Anthropic's top economist says AI won't replace workers yet. Mark Cuban says it trails humans in 2 key ways. 35%

By Theron Mohamed46%

7/23/2026, 12:26:42 PM

BS Summary: This article contains 17 faulty reasoning types, including Optimism Bias, Availability Heuristic, and Framing Effect, with Hasty Generalization as the most egregious example at 25.8% saturation with 149 hits. Analysis detected 640 faulty-reasoning hits from 577 analyzed words, generating a BS Score of 43% and a BS Rank of 35% (13,306 of 20,473 articles). This article is better (less manipulative) than 65.00% of the article peer group.

Mark Cuban is a tech billionaire and former "Shark Tank" investor. 
Andrew Harnik/Getty Images 
Anthropic's head of economics says AI isn't taking jobs yet because it's working best with humans. 
Peter McCrory said that current models benefit from skillful users and augment people's efforts. 
In response, Mark Cuban said that AI might never match a human's ability to "read the room." 
Anthropic's top economist says AI isn't replacing workers yet because it works better with humans than without them. 
Mark Cuban says that may never change. 
Peter McCrory wrote in an X essay on Wednesday that by all accounts, "AI has caused no material increase in the unemployment rate to date," even among workers most at risk of having their jobs automated by the nascent technology. 
The head of economics at Anthropic  the AI company behind Claude Fable 5, one of the top large language models  said that AI so far appears to be "both skill-biased and labor augmenting," meaning expert users get more out of it, and it helps people do their jobs better. 
AI simply isn't up to the job in some areas. 
McCrory said the "tasks that Claude can't handle may depend on interpersonal coordination, in-person interactions, or engagement with the physical world that, so far, only humans can do." 
He cautioned that human expertise could decline in importance as AI models improve, but AI shouldn't materially increase unemployment for at least the next year, he said. 
Cuban , a tech billionaire and former "Shark Tank" investor, highlighted two areas where humans trump AI in an X post responding to commentary on McCrory's essay by Box CEO Aaron Levie. 
"Models don't know the consequences of their actions," he wrote. 
"People know what will get them fired. 
Models suffer from information latency. 
People understand what they see right in front of them." 
Cuban said those are two skills that "AI won't have for a long, long, long time . 
If ever." 
He added that they're "invaluable to every business decision," noting how often it's helpful to "read the room." 
Models don’t know the consequences of their actions. 
People know what will get them fired. 
Models suffer from information latency. 
People understand what they see right in front of them. 
2 skills AI won’t have for a long long long time. 
If ever. 
2 skills that are… https://t.co/dbzGpER01Z 
 Mark Cuban (@mcuban) July 23, 2026 
"Add AI productivity to the real-time capacity and judgment of humans, and you will get the greatest return on both investments," Cuban wrote. 
He added that managers need to figure out how to squeeze the most value out of that combination , as doing so can be a "business propellant and competitive advantage." 
Cuban  who sold his internet-radio startup to Yahoo for nearly $6 billion during the dot-com bubble  recently warned the mad rush to build AI infrastructure could result in excess capacity as power efficiency increases. 
He joked that obsolete data centers could wind up being converted into "pickleball courts." 
Even so, Cuban has repeatedly emphasized that businesses must embrace AI or they'll fail. 
"There's going to be two types of companies in this world: those who are great at AI, and everybody else that they put out of business," he said at a university event in February last year. 
Read the original article on Business Insider 
Confirmation Bias
0%
Anchoring Bias
0%
Availability Heuristic
9.4%
Representativeness Heuristic
0%
Hindsight Bias
0%
Overconfidence Bias
8.5%
Framing Effect
9.4%
Loss Aversion
0%
Status Quo Bias
0%
Sunk Cost Effect
0%
Optimism Bias
14.6%
Pessimism Bias
1.2%
Negativity Bias
0%
Self-Serving Bias
2.9%
Fundamental Attribution Error
0%
Actor-Observer Bias
0%
In-Group Bias
0%
Out-Group Homogeneity Bias
0%
Halo Effect
1.9%
Horn Effect
0%
Dunning-Kruger Effect
0%
Recency Bias
0%
Primacy Effect
0%
Blind-Spot Bias
0%
Ad Hominem
0%
Straw Man
0%
Appeal to Authority
1.6%
False Dilemma
6.6%
Slippery Slope
2.9%
Circular Reasoning
0%
Hasty Generalization
25.8%
Red Herring
0%
Bandwagon
0%
Appeal to Emotion
0%
Begging the Question
0%
Post Hoc (False Cause)
6.9%
Tu Quoque
0%
Burden of Proof
0%
Appeal to Nature
0%
Composition/Division
0%
Anecdotal
2.4%
No True Scotsman
2.9%
Ambiguity (Equivocation)
1.4%
Gambler’s Fallacy
0%
Middle Ground
0%
Personal Incredulity
0%
Special Pleading
0%
Genetic Fallacy
0%
Unattributed Quote
0%
Quote-first Misdirection
0%
Biased Writer Voice
0%
Indoctrination
6.2%
Politically Left Leaning Bias
0%
Politically Right Leaning Bias
0%
Attempt to Sell a Product or Service
6.2%

577 words analyzed.

Analysis

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