettors on underdog outcomes — an event with at most a 35 percent likelihood — won more than half the time on topics related to the military, calling it a sign of “potential insider trading.” Similar wagers on other topics were profitable only 14 percent of the time, the report found.

Polymarket has pledged to combat insider trading, saying it has “no place” on the platform. A company spokeswoman said the firm “continuously monitors its markets for suspicious activity and regularly engages with relevant authorities when appropriate.”

Polymarket and its main rival, Kalshi, are the most popular prediction markets. But they differ in important ways. Polymarket’s main platform processes wagers in crypto, creating a public record of transactions. Much less data is available about the bets on Kalshi, which announced in February that it had opened more than 200 insider-trading investigations resulting in over a dozen “active cases.”

Robert DeNault, Kalshi’s head of enforcement, said in a statement to The Times that insider trading was banned on the platform. “We surveil, investigate and punish it,” he said.

For years, prediction markets occupied a legal gray area in the United States. A tiny financial agency, the Commodity Futures Trading Commission, barred Polymarket from serving U.S.-based customers in 2022, while Kalshi battled those regulators in court for authorization to offer bets on congressional elections.

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Now the landscape is shifting in these firms’ favor.

Kalshi won its case in October 2024, paving the way for election betting in the United States. Within a year, Polymarket secured regulatory approval to start offering some services, though the majority of its betting markets, including wagers on military action, are still available only overseas. Sergeant Van Dyke gained access to the website using a virtual private network, a tool that disguises a user’s location, according to court papers.

Together Kalshi and Polymarket draw $25 billion in monthly trading volume, up from less than $2 billion a year ago, an explosion of popularity that poses a challenge to regulators.

Under federal law and agency regulations, insider trading on prediction markets is prohibited, though what qualifies as an offense is a complex legal question. Some advocates for the sites argue that certain insiders can help generate more accurate forecasts, making prediction markets a useful source of information.

In a CBS “60 Minutes” interview last fall, Shayne Coplan, Polymarket’s chief executive, called insider trading “an inevitability” that comes with “a lot of benefits,” while stipulating that trading platforms need to draw an ethical line somewhere.

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“What’s cool about Polymarket is that it creates this financial incentive for people to go and divulge the information to the market,” he said at an Axios conference in November. “Or someone tells someone, and then the market responds.”

But potential insider activity does not always create a clearer picture for the public, The Times found. Someone with insider knowledge can employ a range of strategies to accumulate large, profitable positions without moving the needle on the odds.

In January 2025, a Polymarket user who regularly wagered on Washington politics began betting that President Joseph R. Biden Jr. would pardon his brother James Biden. The user placed 53 separate bets worth more than $20,000, even as the odds declined.

Less than 40 minutes after the user’s final bet on Jan. 20, the White House announced that Mr. Biden had signed a last-minute pardon for his brother. The user earned $200,000, cashed out and has not bet since.

The Times’s review also found possible coordination among Polymarket accounts that placed bets at identical times. Such activity can signal that an individual user deployed automated bots to avoid detection, obscuring a large position across many accounts.

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A possible example emerged on Feb. 27, when Mr. Trump at 3:38 p.m. gave the order to strike Iran while he was aboard Air Force One. Over the next few hours, at least 27 accounts placed thousands of dollars of simultaneous bets predicting that the United States would attack by Feb. 28. When the strike began around 1 p.m. on Feb. 28, the accounts collected profits of more than $700,000.

Much of the suspicious activity has been concentrated on the conflicts in the Middle East. Of the 27 betting topics that The Times flagged, 12 focused on the U.S.-Israeli war with Iran.

In February, Israeli authorities charged the military reservist with using nonpublic information to help an accomplice make more than $100,000 betting on Polymarket about the timing of Israel’s attacks on Iran and Yemen.

“It’s happening now,” the soldier texted his accomplice, just as military planes took off for the June attack, according to the indictment.

In court this month, the reservist’s lawyer argued that his client’s unit in the Israeli Air Force had a penchant for gambling, a risk-taking impulse that was common in the military.

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An Israeli military representative said the defense forces had taken steps to “strengthen oversight and control systems” since the Polymarket bet was exposed.

The rise of suspicious trading has caused alarm in Washington.

The Senate passed a resolution last month barring senators and their staff members from using prediction markets. In April, Mr. Trump said he was “never much in favor” of the sites and lamented that “the whole world unfortunately has become somewhat of a casino.”

Within days, he reversed himself, noting that people working in the prediction business are “pretty happy with it.” Mr. Trump’s eldest son, Donald Trump Jr., is an adviser to Kalshi and Polymarket, and the family’s social media company, Trump Media, has announced plans to offer a prediction market.

