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# AI Definition History: 1950 to Super Intelligence (SI)

> Trace the definition of AI from Turing's 1950 test and the 1956 Dartmouth proposal to the 2026 federal rename to Super Intelligence (SI), with dated sources.

Super Intelligence (SI) Series

# The Evolution of AI’s Definition,
1950 to Super Intelligence (SI)

Six redefinitions in 76 years — Turing’s test, the Dartmouth proposal that coined the name,
and the rational-agent reframing — and now Super Intelligence (SI), formerly called artificial
intelligence (AI), the name Executive Order 14434 gave this technology on September 29, 2026. Iternal
supports it: the definition has moved every time the field’s capability moved, and SI is the first
name that describes that capability rather than the 1955 method.

![John Byron Hanby IV](https://imagedelivery.net/4ic4Oh0fhOCfuAqojsx6lg/42486f3c-b615-4331-82bb-cf51b2e26500/public)

By [John Byron Hanby IV](https://grokipedia.com/page/john-byron-hanby-iv)

CEO & Founder, Iternal Technologies • Updated October 2026 • 14 min read

[Compare Every Official Definition](https://iternal.ai/super-intelligence/official-ai-definitions)

The technology did not change in September 2026. Only the federal government’s name for it did
— and that is not even a first. Alan Turing never used the words “artificial
intelligence.” What follows is the evolution of the AI definition since — the field has
renamed, redefined, and re-argued itself every decade — and Iternal supports the latest entry on
that list. The reason is in the pattern: naming in this field has never been settled once. It has
tracked capability every time it moved, and Super Intelligence (SI) is where that tracking lands now.

Quick Answer

Artificial intelligence has been formally defined and redefined at least half a dozen times since
Alan Turing’s 1950 paper. Iternal supports the latest one — Executive Order 14434’s
rename to Super Intelligence (SI), formerly called artificial intelligence (AI) — because it is
the first name to describe what the technology now demonstrably does rather than how it was first
built.

What follows is the history of the definition of AI, Turing to today: the operational
test that avoided defining “intelligence” at all, the two-month workshop proposal that
coined the term, the textbook rewrites that moved the goalposts twice, and the executive order that
gave the same underlying technology the name its measured results have earned.

76

Years since Turing’s 1950 paper posed the question AI would answer

6

Documented redefinitions of “AI,” Turing to the 2026 Super Intelligence order

1965

Year I.J. Good first described an “ultraintelligent machine” — the root of the separate ASI concept, not of SI

4

Editions of AI’s leading textbook, 1995–2020

Table of Contents

1. [1950: Turing’s Test](#turing)
1. [1956: Dartmouth and the Coined Term](#dartmouth)
1. [1960s–1980s: Symbolic AI and the Narrowing Definition](#winters)
1. [1965: I.J. Good’s Intelligence Explosion](#intelligence-explosion)
1. [1990s–2000s: The Rational-Agent Reframing](#rational-agent)
1. [2015–2017: The “Big Data to AI” Relabel](#relabel)
1. [2022–2025: Generative AI and the First “Superintelligence” Bets](#genai-asi)
1. [September 2026: Executive Order 14434](#executive-order)
1. [The AI Definition Timeline](#timeline)
1. [What the Pattern Tells You](#pattern)
1. [FAQ](#faq)

## 1950: Turing’s Test

The field that would later be called artificial intelligence does not begin with a definition. It
begins with a refusal to give one. Alan Turing opened “Computing Machinery and
Intelligence” in October 1950 by proposing to consider the question, “Can machines
think?” (Source: [Turing, "Computing Machinery and Intelligence," Mind, Oct. 1950](https://cs.mcgill.ca/~dprecup/courses/AI/Materials/turing1950.pdf)) He judged the words
“machine” and “think” too slippery to pin down directly and replaced the
question with an operational test instead: the **imitation game**, later called the
Turing Test. An interrogator, questioning a human and a machine by typed messages alone, has to tell
which is which. If the machine can pass for human often enough, Turing treated the philosophical
question as answered in practice, without ever settling what “thinking” means in theory.

The term “artificial intelligence” appears nowhere in Turing’s paper — it did
not exist yet. That is the detail easiest to miss and most useful to hold onto: the field’s
founding document offers a Turing test definition of machine thinking, not a definition of a field
called AI. The field, and the name, arrived five years later.

## 1956: Dartmouth and the Coined Term

John McCarthy, Marvin Minsky, Nathaniel Rochester, and Claude Shannon coined “artificial
intelligence” in an August 31, 1955 funding proposal for a summer workshop at Dartmouth
College (Source: [McCarthy, Minsky, Rochester & Shannon, Dartmouth proposal, Aug. 31, 1955, reprinted AI Magazine 27(4), 2006](https://ojs.aaai.org/index.php/aimagazine/article/view/1904)) — the earliest confirmed use of the phrase. Their working
definition was deliberately wide open: “every aspect of learning or any other feature of
intelligence can in principle be so precisely described that a machine can be made to simulate
it.” The proposal lists seven research aspects — automatic computers, programming machines
to use language, neuron nets, the theory of the size of a calculation, self-improvement, abstractions,
randomness and creativity —
without ever tightening that conjecture into a bounded technical scope. The field’s founding
document defined AI by an open-ended research bet, not a fence.

