Nieman Lab.
Predictions for
Journalism, 2025.
For decades, the news industry has operated on a familiar rhythm: Journalists chase scoops, publish headlines, and define the news cycle. But a new model for information sharing is emerging. Prediction markets — platforms where users buy and sell shares based on the probability of future events — are poised to disrupt the media landscape in 2025, transforming not only how news is shared but how it is valued and consumed.
You may have heard about prediction markets during the recent U.S. presidential election. The prediction market Polymarket got a lot of press by accurately predicting the electoral outcome hours before the media called it. Joe Rogan said that at Mar-a-Lago on election night, Elon Musk had a “magical app” that told him the election results in advance. That app was not magic — it was Polymarket.
Polymarket is one of many prediction markets whose usage has exploded in the past year. Others include Kalshi, PredictIt, Manifold Markets, and Metaculus. While Polymarket remains technically illegal for U.S. residents, Kalshi operates a prediction market legally in the U.S. per an October appeals court decision. Prediction markets are currently in legal limbo, but I’d bet against a ban, especially given the new administration.
Why are prediction markets relevant to the future of news? In this most recent presidential election, prediction markets tended to show Trump at a 60% chance of victory ahead of the election, whereas legacy models like those of Nate Silver showed Trump at a 50% chance of victory. It’s incredibly hard to know how any news event might unfold, but prediction markets are creating new structures to surface information in real time.
Prediction markets create incentives for people with information to share what they know. This is what happened with the French whale who bet huge sums on Polymarket that Trump would win, because he had access to proprietary polling that suggested that more people than reported would vote for Trump. Anyone who thinks they can have an edge on the outcome of a news event, or predict news events before they happen, can put their money where their belief is.
At their core, prediction markets are a form of decentralized information gathering. They theoretically reward accuracy over sensationalism, prioritizing actionable data instead of attention-grabbing headlines. They also bring to light news events that might have otherwise gone unnoticed by traditional newsrooms. Instead of journalists manufacturing narratives rife with editorial bias, market incentives surface compelling information.
This more decentralized information ecosystem poses a direct challenge to the pundit class — the columnists, talking heads, and forecasters who dominate traditional news cycles. When thousands of users collectively predict the outcome of an event, the aggregated result often surpasses the accuracy of any single expert.
The rise of prediction markets raises questions about ethics and regulation. Current platforms are primed for market manipulation, insider trading, and the potential for bad actors to game the system. Platforms will need to enforce rigorous safeguards to maintain credibility and prevent misinformation from being incentivized.
Journalists will also face ethical dilemmas as prediction markets are normalized. Should reporters participate in markets they cover? How do outlets navigate the blurred line between reporting on probabilities and influencing them?
Ultimately, the widespread adoption of prediction markets is really just a continuation of the broader shift toward decentralization and user-driven information sharing. Much like how social media empowered content creators to leverage the internet to become the media, prediction markets allow users to quantify and monetize the information they have access to.
If all of this sounds like a libertarian fever dream, I hear you. But as these markets rise, legacy media will continue to slide into irrelevance, and we might soon discover a whole new class of people who can break news and share information about our world.
Taylor Lorenz writes User Mag.
For decades, the news industry has operated on a familiar rhythm: Journalists chase scoops, publish headlines, and define the news cycle. But a new model for information sharing is emerging. Prediction markets — platforms where users buy and sell shares based on the probability of future events — are poised to disrupt the media landscape in 2025, transforming not only how news is shared but how it is valued and consumed.
You may have heard about prediction markets during the recent U.S. presidential election. The prediction market Polymarket got a lot of press by accurately predicting the electoral outcome hours before the media called it. Joe Rogan said that at Mar-a-Lago on election night, Elon Musk had a “magical app” that told him the election results in advance. That app was not magic — it was Polymarket.
Polymarket is one of many prediction markets whose usage has exploded in the past year. Others include Kalshi, PredictIt, Manifold Markets, and Metaculus. While Polymarket remains technically illegal for U.S. residents, Kalshi operates a prediction market legally in the U.S. per an October appeals court decision. Prediction markets are currently in legal limbo, but I’d bet against a ban, especially given the new administration.
Why are prediction markets relevant to the future of news? In this most recent presidential election, prediction markets tended to show Trump at a 60% chance of victory ahead of the election, whereas legacy models like those of Nate Silver showed Trump at a 50% chance of victory. It’s incredibly hard to know how any news event might unfold, but prediction markets are creating new structures to surface information in real time.
Prediction markets create incentives for people with information to share what they know. This is what happened with the French whale who bet huge sums on Polymarket that Trump would win, because he had access to proprietary polling that suggested that more people than reported would vote for Trump. Anyone who thinks they can have an edge on the outcome of a news event, or predict news events before they happen, can put their money where their belief is.
At their core, prediction markets are a form of decentralized information gathering. They theoretically reward accuracy over sensationalism, prioritizing actionable data instead of attention-grabbing headlines. They also bring to light news events that might have otherwise gone unnoticed by traditional newsrooms. Instead of journalists manufacturing narratives rife with editorial bias, market incentives surface compelling information.
This more decentralized information ecosystem poses a direct challenge to the pundit class — the columnists, talking heads, and forecasters who dominate traditional news cycles. When thousands of users collectively predict the outcome of an event, the aggregated result often surpasses the accuracy of any single expert.
The rise of prediction markets raises questions about ethics and regulation. Current platforms are primed for market manipulation, insider trading, and the potential for bad actors to game the system. Platforms will need to enforce rigorous safeguards to maintain credibility and prevent misinformation from being incentivized.
Journalists will also face ethical dilemmas as prediction markets are normalized. Should reporters participate in markets they cover? How do outlets navigate the blurred line between reporting on probabilities and influencing them?
Ultimately, the widespread adoption of prediction markets is really just a continuation of the broader shift toward decentralization and user-driven information sharing. Much like how social media empowered content creators to leverage the internet to become the media, prediction markets allow users to quantify and monetize the information they have access to.
If all of this sounds like a libertarian fever dream, I hear you. But as these markets rise, legacy media will continue to slide into irrelevance, and we might soon discover a whole new class of people who can break news and share information about our world.
Taylor Lorenz writes User Mag.