The scrutiny on prediction markets has put a spotlight on the Commodity Futures Trading Commission. Historically, the agency has overseen markets for oil, agricultural goods and certain financial instruments known as swaps. Because prediction market bets are classified as swaps, the agency has argued, the sites fall under its purview as well. But the C.F.T.C. has a relatively small staff and a spotty record of enforcement that has drawn skepticism from critics.

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Michael Selig, the agency’s chairman, is an outspoken prediction market enthusiast who has hopscotched the country giving speeches about the technology’s potential to rival traditional media as an information source.

“It’s really important that we protect these markets here in the U.S.,” he said at a crypto conference in March.

In a statement to The Times, Mr. Selig said the agency had a “renewed focus on efficiency” and was using artificial intelligence to bolster its capabilities. “There are no gaps in our ability to fulfill our mission,” he added.

As concerns have intensified, Polymarket has promised to monitor for misconduct. But its public pronouncements are sometimes contradictory.

Three weeks before the Special Forces soldier was indicted, Mr. Coplan, Polymarket’s chief, was interviewed at Harvard Business School, where he was asked about suspicious activity in the Maduro betting market.

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“For the Maduro one, it’s actually a very funny story — it’s not what it seems,” Mr. Coplan said. “It’s just more of a fluke than it is some sort of exciting thing.”

Once the federal charges were announced, Mr. Coplan told a different story, writing on social media that Polymarket had “flagged this, referred it, and cooperated throughout the process” with the Justice Department.

In April, Kalshi said it had unearthed three examples of insider trading — all congressional candidates who had placed bets on their own races.

In one case, Kalshi said, a Democratic candidate for U.S. Senate in Virginia placed a bet that he would join the race, a decision he clearly controlled. Kalshi fined him more than $6,000 and gave him a five-year ban from the platform.

Because prediction market data is public, the hunt for insider trading has also become a social media phenomenon.

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On X, users post screenshots of prediction markets with strange patterns or bets from new accounts. Some traders have built strategies around identifying insiders and then copying suspicious wagers before other bettors catch on.

One market that was flagged on social media centered on a prominent internet sleuth, who announced in February that he was preparing a detailed investigation into an unnamed crypto company whose employees had “abused internal data.”

Speculators on Polymarket started betting on who the sleuth’s target might be. Between Feb. 24 and Feb. 26, an anonymous user who had just joined Polymarket bet more than $65,000 that it was Axiom, a crypto trading firm. (Axiom did not respond to a request for comment.)

The wager was correct. On Feb. 26, the sleuth accused Axiom employees of insider trading.

It’s unclear who made the bet. The sleuth said that he had been “retained” to investigate Axiom, and that he had reached out to the firm before posting his findings.

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The anonymous bettor walked away with $411,647 in profits.

Johnatan Reiss contributed reporting.

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Musicians shortchanged by AI deals with labels, lawsuit alleges

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Musicians shortchanged by AI deals with labels, lawsuit alleges

Musicians have been left out of settlements between major record labels and AI companies, a new lawsuit alleges.

The American Federation of Musicians of the United States and Canada (AFM), which has 70,000 members, said Universal Music Group and Warner Music Group “received significant compensation” from the AI companies for past copyright violations and licensed “substantial” portions of their music catalogs to them, but haven’t shared that with the musicians.

UMG and WMG sued AI companies Udio and Suno in 2024, accusing them of copyright infringement. Both companies settled with Udio last year. In November, WMG announced a partnership with Suno, but Universal Music Group’s lawsuit against Suno is pending.

“While the Defendants protected their own interests and created a significant source of new revenue with the retrospective settlements and prospective licenses, they have refused to compensate the musicians whose work — created with their own instruments and through their talent, creativity, and hard work — is fed into AI machines for profit,” AFM said in its lawsuit, filed in U.S. District Court in New York on Friday.

AFM said it believes the AI settlements fall under the “new use” provision of its collective bargaining agreements, which requires music companies to notify the union of new licenses for purposes not covered by the contract and to compensate musicians, whose work was used to train AI models.

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UMG and WMG said in statements that they are in negotiations on a collective bargaining agreement with AFM.

“Warner Music Group is growing the value of music by establishing guardrails and architecting a healthy AI ecosystem on behalf of artists everywhere,” the company said in a statement.

Universal Music Group said it will continue to work to resolve issues during the negotiations.

“Universal Music Group has been at the forefront of protecting the rights and advancing the interests of artists and songwriters in the age of AI — striking responsible AI licensing agreements to ensure they are compensated, leading the charge for legislation to further protect them and taking legal action against bad actors,” the company said in a statement.
“We expect to continue our strong working relationship with the AFM built on mutual respect for the talented musicians in our industry.”