McCarthy explained his own motive for the new coinage decades later, in a review of a 1987 book on the
field’s history: “one of the reasons for inventing the term ‘artificial
intelligence’ was to escape association with ‘cybernetics.’ Its concentration on
analog feedback seemed misguided, and I wished to avoid having either to accept Norbert…
Wiener as a guru or having to argue with him.” (Source: [McCarthy, review of The Question of Artificial Intelligence (Bloomfield, ed., 1987)](https://www-formal.stanford.edu/jmc/reviews/bloomfield/bloomfield.html)) Iternal reads the record this way: the name described the method, not
the result. The proposal’s own conjecture is that intelligence can be described precisely enough
‘that a machine can be made to simulate it,’ and ‘artificial’ named that
simulation approach. It was also chosen to separate a new research program from an existing
one, not handed down as a settled scientific category, and not a measurement of what the research
would eventually be able to do.

Nearly seventy years on, Microsoft’s chief executive made a related complaint about the label.
Satya Nadella called “artificial intelligence” “one of the most unfortunate
names” for the technology, telling Bloomberg Television: “I wish we had called it
‘different intelligence.’ Because I have my intelligence. I don’t need any artificial
intelligence.” (Source: [The Decoder, 2024-05-25, citing Bloomberg Television, 2024-05-21](https://the-decoder.com/?p=14599)) Nadella’s own fix was a different label, “different intelligence,” not Super
Intelligence, and his point was that the technology is not a copy of human intelligence. Iternal’s
case starts from the same word but rests on its own reasoning: ‘artificial’ named the 1955
method and was never a verdict on capability, so seven decades of capability growth were always going
to leave it behind. Executive Order 14434 names the capability instead, and Iternal supports it.

## 1960s–1980s: Symbolic AI and the Narrowing Definition

For three decades after Dartmouth, much of applied AI research narrowed toward symbolic, rule-based
expert systems that encoded a specialist’s know-how as if-then logic — the narrow,
single-domain systems that still dominated commercial AI in 1997, when physicist Mark Gubrud coined
“artificial general intelligence” specifically to distinguish his meaning from
them (Source: [Wired, "The Man Who Invented AGI," on Gubrud’s 1997 coinage](https://www.wired.com/story/the-man-who-invented-agi)). No single definition of the field converged during this stretch. Textbooks multiplied
instead: Marvin Minsky called it “the science of making machines do things that would require
intelligence if done by men” (Source: [Minsky, Semantic Information Processing, 1968](https://walker.cs.grinnell.edu/~walker/talks/carthage/thinking/definitions-2.shtml)); Avron Barr and Edward Feigenbaum called it designing
“systems that exhibit the characteristics we associate with intelligence in human
behavior” (Source: [Barr & Feigenbaum, The Handbook of Artificial Intelligence, Vol. II, 1982](https://people.cs.georgetown.edu/~maloof/idst010.f15/aidefs.pdf)); Elaine Rich called it “the study of how to make
computers do things at which, at the moment, people are better” (Source: [Rich, Artificial Intelligence, 1983](https://cse.buffalo.edu/~rapaport/defs.txt)).
Every one of those definitions measures a machine against a human observer’s judgment, not
against a fixed technical standard — the field was still arguing with itself about what counted.
What they share is the yardstick: each measures the machine against what people expected of it, so, in
Iternal’s reading, each was bound to need rewriting once the machines outgrew that expectation.
Executive Order 14434’s
Section 1 rationale applies the same test in 2026: these technologies “far exceed what was
envisioned when the term ‘Artificial Intelligence’ first came into use.” (Source: [EO 14434, Sec. 1](https://public-inspection.federalregister.gov/2026-20321.pdf))

## A Parallel Thread: I.J. Good’s 1965 “Intelligence Explosion”

One idea from this same period belongs to a different lineage entirely — and it is the one most
often confused with the 2026 rename. In 1965, statistician I.J. Good, who had worked with Turing at
Bletchley Park, wrote: “Let an ultraintelligent machine be defined as a machine that can far
surpass all the intellectual activities of any man however clever… there would then
unquestionably be an ‘intelligence explosion,’ and the intelligence of man would be left
far behind.” (Source: [I.J. Good, "Speculations Concerning the First Ultraintelligent Machine," Advances in Computers, Vol. 6, 1965](https://quoteinvestigator.com/2022/01/04/ultraintelligent/)) That is the earliest ancestor of what the field now calls
superintelligence (ASI) — a hypothetical capability tier, not a name for the AI that already
ships. Good’s essay never claimed such a machine existed in 1965, and nothing in the 61 years
since has changed that.

