Antonio Villaraigosa, Katie Porter, Tom Steyer, Steve Hilton, Chad Bianco and Xavier Becerra participate in a California gubernatorial debate hosted by CNN at East Los Angeles College in Monterey Park, Calif. Tuesday, May 5, 2026. (AP Photo/Ethan Swope)
Davina Hurt is director of government ethics at the Markkula Center for Applied Ethics, Santa Clara University. Views are her own.
A hundred dollars on the game, a twenty-five-dollar office pool, a friendly wager on the Kentucky Derby. Recreational betting has always carried costs we’ve chosen to ignore. But the stakes are no longer low—and the consequences are far more serious than we anticipated.
Rebranded as “prediction markets”—platforms where people trade on the likelihood of future events—this form of betting has moved beyond sports into elections, climate disasters, and geopolitical conflicts. The euphemism matters. Call it “forecasting,” and betting on human outcomes sounds analytical instead of exploitative. But the math hasn’t changed. The house still wins—and in politics, the “house” increasingly includes those with the capital, access, and information to shape outcomes before they’re decided.
The risks aren’t just personal. When individuals lose money betting on elections or economic collapse, the consequences can be devastating. But individual loss is only the surface. The deeper danger emerges when people begin to profit from outcomes they can influence. Because once profit depends on an outcome, incentives shift. Preventing harm may mean losing money. Allowing harm may mean profit. Even without explicit wrongdoing, the structure itself rewards those positioned closest to power—and those best able to anticipate or influence events.
Advocates argue that prediction markets simply aggregate information—that they are more accurate than polls because they reflect what people are willing to bet, not just what they say. But in politics, perception is not neutral. It feeds back into reality. Polls attempt to measure opinion at a moment in time. Markets, by contrast, can influence behavior—shaping donor decisions, media coverage, and even how voters interpret viability.
A Poll Measures. A Market Moves.
That dynamic is no longer theoretical. In March 2026, Governor Gavin Newsom signed an executive order barring state appointees from participating in prediction markets—a response to documented cases of apparent insider trading tied to U.S. military operations. Among the incidents cited: a trader earned roughly $410,000 betting on the capture of Venezuelan President Nicolás Maduro hours before it happened; six accounts reportedly netted $1.2 million on bets placed just before a U.S. strike on Iran; a separate trader posted a 93 percent win rate on Middle East-related contracts, accumulating nearly $1 million since 2024. The greater danger isn’t the losing bet. It’s the winning one.
Prediction markets also operate without the safeguards that govern traditional gambling—transparency rules, consumer protections, and accountability mechanisms built over decades. The current focus on conflicts of interest is important, but it misses the larger issue.
The real concern is not just who profits. It’s how these markets begin to shape democratic decision-making itself.
The Becerra Anomaly
When Eric Swalwell exited California’s gubernatorial race, the expected response was simple: donors reassess, voters reconsider, and the field reshuffles. Instead, a widely discussed prediction market quickly framed the race as a contest between Katie Porter and Tom Steyer. In doing so, it didn’t simply reflect the electorate’s judgment—it risked substituting for it.
The market never asked whether Xavier Becerra—a battle-tested Attorney General with a record of challenging the Trump administration—deserved to be in the conversation. It simply priced him as unlikely. And once a candidate is framed that way in a system watched by donors and media, the consequences can follow, particularly in a media and donor environment sensitive to perceived momentum: less coverage, fewer resources, declining visibility.
For most voters, a market probability doesn’t register as a niche financial signal shaped by a self-selected group of bettors. It reads as “the odds”—a distilled, authoritative judgment. That perception carries a different weight than a poll with a margin of error or a debate with competing viewpoints.
In that sense, prediction markets don’t just predict elections. They can begin to structure them.
Nobody looks at Kentucky Derby odds and concludes certain horses shouldn’t run. But in political markets, candidates without existing financial or media advantages can be quietly sidelined—not because voters rejected them, but because they were never fully considered.
This is what we might call the viability trap: candidates don’t lose because voters decide against them—they struggle to gain traction because markets signal they are unlikely to win before voters fully engage. That perception can become self-reinforcing, shaping coverage, fundraising, and ultimately the range of choices voters believe are realistic.
Importantly, markets don’t have to be right to have influence. In fact, the risk is often greatest when they are wrong. If a candidate like Xavier Becerra regains momentum after being dismissed by market odds, it doesn’t disprove the problem—it highlights it. It shows how a viable candidate can be forced to expend time and resources overcoming a perception of inevitability that voters never created. The distortion isn’t in the final outcome. It’s in the path voters are given to get there.
That dynamic is already playing out. On April 5, Becerra was polling at 4 percent. Within days of Swalwell’s exit, he jumped to 13 percent among Democrats. By April 20, he led the entire field. Voters didn’t discover a new candidate. They finally got to weigh in on one they’d never been asked to consider. The market didn’t predict that. It obscured it.
When Markets Shape the Field
This dynamic extends beyond any single race. It reflects what happens when financial logic is applied to democratic legitimacy—and why regulatory fixes alone may not be sufficient. The problem is structural.
Democracy has absorbed two body blows already. Peter Thiel spent $25 million turning former employees into senators. Elon Musk spent $277 million on a candidate while using a platform he owns to amplify him to 200 million followers—a structure no campaign finance law was built to address. Each represented a new frontier: first, capital buying candidates; then, capital buying the infrastructure of political discourse itself. Prediction markets are the third blow—and the most insidious, because unlike a donor or a platform, a market has no visible author. It doesn’t look like influence. It looks like math.
What makes this moment distinct is not that influence exists—it always has—but how quietly it operates. Donors respond to perceived viability. Media narratives follow momentum. Voters internalize what feels like a settled race. Each step appears independent, but together they can narrow the field before voters meaningfully engage.
The most troubling part isn’t that this is happening—it’s that it’s happening in plain sight. Donors understand that markets influence perception. Political operatives know that odds shape coverage. Voters sense something is off. But like many forms of systemic distortion when responsibility is diffuse, action stalls.
Meanwhile, the market continues to assign probabilities that can influence the trajectory of a race before a single vote is cast—effectively pricing candidates in or out of viability.
There are early signs of response. But isolated ethical boundaries are not the same as systemic guardrails—and the underlying incentives remain unchanged. Prediction markets don’t need to be intentionally manipulated to distort democracy. Their structure does that on its own. When financial incentives align with particular political outcomes, the pressure to influence those outcomes—subtly or directly—becomes embedded in the system.
Organizations can absorb disruption and rebuild. Democracy is less forgiving. The question is no longer whether markets reflect elections. It’s whether we are willing to accept a system where they help shape who is taken seriously before voters ever weigh in.
A Decision Point
Democratic legitimacy is not a price signal. It cannot be captured or optimized by financial instruments without fundamentally changing what it represents.
Once markets begin to shape perceptions of viability, power shifts—not after elections, but before they begin. At that point, outcomes are no longer simply being predicted. They are being conditioned.
The question is not whether any single candidate can overcome those dynamics. It is whether we accept a system where perceptions of viability are increasingly mediated by markets rather than voters.
Because once viability can be priced, it can be influenced—and what begins as a prediction ends as a constraint. At that point, the question is no longer who voters choose. It’s whether the field they’re choosing from was ever really theirs to determine.