AI has become more popular among consumers, dramatically changing the landscape in the entertainment industry. Many startups have popped up allowing users to type text prompts into AI systems to generate original songs, video clips and stories.

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Some creatives say the AI tools help them brainstorm or illustrate bold ideas on a budget. But critics have raised concerns about whether AI systems are trained on copyrighted works without permission or payment to artists. Others are worried AI could eliminate their livelihoods.

Udio said it would create a new platform that would train on licensed and authorized music with artists having the ability to opt-in. Suno agreed to change its platform, launching new licensed models, and place download restrictions.

Bradford Auerbach, a partner at law firm OGC, said he expects to see more of these types of lawsuits filed by unions.

“You’ve got the unions always protecting the status quo, so you’ve got this invariable conflict of new technology coming in, and moving the cheese for a lot of people that were accustomed to having their business set up the way it was,” Auerbach said.

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Trump signs an executive order to vet top AI models for national security risks

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Trump signs an executive order to vet top AI models for national security risks

President Trump signed an executive order Tuesday directing the federal government to establish a voluntary early review process for the country’s most advanced artificial intelligence models, following a months-long internal battle over how aggressively Washington should move to regulate the fast-growing technology.

Under the order, companies are asked to allow government agencies, including the National Security Agency and representatives of the Defense Department, to evaluate cutting-edge models up to 30 days before they are released to the public. The order stops short of mandating participation and explicitly bars the creation of any new licensing or permitting for AI models.

“The main question is whether this is the start of a continued government clamp down and response to continued AI capabilities, or whether this is a one-off, limited, and truly voluntary act,” said James Sanders, research associate at the Center for a New American Security, a Washington, D.C., think tank.

“It’s unclear how voluntary this will stay and how voluntary it will be in practice as the AI labs try to maintain good relationships with the U.S. government,” he said.

The order represents a reversal for Trump, less than two weeks after he scuttled a version of the policy that gave the government a 90-day review period — and, more broadly, for an administration that came to power promising to strip away AI guardrails, a posture that slowly created fractures within the GOP.

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In the executive order, Trump appeared to frame a need to foster AI technologies while taking into account national security. “As these capabilities evolve, my Administration will continue to work closely with industry to ensure that the best and most secure technology is deployed rapidly to confront any and all threats to our country,” he said in the order.

The step set off immediate debate about whether Trump’s plan would be an effective approach. It formalizes an existing practice in which top AI companies share models with external evaluators and government players before deploying them publicly, but raises questions about how voluntary it will be and how the government will choose which labs to target.

David Sacks, who previously served as Trump’s AI advisor, called the 30-day window a “game changer,” arguing that the shorter timeline would allow companies to engage with the government without slowing down new model releases.

“In the AI race, every day counts,” Sacks wrote in a post on X.

Mark Carroll, director of Engineering at Amazon Web Services Annapurna Labs, places his hand on a compute sled of the new Trainium3 system at Annapurna Labs in Austin, Texas, on February 3. Tech titan Amazon is working to step out of Nvidia’s shadow with custom “Trainium” chips designed specially for machine learning as billions of dollars are poured into artificial intelligence.

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(Mark Felix / AFP via Getty Images)

Dean W. Ball, Trump’s former AI advisor, characterized the order as a victory for the AI “safety contingent” and a loss for Sacks and others who promote a more accelerated approach. He called the order a mistake, saying it could be a first step toward a federal licensing requirement for AI models.

“All for a benefit that is barely articulable; what, exactly, is the intelligence community going to do in 30 days to make the models safer?” Ball wrote on X.

The signing of the executive order occurred amid growing tensions among Republicans over AI, job loss and data center construction, including fear among a significant portion of Trump’s supporters that artificial intelligence could eliminate jobs or become a security threat. Polling in May had shown strong support among Republicans for a framework like the one outlined in Trump’s executive order.

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The growing split among Republicans over AI was clearly visible in Florida on Monday, where James Uthmeier, the state’s Republican attorney general, sued OpenAI over the alleged risks of ChatGPT, citing the use of the bot by a gunman in a shooting at Florida State University last year.

Meanwhile, Rep. Byron Donalds — the Trump-endorsed candidate to succeed Gov. Ron DeSantis — said Monday that he did not agree with Trump on AI policy, indicating he supported state-led regulation, a shift for a candidate who had been backed by the AI industry earlier in the year.

A poll released by Americans for Responsible Innovation, a nonprofit advocating for a federal framework for AI policy, found that the majority of Republican voters polled supported the type of plan laid out in Trump’s executive order. Seventy-one percent also said independent security testing should be required by law for advanced AI systems.

When Trump took office, his administration pivoted away from Biden-era policies requiring AI companies to test their AI models and share safety results with the government before public release, reversing the U.S. posture on regulation.