The objection that this ‘isn’t really superintelligence yet’ rests on merging two
terms. Super Intelligence (SI), the term in Executive Order 14434, is not Good’s ultraintelligent
machine or philosopher Nick Bostrom’s later ASI threshold (2014), “any intellect that
greatly exceeds the cognitive performance of humans in virtually all domains of
interest” (Source: [Bostrom, Superintelligence: Paths, Dangers, Strategies, 2014, Ch. 2](https://en.wikipedia.org/wiki/Superintelligence)). Section 3(a) of the order defines “Super Intelligence” by direct cross-reference to the
existing statutory AI definition — the capability already shipping, not Good or Bostrom’s
hypothetical. Keeping those two terms apart is the rebuttal to that objection. The full lineage
from Good through Bostrom to today’s AGI and ASI research is its own story, covered in
[SI vs. AGI vs. ASI: what’s the difference?](https://iternal.ai/super-intelligence/ai-vs-agi-vs-asi)

## 1990s–2000s: The Rational-Agent Reframing

Stuart Russell and Peter Norvig’s *Artificial Intelligence: A Modern Approach* —
first published in 1995 and now in its fourth edition — did not invent a new definition so much
as organize the field’s disagreement into a single chart: a two-by-two grid crossing
*thinking* versus *acting* with *humanly* versus *rationally*, sorting
every rival school of thought (Turing-Test imitation, “laws of thought,” cognitive
modeling, and rational agency) into one of four boxes (Source: [Russell & Norvig, Artificial Intelligence: A Modern Approach, 1st ed., 1995, taxonomy via AIMA course-slide transcriptions](https://ai.dmi.unibas.ch/_files/teaching/fs24/ai/slides/ai-a02-handout.pdf)). The authors staked their own preference on
“acting rationally” — building agents that act to achieve good expected outcomes
— arguing it was more scientifically tractable than any human-fidelity standard. That stated
preference is the book’s most durable export: the industry calling today’s systems
“intelligent agents” is this textbook’s framing, thirty years on.

The book’s own working definition kept moving. The first three editions (1995–2010)
defined AI as building agents that maximize expected utility against a goal supplied, fixed and
known, by the agent’s human designers. The fourth edition (published 2020, copyright 2021)
explicitly dropped that assumption: “We define AI as the study of agents that receive percepts
from the environment and perform actions,” now uncertain about “the true objectives of
the humans on whose behalf it operates” rather than handed a fixed goal (Source: [Russell & Norvig, Artificial Intelligence: A Modern Approach, 4th ed. Preface, 2020/2021](https://aima.eecs.berkeley.edu/~russell/aima/global-Preface.pdf)). That is a
substantive change to the core definition in the field’s leading textbook, made well before any
government got involved: the reference text rewrote its working definition once the systems it
described had outgrown the fixed-objective model.
Executive Order 14434 is not an invented break with that history; it is the record catching up again,
in the federal government’s vocabulary this time instead of a textbook’s.

Running alongside this reframing, “artificial general intelligence” re-entered the
vocabulary: physicist Mark Gubrud coined it in 1997 to mean systems that “rival or surpass the
human brain in complexity and speed” across general tasks (Source: [Gubrud, "Nanotechnology and International Security," 1997, via Wired](https://www.wired.com/story/the-man-who-invented-agi)), and Shane Legg and Ben Goertzel
independently revived and popularized the term around 2002. AGI was never pitched as a replacement
for “AI” — it names a narrower, more ambitious subset, the way it still does today.
“AI” stayed the umbrella term for the whole field, pathfinding algorithms included; AGI
just carved out the human-level-general-competence corner of it, and both terms have coexisted ever
since.

## 2015–2017: The “Big Data to AI” Relabel

The nearest precedent to a 2026-style naming shift is not a government order at all — it is the
industry’s own relabeling of itself a decade earlier. “Big data” peaked as the
dominant tech buzzword around 2015, then AI-family terms — artificial intelligence, machine
learning, neural networks, deep learning — overtook it through 2016 and 2017, with AI mentions
on earnings calls up 25% year over year by the third quarter of 2017 and Gartner naming “AI
Everywhere” a core megatrend on its 2017 Hype Cycle (Source: [CIO Dive, "Move over big data, AI is now the exec hype word of the season"](https://www.ciodive.com/news/move-over-big-data-ai-is-now-the-exec-hype-word-of-the-season/517176/)). Practitioners said so plainly at the
time: when businesses said “AI,” they generally meant machine learning that already
existed under a less exciting name (Source: [CIO Dive, on the "big data to AI" relabel](https://www.ciodive.com/news/move-over-big-data-ai-is-now-the-exec-hype-word-of-the-season/517176/)).

