Computers have always been better than humans at some tasks, which is why they were adopted from the 1950s for databases and calculation.
Mostly true True in substance, wrong in a detail.
Factual: Statements about the present or the past, checked against the record: did they hold up?
The second judge would not resolve this claim; the verdict shown is the first judge's.
What would count as true or false
Judged as of 2026-10-07. The core claim is that computers have always outperformed humans at some tasks, and that this was the reason they were adopted (the proposition adds early uses such as calculation and databases from the 1950s). True: historical sources show that computers from their earliest use outperformed humans at specific tasks (for example arithmetic speed and accuracy, or data processing), and that this advantage drove their adoption. Mostly true: this holds, with a minor slip in a detail such as the exact decade or the example applications. Mixed: computers outperformed humans at some tasks, but sources show adoption was driven largely by other factors. Mostly false: the advantage existed only in narrow cases and is overgeneralized. False: early computers did not outperform humans at any task.
Set before the research began.
Evidence (4)
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E1 The ENIAC Story Ordnance Ballistic Research Laboratories, Aberdeen Proving Ground (text by Martin H. Weik) · 1961
“For example, a skilled person with a desk calculator could compute a 60- second trajectory in about 20 hours. The analog differential analyzer produced the same result in 15 minutes. ENIAC required 30 seconds--just half the time of the projectile's flight.”
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E2 Programming men and machines. Changing organisation in the artillery computations at Aberdeen Proving Ground (1916-1946) HAL open archive (Maarten Bullynck, Paris 8) · 2015
“The ENIAC could do 5000 additions per second and it could consult about 1000 values from its function table per second, but reading a punched card took half a second and crippled its speed.”
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E3 The ENIAC Story Ordnance Ballistic Research Laboratories, Aberdeen Proving Ground (text by Martin H. Weik) · 1961
“It is recalled that no electronic computers were being applied to commercial problems until about 1951.”
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E4 When Computers Were Human - NASA NASA Jet Propulsion Laboratory · 2 November 2016
“Human capabilities were much more powerful for many tasks, including the rapid calculations needed for trajectory analysis and verification”
Reasoning
The Ballistic Research Laboratories history (E1) reports that ENIAC computed a 60-second trajectory in 30 seconds, against about 20 hours for a skilled person with a desk calculator. E2 adds that ENIAC could do 5,000 additions per second. So early computers clearly beat humans at arithmetic-heavy work such as trajectory calculation [E1][E2]. E4 shows humans still did better at many tasks in early spaceflight, but this does not contradict a claim about "some" tasks. E3 says commercial use of electronic computers began around 1951, consistent with the 1950s timing; the evidence on why computers were adopted is indirect, which supports mostly true rather than true.
Cite this claim
Steven Pinker, “Computers have always been better than humans at some tasks, which is why they were adopted from the 1950s for databases and calculation.” (said 7 October 2026). Verdict: mostly true. Reliability API, claim c_b7f2a74088c8, method 0.1.0+28da144b, dataset release v1.1.2. https://epistacklabs.com/claims/c_b7f2a74088c8
This claim is in dataset release v1.1.2, with the same verdict.
Reply to this claim
More factual claims by Steven Pinker
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“A major fact about language, known for decades, is that people don’t blurt out what they mean”
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Resolved true
“then it is very much unlike AlphaGo, with this closed universe governed by fixed rules.”
AlphaGo operated in a closed universe governed by fixed rules, unlike the open-loop real world.
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“The capabilities of LLMs trained on gargantuan datasets are more general than I (and almost everyone else) would have guessed at the time.”
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“There are some features in large language models that actually implicitly build in some of the insight of linguistics.”
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Mostly false
“What these models don’t have is a model of the world.”
Large language models like GPT do not have a model of the world.
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