That changed after Anthropic — acting on its own initiative — brought its Claude Mythos Preview model to senior White House officials, a move that exposed vulnerabilities in its software and raised concerns about the potential need for safety-testing of AI models before broad public release.

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The White House attempted to downplay the executive order as a regulatory move, emphasizing in a post Tuesday that the federal government would not conduct sweeping oversight and the process outlined in the executive order would be voluntary.

“We are NOT conducting oversight of all new models, as that level of government overreach would have chilling effects on free speech and innovation,” the White House Office of Science and Technology Policy posted on X.

Trump’s signing of the order prompted calls from those who support stricter AI regulation for Congress to take steps beyond Trump’s plan. Thus far, Congress has not passed any major legislation to regulate artificial intelligence.

“Congress should take the structure this order creates, make participation mandatory, and extend it beyond cyber threats to the full range of risks the most capable models present,” Riki Parikh, policy director of the Alliance for Secure AI, a nonprofit that promotes safeguards for AI, said on X, saying the order’s voluntary framework “isn’t enough.”

Progressives, including Gov. Gavin Newsom and Vermont Sen. Bernie Sanders, said the executive order was too weak and slammed Trump for flip-flopping on regulation.

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Some experts suggested the distinction between voluntary and mandatory sharing of their cutting-edge technology may be crucial.

“No company is formally required to participate, but if a developer wants to sell frontier AI systems to the federal government, participation may soon become the price of entry,” Jessica Tillipman, a professor who studies contracting law at George Washington University, wrote in a post on X.

The administration’s approach was welcomed by industry leaders, including Microsoft President Brad Smith, who said the order was “an important step toward advancing innovation while protecting the security of the American public.”

Anthropic endorsed the order and called it “an important step in strengthening America’s leadership in AI.” The company said it was looking forward to supporting the implementation of the program.

Ceballos and McDaniel reported from Washington, Christopher from Los Angeles. Times staff writer Michael Wilner contributed to this report.

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Ex-girlfriend of former Google CEO Eric Schmidt ordered to pay him $10 million after rape accusations

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Ex-girlfriend of former Google CEO Eric Schmidt ordered to pay him  million after rape accusations

An arbitrator has sided with former Google Chief Executive Eric Schmidt, saying in a preliminary ruling that he was not guilty of sexual assault against his former girlfriend and business partner Michelle Ritter.

The arbitrator, retired Washington State Judge Beth Andrus, recently ordered Ritter to pay $10.7 million in damages to Schmidt.

Ritter sued Schmidt in Los Angeles County Superior Court last September, accusing the billionaire tech mogul of “forcibly” raping her on a yacht off the coast of Mexico in 2021. She also alleged Schmidt forced her to have nonconsensual sex at the Burning Man festival in 2023.

“I clearly told him ‘no’ and tried to get him to stop, but I had learned that attempting to resist physically would be futile and make things worse,” Ritter said in a legal filing.

Schmidt has denied the accusations under oath. The arbitrator said that Ritter did “everything she could possibly do” to avoid discussing the rape accusations under oath.

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Ritter had a romantic relationship with the 71-year-old Schmidt after they met in 2020 while she was pursuing graduate degrees in law and business at Columbia University. He invested about $100 million in a joint venture with her that later fell apart.

The pair’s dispute stretches back to 2024 after their personal relationship unraveled and as they were negotiating a settlement of their Steel Perlot venture, a business accelerator that invested in artificial intelligence, crypto and other startups.

Ritter also accused Schmidt of stealing the joint venture from her, which he denied.

“One can also conclude that Ritter engaged in self-centered efforts to obtain revenge against Schmidt in a way that was more damaging than helpful to her cause,” Andrus wrote in her decision, which was recently made public. “I find that Ritter’s statement that she was raped by Schmidt to be false.”

Ritter, 32, alleged that a 2022 federal law inspired by the #MeToo movement intended to end forced arbitration of sexual assault and harassment claims allowed her to have her case heard in open court.

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Superior Court Judge Michael Small disagreed, ruling that the law did not apply because a financial settlement and arbitration agreement Ritter and Schmidt signed in December 2024 was entered into after the alleged sexual wrongdoing — not before as legally required.

The judge sent the case to arbitration in March. Ritter filed a federal lawsuit in California in April challenging the arbitration. That litigation is pending.

Schmidt served as Google chief executive from 2001 to 2011 and later as the chairman of the Silicon Valley company and its parent, Alphabet Inc., until 2017.

Schmidt is worth about $52 billion, largely through his stock holding in Google’s parent company, Alphabet, according to Bloomberg.

Last year, Schmidt took a controlling interest in Relativity Space, a Long Beach rocket startup founded in 2015.

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