Mark Cuban predicts AI will let workers train for jobs using simulators 'like pilots and race car drivers' 72%

By Theron Mohamed72%

7/24/2026, 12:48:46 PM

BS Summary: This article contains 20 faulty reasoning types, including Anecdotal, Overconfidence Bias, and Optimism Bias, with Availability Heuristic as the most egregious example at 23.1% saturation with 114 hits. Analysis detected 698 faulty-reasoning hits from 494 analyzed words, generating a BS Score of 64.4% and a BS Rank of 72% (6,179 of 21,887 articles). This article is worse (more manipulative) than 71.80% of the article peer group.

Mark Cuban predicts AI will let workers train for jobs using simulators 'like pilots and race car drivers' 
Mark Cuban is a tech billionaire. 
Julia Beverly/WireImage 
Mark Cuban says traditional employee training will be replaced by AI job simulators. 
The former "Shark Tank" star said workers will learn by navigating virtual workplace scenarios. 
Cuban said earlier this week that AI can't "read the room" or empathize like a human being. 
Hustling for work experience and learning from coworkers has been key to building a successful career for decades. 
Mark Cuban says that's bound to change. 
The tech billionaire and former "Shark Tank" investor said in an X post on Thursday that he expects the "next great AI application" to be a "job simulator." 
"How employees gain experience in a future AI world is going to be far different from today," he wrote. 
"Employees won't have as many touch points in the company to gain knowledge and experience from. 
That's where judgement has historically come from ." 
Cuban predicted that "much like race car drivers and pilots," future generations of workers will be trained using simulations, intended to teach them how to navigate real-life scenarios in the workplace. 
Commercial pilots spend long hours in simulators during their training, while simulators have become increasingly commonplace in recent years for race car drivers to train without being at a race track. 
Cuban said that "smart companies will have their employees and stakeholders with the most domain knowledge create the simulator that takes them through every possible situation they could face and helps prepare them." 
" Onboarding will have a completely different meaning," he added. 
The next great AI application, driven by open source, or open weights, will be a job simulator. 
How employees gain experience in a future AI world is going to be far different from today. 
Employees won’t have as many touch points in the company to gain knowledge and… 
 Mark Cuban (@mcuban) July 24, 2026 
It's easy to imagine a newly qualified lawyer sitting through simulations of depositions, court hearings, and settlement negotiations so they know what to expect. 
Or a trainee doctor preparing for real-life situations by speaking with AI patients, assisting in a virtual surgery, and participating in simulated emergencies. 
If, as Cuban suggests, those scenarios are created by harnessing the knowledge and experience of their real-life colleagues at those law firms and hospitals, a job simulator could provide practical, realistic training. 
Cuban has posted repeatedly this week that AI will change the world, but falls short in areas such as "reading the room" and having emotional intelligence. 
He's said that it will work best in collaboration with humans. 
"Add AI productivity to the real time capacity and judgement of humans, and you will get the greatest return on both investments ," he posted on Thursday. 
Read the original article on Business Insider 
Article reasoning-pattern comparisonThis article: 0.0%Theron Mohamed: 2.5%Business Insider: 2.5%Confirmation Bias0.0%This article: 3.8%Theron Mohamed: 0.6%Business Insider: 0.7%Anchoring Bias3.8%This article: 23.1%Theron Mohamed: 6.7%Business Insider: 3.4%Availability Heuristic23.1%This article: 6.3%Theron Mohamed: 1.9%Business Insider: 0.7%Representativeness Heuristic6.3%This article: 0.0%Theron Mohamed: 0.0%Business Insider: 0.9%Hindsight Bias0.0%This article: 12.1%Theron Mohamed: 10.3%Business Insider: 1.9%Overconfidence Bias12.1%This article: 7.5%Theron Mohamed: 4.4%Business Insider: 5.0%Framing Effect7.5%This article: 0.0%Theron Mohamed: 0.0%Business Insider: 0.8%Loss Aversion0.0%This article: 2.6%Theron Mohamed: 1.0%Business Insider: 0.8%Status Quo Bias2.6%This article: 0.0%Theron Mohamed: 0.0%Business Insider: 0.3%Sunk Cost Effect0.0%This article: 11.3%Theron Mohamed: 12.8%Business Insider: 3.1%Optimism Bias11.3%This article: 0.0%Theron Mohamed: 2.0%Business Insider: 1.6%Pessimism Bias0.0%This article: 8.7%Theron Mohamed: 1.3%Business Insider: 4.6%Negativity Bias8.7%This article: 0.0%Theron Mohamed: 0.5%Business Insider: 2.0%Self-Serving Bias0.0%This article: 0.0%Theron Mohamed: 0.0%Business Insider: 0.6%Fundamental Attribution Error0.0%This article: 0.0%Theron Mohamed: 0.0%Business Insider: 0.2%Actor-Observer Bias0.0%This article: 0.0%Theron Mohamed: 0.0%Business Insider: 0.8%In-Group Bias0.0%This article: 0.0%Theron Mohamed: 0.0%Business Insider: 0.2%Out-Group Homogeneity Bias0.0%This article: 5.3%Theron Mohamed: 1.2%Business Insider: 3.0%Halo Effect5.3%This article: 0.0%Theron Mohamed: 0.0%Business Insider: 0.1%Horn Effect0.0%This article: 0.0%Theron Mohamed: 0.0%Business Insider: 0.0%Dunning-Kruger Effect0.0%This article: 3.4%Theron Mohamed: 0.5%Business Insider: 1.3%Recency Bias3.4%This article: 3.6%Theron Mohamed: 0.6%Business Insider: 0.4%Primacy Effect3.6%This article: 0.0%Theron Mohamed: 0.0%Business Insider: 0.1%Blind-Spot Bias0.0%This article: 0.0%Theron Mohamed: 0.0%Business Insider: 0.3%Ad Hominem0.0%This article: 0.0%Theron Mohamed: 0.0%Business Insider: 0.1%Straw Man0.0%This article: 5.5%Theron Mohamed: 2.2%Business Insider: 3.3%Appeal to Authority5.5%This article: 2.6%Theron Mohamed: 4.3%Business Insider: 1.2%False Dilemma2.6%This article: 6.3%Theron Mohamed: 1.5%Business Insider: 0.6%Slippery Slope6.3%This article: 0.0%Theron Mohamed: 0.0%Business Insider: 0.1%Circular Reasoning0.0%This article: 6.3%Theron Mohamed: 16.1%Business Insider: 4.0%Hasty Generalization6.3%This article: 0.0%Theron Mohamed: 0.0%Business Insider: 0.1%Red Herring0.0%This article: 0.0%Theron Mohamed: 0.0%Business Insider: 0.7%Bandwagon0.0%This article: 0.0%Theron Mohamed: 0.0%Business Insider: 3.1%Appeal to Emotion0.0%This article: 1.6%Theron Mohamed: 0.2%Business Insider: 0.7%Begging the Question1.6%This article: 6.5%Theron Mohamed: 2.2%Business Insider: 2.3%Post Hoc (False Cause)6.5%This article: 0.0%Theron Mohamed: 0.0%Business Insider: 0.1%Tu Quoque0.0%This article: 5.5%Theron Mohamed: 0.8%Business Insider: 0.2%Burden of Proof5.5%This article: 0.0%Theron Mohamed: 0.0%Business Insider: 0.1%Appeal to Nature0.0%This article: 0.0%Theron Mohamed: 0.0%Business Insider: 0.2%Composition/Division0.0%This article: 13.2%Theron Mohamed: 2.5%Business Insider: 3.6%Anecdotal13.2%This article: 0.0%Theron Mohamed: 0.5%Business Insider: 0.1%No True Scotsman0.0%This article: 6.1%Theron Mohamed: 1.2%Business Insider: 1.4%Ambiguity (Equivocation)6.1%This article: 0.0%Theron Mohamed: 0.0%Business Insider: 0.0%Gambler’s Fallacy0.0%This article: 0.0%Theron Mohamed: 0.0%Business Insider: 0.1%Middle Ground0.0%This article: 0.0%Theron Mohamed: 0.0%Business Insider: 0.0%Personal Incredulity0.0%This article: 0.0%Theron Mohamed: 0.0%Business Insider: 0.1%Special Pleading0.0%This article: 0.0%Theron Mohamed: 0.0%Business Insider: 0.0%Genetic Fallacy0.0%This article: 0.0%Theron Mohamed: 0.0%Business Insider: 1.2%Unattributed Quote0.0%This article: 0.0%Theron Mohamed: 1.5%Business Insider: 0.7%Quote-first Misdirection0.0%This article: 0.0%Theron Mohamed: 0.0%Business Insider: 3.3%Biased Writer Voice0.0%This article: 0.0%Theron Mohamed: 1.1%Business Insider: 1.3%Indoctrination0.0%This article: 0.0%Theron Mohamed: 0.0%Business Insider: 0.1%Politically Left Leaning Bias0.0%This article: 0.0%Theron Mohamed: 0.0%Business Insider: 0.1%Politically Right Leaning Bias0.0%This article: 0.0%Theron Mohamed: 1.1%Business Insider: 1.5%Attempt to Sell a Product or S…0.0%

