A post arguing that “superintelligence” is the wrong word for current artificial intelligence systems climbed to the top of Reddit’s r/technology community this week, drawing tens of thousands of votes and a long comment thread about who gets to name a technology. The post’s core claim is narrow and largely linguistic: that labels for AI should be set by technical precision and ordinary public use, not by a head of state’s preference, and that applying “superintelligence” to today’s chatbots misdescribes what the software does.
The discussion sits on top of remarks that President Donald Trump has made repeatedly since 2025, in which he has said he dislikes the word “artificial” in “artificial intelligence” and has floated alternatives, including calling it “genius.” Those comments, delivered at technology-industry events and in public appearances, were widely reported at the time and were generally treated as an aside rather than a formal policy instruction. NarwhalTV has found no evidence of any executive order, agency directive or federal rulemaking that requires the government or the public to replace “artificial intelligence” with another term, and the viral post itself does not cite one.
What the viral argument actually says
Stripped of its political framing, the r/technology post makes three claims that are worth separating:
- That “superintelligence” has an established meaning in AI research and should not be used loosely as a marketing or political label.
- That current systems, including large language models, do not meet that definition.
- That vocabulary shifts through usage, publication and standards work, not by decree.
The first two points are defensible on the record. The third is how language has generally behaved, though political speech does influence usage over time, which is why the question is being argued at all.
The terms, and what they mean
The phrase “artificial intelligence” dates to a 1955 funding proposal for the following summer’s Dartmouth College workshop, written by John McCarthy with Marvin Minsky, Nathaniel Rochester and Claude Shannon. McCarthy later said he chose it in part to distinguish the new field from cybernetics. It has survived seventy years of boom-and-bust cycles.
Narrow AI
Systems built for specific tasks: image classification, speech recognition, recommendation ranking, protein structure prediction, text generation. Essentially all deployed commercial AI, including the chatbots and coding assistants in mass use, falls here, however broad their apparent range.
Artificial general intelligence
A hypothetical system matching human competence across most cognitive tasks, including learning new domains without retraining. There is no agreed benchmark for AGI, which is one reason labs can disagree publicly about how close it is. OpenAI’s own charter and corporate documents have used the term for years without a settled technical test.
Superintelligence
The term was popularized in philosopher Nick Bostrom’s 2014 book of that title, which defined it as an intellect that greatly outperforms the best human minds in virtually every field, including scientific creativity and social skill. By that standard, no existing model qualifies. Current systems fail at tasks requiring reliable long-horizon planning, produce confident errors, and depend on human-curated data and evaluation.
The word has nonetheless become commercial branding. Ilya Sutskever, a co-founder of OpenAI, launched Safe Superintelligence Inc. in 2024. Meta reorganized its AI teams under a “Superintelligence Labs” banner in 2025 after an aggressive hiring campaign. Those choices arguably did more to loosen the term than any political remark, a point several commenters in the Reddit thread made.
Why the wording matters beyond semantics
Definitions carry legal weight. The European Union’s AI Act, which entered into force in 2024 with obligations phasing in through 2026 and 2027, assigns duties based on categories such as “general-purpose AI model” and “systemic risk,” with thresholds tied partly to training compute. The US National Institute of Standards and Technology’s AI Risk Management Framework, published in 2023, leans on measurable system characteristics rather than grand labels. Insurance underwriting, procurement contracts and securities disclosures all turn on how a product is described.
That is the practical case against inflationary language: a company that tells investors it is building “superintelligence” while shipping a narrow model invites exactly the kind of disclosure scrutiny that has followed other high-profile claims. Our coverage of disclosure questions around a SpaceX bonds claim and of a data-theft claim naming 3,615 Trump Mobile customers illustrates how quickly loose public statements become documentation problems.
Who actually changes a word
Lexicographers describe usage rather than prescribe it. Merriam-Webster and the Oxford English Dictionary add and revise entries based on evidence of sustained use across sources; Merriam-Webster’s 2023 word of the year was “authentic,” chosen in part because of AI-driven anxiety about what is real. Standards bodies, including ISO/IEC and NIST, publish controlled vocabularies that regulators then cite. Peer-reviewed literature anchors technical meaning.
Political language does shift usage, but usually by repetition and media amplification rather than instruction, and often with the original term intact. “Artificial intelligence” is embedded in statutes, academic department names, stock tickers and seven decades of citations. Replacing it by announcement would be unusually difficult.
A note on viral framing
The Reddit post is commentary, not reporting, and its headline implies a presidential order that has not been documented. Readers tracking AI debates online will recognize the pattern from other fast-spreading claims, including a statue story attributed to the European Parliament that required verification before it could be repeated. Skepticism applies to criticism as well as to hype.
What to watch
Three things will determine whether “superintelligence” keeps a technical meaning: whether major labs continue using it as branding, whether regulators write it into binding text, and whether dictionaries record a broadened sense. Separately, debates over how AI is marketed to individuals continue to draw criticism from outside the industry, including actor Joseph Gordon-Levitt’s argument that AI products are designed to capture emotional attention.
For now, the accurate description of the most capable public systems remains unglamorous: large neural networks trained on vast text and multimodal data, strong at pattern completion, unreliable at verification, and dependent on human oversight. That is a significant technology. It is not superintelligence, under the definition the word was coined to carry.
