Futurism89%

OpenAI Strikes Bold Deal With Kalshi to Mix Together the Most Hated Technologies in Existence: AI and Prediction Markets 41%

By Frank Landymore73%

7/15/2026, 7:33:08 PM

BS Summary: This article contains 23 faulty reasoning types, including Unattributed Quote, Biased Writer Voice, and Anecdotal, with Negativity Bias as the most egregious example at 36.1% saturation with 214 hits. Analysis detected 1,600 faulty-reasoning hits from 593 analyzed words, generating a BS Score of 45.4% and a BS Rank of 41% (9,832 of 16,550 articles). This article is better (less manipulative) than 59.40% of the article peer group.

Is it not enough to simply watch the beautiful game, unadorned? 
These days you might use an AI chatbot to keep abreast of what’s happening in the World Cup. 
And that AI chatbot, in a sign of the times, might try to shove prediction market odds in your face as another way of ostensibly keeping you up to speed. 
Because are you really getting the full picture if you don’t know where a bunch of gamblers fall on the outcome? 
This is exactly what OpenAI is doing. 
The Sam Altman-led company quietly struck a deal with Kalshi, which lets you bet on outcomes far beyond sports, to show its prediction market data in ChatGPT, the New York Times reported . 
It’s perhaps the inevitable melding of two of the most divisive innovations to come out of the tech industry in recent years. 
Searching France and Spain on ChatGPT ahead of their quarterfinal clash on Tuesday returned a graphic that showed that Les Bleus had a 60 percent chance of winning, according to the reporting. 
( We hope no one acted on that information .) 
Asking about the England and Argentina game on Wednesday showed that the Three Lions had a 54 percent chance of coming out on top. 
Neither side promoted the deal, and the graphic is tellingly light on branding. 
There are no logos and no outbound links. 
The only sign of the collab is a small notice in the bottom left corner stating, “Source: Kalshi.” 
This is the first partnership of its kind for OpenAI. 
The company recently updated its help page to stress that users “cannot place bets through ChatGPT,” with the Kalshi data being limited to “queries related to the 2026 World Cup,” according to the NYT . 
Zooming out, it’s another sign of prediction markets laundering their image by glomming themselves onto other, more credible brands. 
In January, Kalshi partnered with CNN to provide its real-time prediction data on the news network’s broadcasts. 
Its rival Polymarket entered into a similar partnership with Dow Jones , the publisher of The Wall Street Journal, that same month. 
Both have also partnered with Google to show their data in search results. 
Unlike traditional betting platforms, prediction markets don’t frame what they provide as gambling: they provide markets, not bets. 
They allow you to wager on all kinds of real-life events, ranging from the geopolitical outcomes to the completely trivial. 
Polymarket lets you bet on the destruction caused by wildfires and the use of nuclear weapons , for example, while also giving you the chance to make a buck on whether Cristiano Ronaldo will cry at the World Cup . 
(He did.) 
Their fuzzy legal framework, plus their Wild West approach to gambling, has led to numerous controversies. 
Suspiciously timed bets on massive events like the US’s capture of ousted Venezuelan president Nicolás Maduro have raised concerns of rampant insider trading and put pressure on lawmakers to crackdown on the platforms. 
Arrests have been made in some cases , but these have been rare. 
Put simply, for OpenAI, it may be somewhat risky to associate itself with all this baggage, which might be why the Kalshi collaboration is very limited  at least for now. 
More on: Grim New Prediction Market Lets Gamblers Bet on Raging Wildfires 
The post OpenAI Strikes Bold Deal With Kalshi to Mix Together the Most Hated Technologies in Existence: AI and Prediction Markets appeared first on Futurism . 
Confirmation Bias
1.2%
Anchoring Bias
0%
Availability Heuristic
9.4%
Representativeness Heuristic
0%
Hindsight Bias
0.3%
Overconfidence Bias
5.9%
Framing Effect
17.9%
Loss Aversion
0%
Status Quo Bias
0%
Sunk Cost Effect
0%
Optimism Bias
0%
Pessimism Bias
10.8%
Negativity Bias
36.1%
Self-Serving Bias
0%
Fundamental Attribution Error
3.2%
Actor-Observer Bias
0%
In-Group Bias
0%
Out-Group Homogeneity Bias
0%
Halo Effect
0%
Horn Effect
0%
Dunning-Kruger Effect
0%
Recency Bias
7.3%
Primacy Effect
0%
Blind-Spot Bias
0%
Ad Hominem
0%
Straw Man
0%
Appeal to Authority
21.6%
False Dilemma
9.1%
Slippery Slope
3.2%
Circular Reasoning
0%
Hasty Generalization
6.7%
Red Herring
0%
Bandwagon
0%
Appeal to Emotion
13.7%
Begging the Question
3.5%
Post Hoc (False Cause)
16.7%
Tu Quoque
0%
Burden of Proof
5.2%
Appeal to Nature
3%
Composition/Division
0%
Anecdotal
21.8%
No True Scotsman
0%
Ambiguity (Equivocation)
5.6%
Gambler’s Fallacy
0%
Middle Ground
0%
Personal Incredulity
0%
Special Pleading
0%
Genetic Fallacy
0%
Unattributed Quote
30.5%
Quote-first Misdirection
0%
Biased Writer Voice
30.4%
Indoctrination
0%
Politically Left Leaning Bias
0%
Politically Right Leaning Bias
0%
Attempt to Sell a Product or Service
6.7%

593 words analyzed.

Analysis

Hover over highlighted words in the article to view the associated bias or fallacy analysis.