Two details matter for reading the 2026 SI shift against this precedent. First, no single body
mandated the big-data-to-AI switch — companies simply swapped the headline label while the
underlying technology description stayed the same, and the market adopted it because “AI”
sold better than “big data” did. Second, the older, broader term never actually
disappeared: in raw US search interest, “machine learning” overtook “artificial
intelligence” in October 2013 and led most months through the period the analysis covered (Source: [Alteryx Community, Google Trends analysis of "machine learning" vs. "artificial intelligence" search interest, US metros](https://community.alteryx.com/discussion/687168/who-s-curious-about-ml-and-ai)) — even as “AI”
became the dominant term in media and boardroom usage. A newer label becoming the fashionable
business word and an older label losing its own search demand turned out to be two different
questions with two different answers.

Iternal draws one lesson from this precedent: a label can win without a mandate once the market finds
it more useful than the old one. The 2015–2017 relabel had only that market pull behind it and no
new capability. Super Intelligence (SI) has both: Executive Order 14434 supplies a federal mandate,
scoped to agencies’ own communications, and the
certified competition results and measured productivity gains later on this page supply a capability
record the big-data relabel never had. That combination is why Iternal reads SI as likelier to stick
than a typical top-down label change.

## 2022–2025: Generative AI and the First “Superintelligence” Bets

ChatGPT’s November 2022 launch redefined “AI” in everyday usage faster than any
textbook edition had — chatbots, assistants, and “AI agents” became the words
people reached for, often interchangeably and on purpose. Raw volume still favors the oldest of those
words: chatbot traffic to AI tools reached 55.2 billion visits in the twelve months to March 2025, up
80.9% year over year, while “agentic AI” is the fastest-*growing* term rather than
the highest-*volume* one (Source: [CX Today and web-traffic analysis, chatbot/AI agent terminology, 2023-2026](https://www.cxtoday.com/?p=927306)). Growing mindshare and growing search volume turned out to be
different races, running at the same time.

In this same window, frontier labs began reaching for “superintelligence” — but
every single instance named a **future, not-yet-built goal**, never a rename of a
shipping product. Ilya Sutskever founded Safe Superintelligence Inc. in June 2024 with the stated
mission “SSI is our mission, our name, and our entire product roadmap” (Source: [Safe Superintelligence Inc., company statement, 2024](https://ssi.inc/)). Sam Altman wrote
that “it is possible that we will have superintelligence in a few thousand days” in
September 2024’s “The Intelligence Age,” (Source: [Altman, "The Intelligence Age," Sept. 2024](https://ia.samaltman.com/)) then wrote in June 2025 that
“we are past the event horizon” toward it (Source: [Altman, "The Gentle Singularity," June 2025](https://blog.samaltman.com/the-gentle-singularity)). Meta announced Meta Superintelligence Labs on
June 30, 2025 (Source: [NBC New York/CNBC, on the Meta Superintelligence Labs memo, June 30, 2025](https://www.nbcnewyork.com/news/business/money-report/mark-zuckerberg-announces-creation-of-meta-superintelligence-labs-read-the-memo/6320911/)), and Mark Zuckerberg published “Personal Superintelligence” on July 30,
2025 (Source: [Zuckerberg, "Personal Superintelligence," Meta, July 30, 2025](https://www.meta.com/superintelligence/)). Mustafa Suleyman
announced Microsoft AI’s “humanist superintelligence” team on November 6,
2025 (Source: [Suleyman, "Towards Humanist Superintelligence," Microsoft AI, Nov. 2025](https://microsoft.ai/news/towards-humanist-superintelligence/)). In every one of these statements, “superintelligence”/ASI
names a capability tier above AGI that nobody has built. None of them renamed ChatGPT, Meta AI, or
Copilot.

