Prediction markets such as Polymarket and Kalshi have soared in popularity over the past few months. From bets on disease outbreaks to wagers about artificial intelligence, many of their markets relate to science and research. So how do Polymarket’s prediction powers compare to the opinions of subject-matter experts?
In prediction markets, users bet on a future event by buying and selling shares in favour of various outcomes. The price of each share is determined neither by expert opinions nor by the ‘house’ setting odds. Rather, prices are based on demand, reflecting the market’s collective belief in the probability of the outcome.
But as well as providing a gambling platform, prediction markets offer a test of the concept of the wisdom of crowds — the long-held idea that collective predictions by large groups of people tend to be better than forecasts by subject specialists. According to Polymarket’s website, prediction markets can often determine outcomes more accurately than experts or polls because “economic incentives ensure market prices adjust to reflect true odds as more knowledgeable participants join.”
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Research has found that prediction markets sometimes outperform other forecasting methods in political elections, but some researchers remain unconvinced that they can rival the work of expert scientists.
Prediction markets are “potentially helpful forecasting supplements” when it comes to science, says Richard Borghesi, who researches finance and prediction markets at the University of South Florida in Tampa. The markets can be useful to gauge how scientific information is received by the public, he says, but they are not “substitutes for models, peer review or expert judgement,” and are less informative when the people trading lack specialist knowledge on the subject.
There are also growing concerns about market manipulation and insider trading on Polymarket and Kalshi. In October last year, Norwegian officials who oversee the Nobel Peace Prize investigated a surge in bets for Venezuelan opposition leader Maria Corina Machado hours before she was awarded the prize.
Possible pandemics
One science-based area in which researchers question the effectiveness of prediction markets’ forecasting is disease outbreaks. When an outbreak of hantavirus was reported on a cruise ship in early May, a Polymarket market predicted a 19% probability of the World Health Organization (WHO) declaring a hantavirus pandemic this year. But that sank after the shock of the initial news; when this article was published, the market sat at a probability of 5%, with about US$14 million in shares traded so far. A similar Kalshi market predicts a 7% chance of the WHO declaring a hantavirus outbreak a public-health emergency of international concern in 2026.
Users in these markets do follow some scientific evidence, with comment sections referencing WHO updates and case numbers. In comparison, researchers usually forecast disease spread using mathematical models and a variety of data, including hospital surveillance, genomic data and even school absences.
It is difficult for experts to pin down the precise probability of a pandemic, but the chance of a global hantavirus outbreak “is very, very low,” says Vaithi Arumugaswami, an infectious-disease researcher at the University of California, Los Angeles. Forecasting from the US Centers for Disease Control and Prevention suggests that the virus’s risk to the US public is extremely low, and the WHO says that transmission between humans is uncommon.
The way users trade may be an effect of anxiety surrounding pandemics, which seems especially present since the COVID-19 pandemic, says Bill Hanage, an epidemiologist at Harvard University in Cambridge, Massachusetts. "In that regard, Polymarket bets do "tell you something about how the public feels."
Climate forecasting
Another science-based subject creating buzz in prediction markets is climate change — and there, some bets seem “reasonably in line with experts’ estimates”, says Zeke Hausfather, a climate scientist at the research organization Berkeley Earth in California.
One Polymarket market predicts a 34% chance of 2026 being the hottest year on record, and a 60% chance of it being the second. Kalshi similarly gives this year a 32% chance of being the hottest yet. Hausfather’s own real-time projections — based on data from the European Space Agency’s Earth-observation programme Copernicus — give a 28% chance of 2026 being the hottest year so far, and a 67% chance of being the second hottest. Last week, a report from the World Meteorological Organization warned that a record-breaking hot year is almost certain by 2030.
Quantum predictions
Polymarket users are also placing bets on whether a quantum computer will soon be able to ‘break’ the cryptocurrency Bitcoin by deriving the private key associated with an existing Bitcoin address. The market gives a 3% chance of this being achieved by the end of 2026, and a 16% chance by the end of 2027.
Breakthroughs this year have pushed forward the timeline of quantum computers cracking such keys, but it will still take time for researchers to assemble a system at the scale necessary to threaten cryptography, says Scott Aaronson, a theoretical computer scientist at the University of Texas at Austin. The timeframes posed by Polymarket are probably too optimistic, he says, but some specialists think the feat could be possible in the next few years.
One unknown is how long it will take to overcome some of the biggest obstacles that keep quantum computing from real-world use, says Chloe Martindale, who researches post-quantum cryptography at the University of Bristol, UK. Such a breakthrough could happen this year, or “it could be in 30 years”, she says.
Borghesi warns that prediction markets shouldn’t be taken as “definitive evidence that a scientific risk is either serious or not serious, when the market may only be reflecting short-term sentiment or the way a contract happens to be written”, he says. These markets’ “value would be highest when they are treated as one signal among many, not as a replacement for scientific expertise.”
This article is reproduced with permission and was first published on June 1, 2026.