494 words analyzed.

Speakers

1speaker47%attributed speech260writer words
Voice mapSelect a segment to jump to its words
Writer's voice • 18 words • 0.0% coverageWriter's voice • 18 words • 0.0% coverageWriter's voice • 6 words • 0.0% coverageWriter's voice • 2 words • 0.0% coverageMark Cuban • 13 words • 0.0% coverageMark Cuban • 14 words • 0.0% coverageMark Cuban • 17 words • 0.0% coverageWriter's voice • 18 words • 0.0% coverageMark Cuban • 7 words • 0.0% coverageMark Cuban • 28 words • 0.0% coverageMark Cuban • 19 words • 0.0% coverageMark Cuban • 16 words • 0.0% coverageMark Cuban • 8 words • 0.0% coverageMark Cuban • 31 words • 0.0% coverageWriter's voice • 31 words • 0.0% coverageMark Cuban • 33 words • 0.0% coverageMark Cuban • 10 words • 0.0% coverageWriter's voice • 17 words • 0.0% coverageWriter's voice • 17 words • 0.0% coverageWriter's voice • 14 words • 0.0% coverageWriter's voice • 7 words • 0.0% coverageWriter's voice • 24 words • 0.0% coverageWriter's voice • 23 words • 0.0% coverageWriter's voice • 32 words • 0.0% coverageWriter's voice • 26 words • 0.0% coverageMark Cuban • 11 words • 0.0% coverageMark Cuban • 27 words • 0.0% coverageWriter's voice • 7 words • 0.0% coverage
Selected voice

Mark Cuban

77%flagged-word coverage
234 attributed words100% of attributed speech92% writer coverage

No manipulation-pattern hits were found in this speaker's attributed words or the writer's voice.

Attribution is sentence-level. Pattern percentages are calculated only from words assigned to that voice.

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Analysis

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