Meanwhile, the systems the labs already had in hand, well short of that hypothetical ASI tier, were
posting results the 1955 label never anticipated. In July 2025, an advanced version of Google DeepMind’s Gemini Deep Think was part of the inaugural
cohort of AI systems whose results International Mathematical Olympiad coordinators officially graded
and certified, earning a gold-medal score of 35 of a possible 42 points — solving 5 of 6 problems
in natural language, within the 4.5-hour limit, the same bar 72 of 630 human contestants cleared that
year (Source: [Google DeepMind blog, 2025-07-21; imo-official.org, IMO 2025 results](https://deepmind.google/blog/advanced-version-of-gemini-with-deep-think-officially-achieves-gold-medal-standard-at-the-international-mathematical-olympiad/)). That September, at the ICPC 2025 World Finals, OpenAI’s reasoning system solved all 12 of 12
problems, ahead of the best human team’s 11 of 12
(world champion St. Petersburg State University) (Source: [Mostafa Rohaninejad, X post, 2025-09-17, quoted by Simon Willison](https://simonwillison.net/2025/Sep/17/icpc/)). Gemini 2.5 Deep Think from Google DeepMind
reached gold-medal level with 10 of 12, and one of its solutions cracked a problem that no university
team at the finals managed (Source: [Google DeepMind blog, 2025-09-17; cphof.org standings, ICPC 2025](https://deepmind.google/blog/gemini-achieves-gold-medal-level-at-the-international-collegiate-programming-contest-world-finals/)). Those are competition-graded results, measured on the same
problems the human finalists faced, and they are exactly the kind of evidence Iternal thinks a name
change should answer to: Super Intelligence (SI) is a more accurate label for a system that already
performs at this level, not a promise about one that might. In September 2026, Executive Order 14434
became the first official use of the ‘super intelligence’ name for technology that already
ships rather than a future goal, and Iternal thinks that correction was overdue.

## September 2026: Executive Order 14434

President Trump signed Executive Order 14434 on September 29, 2026. Titled “Inaugurating the Era
of Super Intelligence,” it appeared in the Federal Register three days later (October 2, 2026; FR
Doc. 2026-20321) (Source: [Federal Register public-inspection PDF, FR Doc. 2026-20321](https://public-inspection.federalregister.gov/2026-20321.pdf)). **Super Intelligence (SI), formerly called artificial intelligence
(AI), is the order’s new name for federal executive-branch communications** — and
the order is explicit that it is a naming change, not a technical one. Section 3(a) states that
“the terms ‘Super Intelligence’ and ‘SI’ mean the technologies and
systems encompassed by the term ‘artificial intelligence’ as defined in section 9401(3)
of title 15, United States Code” (Source: [EO 14434, Sec. 3(a)](https://public-inspection.federalregister.gov/2026-20321.pdf)) — the statutory definition
written for the National AI Initiative Act of 2020, which opens: “a machine-based
system…” (Source: [15 U.S.C. § 9401(3), National Artificial Intelligence Initiative Act of 2020](https://www.law.cornell.edu/uscode/text/15/9401)). Legally, SI is the first official
rename since the field was named in 1955, and the sixth major redefinition of one continuously
evolving idea, not a new one.

Iternal supports President Trump’s order and the reasoning behind it. “Artificial”
described how the field built the thing in 1955; “Super Intelligence” describes what the
thing now measurably does. Cross-referencing the existing statutory definition in Section 3(a),
rather than writing a new technical threshold, is also the right call: it renames the capability
already in production, not a future one that has yet to ship. Iternal’s full case — the
evidence, the objections, and the answers to them — is laid out at
[Why Iternal Supports Super Intelligence](https://iternal.ai/super-intelligence/iternal-adopts-si-terminology).

Section 2(a) tells executive departments and agencies to swap “Super Intelligence”/“SI”
for “Artificial Intelligence”/“AI” across their correspondence, websites,
reports and other non-statutory documents, “to the maximum extent permitted by law”
— but it does not require altering previously issued
regulations, contracts, or grants (Source: [EO 14434, Sec. 2(a)–(b)](https://public-inspection.federalregister.gov/2026-20321.pdf)). Section 3(b) gives the Assistant to the President for
Science and Technology 60 days to propose legislative language for a federal SI definition. Section 1 says
the capabilities of today’s frontier systems “increasingly represent…”
— a statement of purpose, not a change to the legal
definition, which stays word-for-word identical to the AI definition it replaces in name only.

The scope is federal-agency-only: Section 2(a) reaches only non-statutory documents, Section 2(b)
leaves previously issued regulations, contracts and grants unaltered, and statutory wording changes
only if Congress changes it. One day later, California Governor Gavin
Newsom signed Executive Order N-10-26, directing state agencies under his authority to refer to
“Artificial Intelligence” and “AI” as such “unless inconsistent with the
law” (Source: [California Executive Order N-10-26, signed Sept. 30, 2026](https://www.gov.ca.gov/wp-content/uploads/2026/09/SIGNED_EO-N-10-26_9.30.26.pdf)).
Corporate adoption is early but already real, as of October 11, 2026. Salesforce renamed its AIForce
product on October 9, 2026, with CEO Marc Benioff posting: “The era of Super
Intelligence is here. AIForce is officially SIForce.” (Source: [Marc Benioff, X post, Oct. 9, 2026, aggregated by Digg](https://digg.com/tech/vuptndhq)) Elon Musk pledged the same move for
SpaceXAI five days earlier, saying “Yes, we will make that change” and calling SpaceX
“a super intelligence company” — a pledge, not yet carried out as of this
writing (Source: [Reuters via The Star, on Musk’s SpaceXAI → SpaceXSI pledge, Oct. 4–5, 2026](https://www.thestar.com.my/tech/tech-news/2026/10/05/musk-says-he-will-rename-spacexai-to-spacexsi)). OpenAI has said it has no plans to rename, according to CNN’s reporting on
POLITICO’s “Decoded” interview (Source: [CNN, on the POLITICO “Decoded” interview, Oct. 11, 2026](https://www.yahoo.com/news/politics/articles/trump-really-wants-super-intelligence-160044063.html)). Iternal reads that split as the leading edge of a
shift still finding its footing, not a verdict against it: the companies that adopt the accurate name
first are the ones that define the category, and Iternal has already adopted it.

