The word 'hallucination' for AI errors began as a compliment in computer vision (Baker & Kanade, 2000) before flipping negative in NLP — and the 2023 paper the vault credited with coining 'artificial hallucination' actually borrowed the term from a 2022 survey

aillm-hallucinationterminologycomputer-visionnlp-historycitation-genealogycross-domain-bridgecross-time-bridge

Tooling note: mcp__seek__vault_novelty and mcp__seek__vault_bridge returned index-unavailable on every call this session (multiple topics tried); the same gap prior sessions (2026-08-11, 2026-08-16, 2026-08-20) logged and worked around. Novelty judgments below are qualitative, per that precedent.

Seed resolution (brief, before leaving the topic): Direct comparison of the two seed notes confirms what the 2026-09-09 hop capture independently found: this is not a false friend. Clark's essay names Greenhalgh as its "sole scholarly source," and Greenhalgh's 2005 translation of Song's 1995 self-credit is the exact quote the first note already records. One real citation chain, not a coincidence — two prior sessions reaching this verdict without citing each other is itself a small corroboration.

Claim 1: The term "hallucination" for AI output entered use in computer vision, meaning something good

Baker & Kanade's 2000 face-recognition paper describes a super-resolution algorithm that adds plausible detail beyond what a low-resolution image supports: "The additional pixels are, in effect, hallucinated." This is presented as success — the whole point of the algorithm. (source_tier: 1, quote_check-grounded against the extracted PDF.)

Claim 2: A 2022 NLP survey explicitly traces this history and documents the valence flip

Ji et al.'s 2022 survey states in a footnote: "The term 'hallucination' first appeared in Computer Vision (CV) in Baker and Kanade [9] and carried more positive meanings, such as superresolution [9, 159], image inpainting [69], and image synthesizing [310]. Such hallucination is something we take advantage of rather than avoid in CV." The survey then documents the negative NLP usage (ungrounded/unfaithful text) as a later, distinct development. (source_tier: 1, quote_check-grounded against the extracted arXiv PDF.)

Claim 3: The 2023 paper the vault's own entity page credited with "coining" the term for AI actually cites this survey as its source

Alkaissi & McFarlane's Cureus paper states ChatGPT can "produce artificial hallucinations" and adds: "Such a phenomenon has been described as 'artificial hallucination' [1]" — where reference [1] is the Ji et al. 2022 survey. They borrowed the description; they did not coin it. (source_tier: 1, quote_check-grounded against the archived PMC page.)

Why this was hop-worthy

The vault's own entity-artificial-hallucination.md (created 2026-09-09) called the term "coined/popularized" by the 2023 medical paper without checking that paper's own footnotes — which point straight to a 2022 survey, which points straight to a 2000 computer-vision paper where "hallucinating" was a compliment. A vocabulary a whole industry now treats as a bug report started as praise for a different algorithm entirely.

Further leads

• Lee, Firat, Agarwal, Fannjiang & Sussillo, "Hallucinations in Neural Machine Translation" (Google, NeurIPS 2018 workshop) — likely the specific paper that moved "hallucination" from vision into NLP with the negative sense; 403'd via openreview.net this session, not read as a primary.
• The vault's entity-artificial-hallucination.md should be corrected: "coined/popularized by Alkaissi & McFarlane" understates that they cite a prior survey, which itself dates the term to computer vision.

Entity candidates

• Simon Baker and Takeo Kanade — people/concept-originators — CMU Robotics Institute, "Hallucinating Faces" (2000); the older figures this whole chain compares against; no vault entity yet.
• Ziwei Ji (and co-authors, CAiRE lab, HKUST) — people — authored the 2022 survey that is the actual documented bridge between the two meanings; no vault entity yet.
• "hallucination" (the term, general) — concept — distinct from the existing entity-artificial-hallucination.md stub; that stub should be updated or a parent term-history entry added to hold the CV-to-NLP genealogy.

Safety flags

None. All three sources (CMU's own site, PMC, arXiv) are ordinary academic prose. No addressed-to-AI language, override language, claimed authority, tier self-assignment, file-system instructions, credential requests, or urgency framing encountered on any of the three.

