SI vs AI: What the Super Intelligence Naming Change Means

What happened to the name AI?

On September 29, 2026, President Donald Trump signed an executive order directing U.S. executive agencies to substitute Super Intelligence for Artificial Intelligence in specified official communications and non-statutory documents, where legally permitted.

For the order's purposes, SI uses the existing statutory AI definition. Historical documents need not be rewritten. The order also requests proposed legislative language within 60 days; that request is not itself an enacted replacement definition.

This scope matters: a government terminology policy is not a global technical standard. Read the executive order, especially sections 2 and 3, for the operative wording.

The discussion becomes confusing when a headline compresses three questions into one: what a government calls a system, what researchers mean by intelligence, and what a particular product can actually do. Those questions need separate answers.

Event and terminology checked October 3, 2026. Later policy changes should be assessed against their own text and dates.

SI vs AI vs AGI vs ASI: a comparison

AI is the broad category. AGI and ASI describe ideas about the breadth and level of intelligence. SI, in this news story, is an administrative naming choice. Placing all four in a simple “old technology to new technology” sequence would hide these differences.

Stanford HAI's AI definition treats AI as a broad term, covering both specialized and more general-purpose systems. Its AGI explainer also notes that there is no universally accepted test. A confident label should not hide that uncertainty.

For the AGI–ASI distinction, IBM's technical overview emphasizes general capability across tasks. Excelling at a particular game or benchmark does not, by itself, establish broad superintelligence.

A name is not a capability evaluation

Imagine that a writing service changes its menu from “AI assistant” to “SI assistant” while keeping the same model and settings. The wording changes immediately. Whether the service writes a more accurate summary, follows instructions better, or makes fewer errors remains a separate question that requires testing.

Google DeepMind's Levels of AGI framework considers performance, generality, and autonomy. These are useful dimensions for interpreting a claim: how well the system performs, across how many tasks, and with what degree of independent action.

When evaluating a product described as SI, ask for concrete details:

• Task: Is the claim about editing an email, solving a research problem, or acting across applications?
• Evidence: Are examples representative, and can the method be repeated?
• Conditions: Did a person supply extensive instructions, select the best attempt, or correct the result?
• Failure cases: Where does it misunderstand context or produce unsupported statements?

For a writing tool, a small test using your own draft can be more useful than a broad intelligence slogan. Compare factual preservation, readability, and the amount of cleanup required. Keep the input and instructions consistent when comparing versions.

What should writers and editors do with the new term?

Start with the purpose of the document. A report about the naming event should identify SI and explain its context on first use. An explanation of machine learning should use terminology that accurately describes the technology. A direct quotation should preserve the speaker's wording.

Avoid replacing every instance of AI automatically. An article may refer to the formal title of a paper, a product name, a historical event, or someone else's definition. Blind replacement can make those references inaccurate and leave readers unsure whether the subject has changed.

For an existing article, make a deliberate editorial pass: add a dated explanation where the event is relevant, define the abbreviation once, and retain precise terms elsewhere. Do not change dates to make an unchanged article look newly researched.

Where does “SI humanizer” fit?

On UltraHumanizer, an SI humanizer is an entry point for rewriting generated drafts into more natural prose. The editing task stays concrete: remove unnecessary framing, improve sentence flow, and check that the result still says what the author intended.

The name is not evidence of a special superintelligence model. Read What Is an SI Humanizer? for examples and an editing workflow, or open the SI humanizer tool with a passage you want to revise.