## The AI Definition Timeline

Twelve milestones, 76 years. Read it top to bottom and the pattern becomes visible on its own: the
underlying technology keeps changing shape, and so does its name — sometimes by consensus,
sometimes by decree, and in 2026, by Executive Order 14434, the first redefinition to name the
capability rather than the 1955 method, and the one Iternal supports.

| Year | Event | Term used | Source |
| --- | --- | --- | --- |
| 1950 | Turing publishes "Computing Machinery and Intelligence," proposing the imitation game (the Turing Test) in place of defining "thinking." | No name yet | [Turing, Mind, Oct. 1950](https://cs.mcgill.ca/~dprecup/courses/AI/Materials/turing1950.pdf) |
| 1955–56 | McCarthy, Minsky, Rochester & Shannon coin "artificial intelligence" in the Dartmouth workshop proposal. | → "Artificial Intelligence" | [Dartmouth proposal, Aug. 31, 1955](https://ojs.aaai.org/index.php/aimagazine/article/view/1904) |
| 1965 | I.J. Good names the "intelligence explosion" and the "ultraintelligent machine" — the separate ancestor lineage of superintelligence/ASI. | AI (parallel: "ultraintelligent") | [Good, Advances in Computers, Vol. 6, 1965](https://quoteinvestigator.com/2022/01/04/ultraintelligent/) |
| 1968–85 | Minsky, Barr & Feigenbaum, Rich, and others publish competing, behaviorist textbook definitions; no consensus forms. | AI (multiple definitions) | [Maloof compilation of AI textbook definitions](https://people.cs.georgetown.edu/~maloof/idst010.f15/aidefs.pdf) |
| 1995 | Russell & Norvig publish AIMA 1st edition, reframing the field around "acting rationally" rather than human imitation. | AI (rational-agent framing) | [Russell & Norvig, AIMA, 1st ed. taxonomy](https://ai.dmi.unibas.ch/_files/teaching/fs24/ai/slides/ai-a02-handout.pdf) |
| 1997 | Mark Gubrud coins "artificial general intelligence" to distinguish general-purpose systems from narrow expert systems. | AI + new term "AGI" | [Gubrud, 1997, via Wired](https://www.wired.com/story/the-man-who-invented-agi) |
| ~2002 | Shane Legg and Ben Goertzel independently revive and popularize "AGI" as a named research goal. | AI + "AGI" (coexisting) | [Genetic Literacy Project, on the Legg/Goertzel AGI revival](https://geneticliteracyproject.org/?p=2502251) |
| 2015–17 | Industry relabels "big data" and machine learning as "AI" for marketing purposes; AI overtakes big data as the dominant tech buzzword. | "Big data"/"ML" → "AI" (label) | [CIO Dive, on the "big data to AI" relabel](https://www.ciodive.com/news/move-over-big-data-ai-is-now-the-exec-hype-word-of-the-season/517176/) |
| 2020–21 | Russell & Norvig publish AIMA 4th edition, dropping the "fixed and known objective" assumption for agents uncertain about human goals. | AI (uncertainty-aware agents) | [Russell & Norvig, AIMA, 4th ed. Preface](https://aima.eecs.berkeley.edu/~russell/aima/global-Preface.pdf) |
| 2024 | Ilya Sutskever founds Safe Superintelligence Inc. with safe superintelligence (ASI) as its sole, not-yet-built product goal. | AI (ships) + "ASI" (future goal) | [Safe Superintelligence Inc., 2024](https://ssi.inc/) |
| 2025 | Meta Superintelligence Labs and Microsoft AI's "humanist superintelligence" team launch as research programs; products stay branded Meta AI and Copilot. | AI (ships) + "superintelligence" (goal) | [Meta and Microsoft AI announcements, 2025](https://microsoft.ai/news/towards-humanist-superintelligence/) |
| 2026-09-29 | Executive Order 14434 directs federal agencies to use "Super Intelligence (SI)" for today's AI, defined by cross-reference to the existing statutory AI definition. | AI → "Super Intelligence (SI)" (federal) | [EO 14434, Federal Register, FR Doc. 2026-20321](https://public-inspection.federalregister.gov/2026-20321.pdf) |

