Polymarket Bets Erroneously Classified as News by Google Algorithms
Google briefly displayed Polymarket betting markets in Google News results before calling it an error and removing them, but the algorithm’s mistake was entirely logical, and the incident raises pointed questions about how prediction markets are classified as information sources versus gambling products.
For a brief period this week, users searching Google News for coverage of geopolitical events found something unexpected sitting between Reuters and The Guardian. A search for news about the Strait of Hormuz returned, just below credible news outlets, a Polymarket bet on the exact number of ships allowed to pass through it.
Google called it an error and removed the results. But the fact that the mistake happened at all is worth understanding, because it was not a random glitch. It was the algorithm doing exactly what it is designed to do, and drawing the wrong conclusion for entirely logical reasons.
What Google’s Algorithm Was Thinking
Google News does not curate its results through editorial judgment in the traditional sense. It uses a set of automated criteria to identify sources likely to produce relevant news content: publication freshness, topical relevance to trending events, publication frequency, and structural markers resembling those of news articles.
Google’s own explanation is that its news product “is designed to show sources that create content about current issues, events, and important topics,” with policies governing which sites are eligible to appear.
Polymarket meets almost every one of those criteria, and it does so in a way that would have been essentially impossible to anticipate when those criteria were designed. The platform publishes new markets continuously. Those markets are almost always tied to real-world events that are actively in the news. The pages are updated constantly as odds shift with incoming information. The titles read like headlines.
A market asking “Will ChatGPT Be the Number One Free App in the US Apple Store by April 10?” is, structurally, indistinguishable from a news article tracking the same question, at least from the perspective of a content indexing system trying to identify topically relevant, frequently updated, event-driven material.
Google’s algorithm identifies news sites in part by how frequently new information is added and how much of it pertains to topics it knows are trending in current events.
Prediction market pages for world events meet both of those criteria precisely. And because the mainstream visibility of prediction markets is so recent, it is not surprising that Google’s filtering systems had not been updated to specifically exclude them. The platform was not trying to game Google News. It simply looks, to an algorithm, a great deal like one.
Why Google Was Right to Remove Them Anyway
The algorithmic confusion is understandable. Google’s decision to remove Polymarket from News results is also correct, and the reasoning behind it matters beyond the immediate incident.
There is a fundamental difference between reporting news and betting on it. Google News is supposed to surface journalism, stories researched, reported, and fact-checked by editorial teams. Prediction markets reflect where money is flowing, which can be influenced by insider knowledge, coordinated positioning, or pure speculation. Those are not the same thing, and presenting them as equivalent in the same interface actively misleads users about the nature of what they are reading.
The Polymarket CEO has argued that his platform represents “the most accurate thing we have as mankind right now” for predicting future events. That claim is genuinely debated and not without some empirical support in certain contexts.
But prediction accuracy is not the standard for news. Journalism is not primarily in the business of forecasting. It is in the business of reporting what has happened, with verifiable sourcing, editorial accountability, and the ability to be corrected when wrong. A betting market that aggregates financial positions has none of those properties. It has different, sometimes useful properties, but they are not the same.
It is also worth noting that Google already has a data partnership with both Polymarket and Kalshi for its Finance product. That is arguably the right place for prediction market data. Finance surfaces probability estimates alongside stock prices, economic indicators, and market data, a context in which the nature of the information is clear, and users can evaluate it accordingly. News is a different context entirely, and conflating the two does real harm to the informational ecosystem that journalism depends on.
The Broader Question This Raises
The incident is small. The question that surfaces is not. Prediction markets have spent the last two years arguing, with growing success, that they are financial instruments rather than gambling products, information infrastructure rather than entertainment, and legitimate participants in public epistemology rather than bettors in a casino dressed up in fintech clothing. That argument has found sympathetic ears in federal regulatory circles and among some media organizations that now routinely cite Polymarket odds in election coverage.
The Google News episode is a useful stress test of that argument. If prediction markets really are information infrastructure, it is hard to explain why their presence in a news aggregator is an error. If they are something categorically different from journalism, which is the right answer, then the industry needs to be more careful about how it positions itself and what analogies it invites.
The algorithm made a reasonable mistake. The correction was appropriate. But the fact that the mistake was reasonable, that a sophisticated content classification system looked at Polymarket and saw something that resembled news, should prompt some reflection about what exactly prediction markets are and what role they are actually playing in the information environment. The answer to that question has implications well beyond a Google settings change.
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