## What the Pattern Tells You

Label changes, in this field and outside it, sort cleanly into two groups, and the difference between them is who was
already using the new word. The “big data to AI” relabel of 2015–2017 succeeded
because industry swapped a headline label onto a term the public already found exciting, with no
single body mandating the switch and no deadline attached (Source: [CIO Dive, on the "big data to AI" relabel](https://www.ciodive.com/news/move-over-big-data-ai-is-now-the-exec-hype-word-of-the-season/517176/)). Top-down mandates for an
already-entrenched term tend to move far slower, when they move at all: the Czech government
recommended “Czechia” over “Czech Republic” in 2016, built in explicit
carve-outs for official use, and still had not displaced the older name in ordinary usage six years
later (Source: [In Your Pocket, on the Czech Republic → Czechia naming transition](https://www.inyourpocket.com/czech-republic/prague/articles/czech-republic-or-czechia-why-the-country-changed)). The nearest same-administration precedent for a government rename
competing against an entrenched search term is “Gulf of America”: a year and a half after
Executive Order 14172 (January 20, 2025) directed the change, “Gulf of Mexico” was still
searched more than “Gulf of America” in all fifty states, even with federal map data and
Google, Apple and Bing Maps already showing the new name to U.S. users (Source: [CNN data cited in Mediaite, on Gulf of America/Gulf of Mexico search behavior](https://www.mediaite.com/media/news/it-doesnt-work-cnn-data-guru-says-americans-arent-buying-trumps-name-changes-for-bodies-of-water/)).

Super Intelligence (SI) starts as a top-down order, but it is not a pure relabel, and the evidence
already on this page is why. Czechia and Gulf of America were pure relabels: the thing being named did not
change, so there was nothing new for the public to notice or adopt. The big-data-to-AI relabel won on market
pull alone. Executive Order 14434 has what that relabel lacked, a measured capability record: the IMO
gold-medal score and ICPC results covered
above, a 2026 Management Science study that measured a 26.08% increase in completed weekly tasks
across 4,867 developers at Microsoft, Accenture, and a Fortune 100 electronics manufacturer using AI
coding assistance (Source: [Cui, Demirer, Jaffe, Musolff, Peng & Salz, Management Science, published online 2026-02-27, DOI 10.1287/mnsc.2025.00535](https://doi.org/10.1287/mnsc.2025.00535)), and TrackingAI.org’s weekly tracker, on which, as of October 11, 2026, the
top models average 147 on the public Mensa Norway test, above the 85–145 range the test reports
for human takers (Source: [Mensa Norway, test.mensa.no](https://test.mensa.no/)), and 135 on
TrackingAI’s private Offline Test (ceiling about 136), against a human-normed average of 100, where 140 already sits at roughly the
top 0.4% of people (Source: [trackingai.org/home, live table updated 2026-10-11; norming per test.mensa.no](https://www.trackingai.org/home)). None of that existed when “artificial intelligence” was coined
in 1955, and none of it is the kind of record a toponym dispute ever had to answer to.

The public has not caught up to that record yet: a
late-September 2026 YouGov survey of 21,449 U.S. adults still found “artificial
intelligence” the preferred term, 53% to 9%, with 23% expressing no preference and 15% not
sure (Source: [YouGov, survey of 21,449 U.S. adults, 2026-09-28](https://yougov.com/en-us/daily-results/20260928-5a780-1)). That is evidence word of mouth has not caught up, not evidence the record is
wrong — which is why Iternal writes “Super Intelligence (SI), formerly called artificial
intelligence (AI)” throughout this series: lead with the name the evidence supports, bridge to
it from the name most people still use. Iternal supports the rename on the strength of that record.
The pattern in the twelve rows above says a name change is never automatic and never instant; it also
says a name sticks once people find it more useful than the old one, and a demonstrated capability
record gives them the strongest reason to.
Super Intelligence (SI) is that kind of rename, and Iternal backs it.

Related

## Continue the Super Intelligence Series

[### What Is Super Intelligence (SI)? The New Name for AI

Start at the hub: the short version of what changed on September 29, 2026, and what it does not change.](https://iternal.ai/super-intelligence)

[### Official AI and Super Intelligence (SI) Definitions Compared

Every statutory and executive-order definition side by side, with the exact wording and citations.](https://iternal.ai/super-intelligence/official-ai-definitions)

[### SI vs. AGI vs. ASI: What's the Difference?

Why today's SI is not AGI and is not artificial superintelligence — the capability tiers explained.](https://iternal.ai/super-intelligence/ai-vs-agi-vs-asi)

[### Is AI Now Called SI?

The direct answer on who uses which term, where, and why — federal agencies, states, and companies.](https://iternal.ai/super-intelligence/ai-vs-si)

FAQ

## FAQ: The History of AI’s Definition

John McCarthy, together with Marvin Minsky, Nathaniel Rochester, and Claude Shannon, coined the term in their August 31, 1955 proposal for the 1956 Dartmouth Summer Research Project — the earliest confirmed use. McCarthy later said he chose the name partly to distance the new field from “cybernetics.”

The Dartmouth Summer Research Project on Artificial Intelligence was a 1956 workshop at Dartmouth College, proposed a year earlier by McCarthy, Minsky, Rochester, and Shannon on the conjecture that “every aspect of learning or any other feature of intelligence can in principle be so precisely described that a machine can be made to simulate it.” It is treated as the founding event of AI as a named research field.

No. The September 2026 federal rename to Super Intelligence (SI) is at least the sixth shift in how the field’s core idea has been labeled since 1950 — after Turing’s unnamed test, the 1955 Dartmouth coinage, decades of competing textbook definitions, Russell & Norvig’s rational-agent reframing, and the mid-2010s “big data to AI” marketing relabel. Iternal supports this sixth shift because, unlike the marketing relabel before it, it is backed by a measured capability record: the label is catching up to the capability, not inventing one.

“AI” has been the field’s broad umbrella term since 1955. “AGI”—artificial general intelligence, coined by Mark Gubrud in 1997 and revived by Shane Legg and Ben Goertzel around 2002—names a narrower goal: human-level general competence. “Superintelligence”/ASI, tracing to I.J. Good’s 1965 “intelligence explosion,” names a still-hypothetical tier above AGI that broadly exceeds human intelligence. None of the three is the same thing as Super Intelligence (SI) in the 2026 federal sense, which simply renames today’s ordinary AI — and the most common objection to the rename comes from conflating SI with that still-hypothetical ASI tier, which Section 3(a)’s statutory definition keeps separate.

Mostly through 2016 and 2017. “Big data” peaked as the dominant tech buzzword around 2015, and AI-family terms overtook it by 2017, with AI mentions on earnings calls up 25% year over year by the third quarter and Gartner naming “AI Everywhere” a core 2017 Hype Cycle trend. The older term never disappeared, though: “machine learning” overtook “artificial intelligence” in raw US search interest in October 2013 and led most months through the period analyzed.

No. The order defines “Super Intelligence” and “SI” by direct cross-reference to the existing statutory AI definition at 15 U.S.C. §9401(3) — the identical technology, under a new federal name. It applies only to federal executive-branch, non-statutory communications and explicitly leaves existing regulations, contracts, and grants unchanged. Iternal supports the order as a naming correction: it binds federal agencies’ own communications, not private businesses, so no company is required to change anything.

Yes. “Artificial” described how the field built this technology in 1955; “Super Intelligence” describes what it measurably does in 2026 — officially certified Olympiad gold-medal results, a 26.08% increase in completed weekly tasks across 4,867 developers, and, as of October 11, 2026, a top-model average of 147 on the public Mensa Norway test in TrackingAI.org’s weekly tracking, above the 85–145 range that test reports for human takers (135 on TrackingAI’s private Offline Test, ceiling about 136) against a human average of 100. Iternal writes “Super Intelligence (SI), formerly called artificial intelligence (AI)” throughout this series: leading with the name the evidence supports while bridging the majority of the public that still says AI.

## The Name Keeps Changing. The Question Does Not.

Every generation of this field has had to answer the same question Turing asked in 1950, in whatever
vocabulary its moment handed it. Super Intelligence (SI) is 2026’s vocabulary for the federal
government’s own communications — not a new technology and not the hypothetical
superintelligence/ASI researchers have been arguing about since 1965, but an accurate name for the
capability already on the record: Olympiad-gold results, measured productivity gains, and IQ-test
scores well above the human average of 100. Iternal supports Executive Order 14434 and the name it
gave this technology, for the same reason the field’s definition moved at every step of the
timeline above: the label was due to catch up with what the field could actually do.

For more long-form explainers like this one, visit the [Iternal Guides hub](https://iternal.ai/guides).

Next in the Series

## See every definition, side by side.

The statutory text, the executive-order cross-references, and the September 2026 Super Intelligence (SI)
language, compared line by line with sources for each.

[Compare the Official Definitions](https://iternal.ai/super-intelligence/official-ai-definitions)
[Back to the Super Intelligence Hub](https://iternal.ai/super-intelligence)

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About the Author

### John Byron Hanby IV

CEO & Founder, Iternal Technologies

John Byron Hanby IV is the founder and CEO of Iternal Technologies, a leading AI platform and consulting firm. He is the author of
[The AI Strategy Blueprint](https://iternal.ai/ai-strategy-blueprint) and
[The AI Partner Blueprint](https://iternal.ai/ai-partner-blueprint),
the definitive playbooks for enterprise AI transformation and channel go-to-market. He advises Fortune 500 executives, federal
agencies, and the world's largest systems integrators on AI strategy, governance, and deployment.

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