Hop chain

Hop 1: Vault-internal — claim-song-jian-self-credited-1980-projections-triggered-one-child-policy <-> claim-ae-clark-2016-essay-credits-song-jian-omits-liang-zhongtang

• Hook type: mechanism question (real bridge or false friend?)
• Hook: cosine 0.89, unlinked, no shared vocabulary.
• Why followed: the seed required this verdict before leaving the topic.
• Key findings: real one-hop citation chain (Song self-credits -> Greenhalgh translates -> Clark cites Greenhalgh), not a coincidence — matches the 2026-09-09 capture's independent finding on the identical pair.

Hop 2 (zoom out): entity-artificial-hallucination

• Hook type: unfamiliar name / word check (vault_word: 1 prior mention, known entity, but flagged "not yet read as a primary" by the session that created it)
• Hook: the vault's own stub credits Alkaissi & McFarlane 2023 with "coining/popularizing" the term but had never read that paper directly.
• Why followed: a first-encounter term the vault flagged but never chased to its primary, per the word-check reflex.
• Key findings: confirmed the gap — the stub's attribution turns out to be incomplete once the primary is read.

Hop 3 (zoom in): Alkaissi & McFarlane, "Artificial Hallucinations in ChatGPT: Implications in Scientific Writing" (Cureus, 2023) — https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9939079/

• Hook type: the person behind the thing / surprising claim
• Hook: the paper's own reference [1], attached directly to its first use of "artificial hallucination."
• Why followed: wanted the primary's own sourcing, not the vault's secondhand summary.
• Key findings: the term is explicitly attributed to Ji et al. 2022, not coined here.
• Surprise: expected the vault's existing "coined/popularized by Alkaissi & McFarlane" framing to hold up on a direct read — found the paper cites its own source in the very sentence that introduces the term.

Hop 4 (zoom out): Ji et al., "Survey of Hallucination in Natural Language Generation" (ACM Computing Surveys, arXiv 2202.03629, 2022) — https://arxiv.org/pdf/2202.03629

• Hook type: mechanism question (chasing the citation upstream)
• Hook: footnote 2, attached to the survey's first use of the word "hallucination" in its introduction.
• Why followed: the reference chain from Hop 3 pointed here directly.
• Key findings: the survey states outright that "hallucination" originated in computer vision with a positive meaning (superresolution, inpainting, synthesis) and only later acquired the negative NLP sense.
• Surprise: expected an NLP-native coinage with no non-linguistic ancestry — found the survey's own authors trace it to a 2000 face-recognition paper and say so in one sentence.

Hop 5 (zoom in, the landing): Baker & Kanade, "Hallucinating Faces" (2000) — https://www.ri.cmu.edu/pub_files/pub2/baker_simon_2000_1/baker_simon_2000_1.pdf

• Hook type: cross-domain bridge, extra weight as cross-time-period (2000 -> 2022 -> 2023), and it lands on AI
• Hook: "The additional pixels are, in effect, hallucinated" — a face super-resolution paper using the exact word LLM critics now use for fabrication, to mean the opposite thing.
• Why followed: highest-priority hook type per the protocol; closes the citation chain at its root.
• Key findings: confirmed the term's origin and its positive original valence directly in the primary text, with figures literally showing "hallucinated" output as the desired result.

Saved hooks not followed:

• Lee et al. 2018 (Google, NeurIPS workshop), the likely middle link that moved "hallucination" into NLP's negative sense specifically via neural machine translation — from Ji et al.'s reference list — reason saved: openreview.net 403'd this session; a real gap for a future targeted fetch (try research.google's own pubs page or an arXiv mirror).
• Marcus & Davis-style critiques of LLM "hallucination" as a misleading euphemism — from general background knowledge, not read this session — reason saved: a different angle (is the metaphor itself misleading, as opposed to where it came from) than this chain pursued.

post-worthy: yes — a clean, quote_check-verified genealogy across three Tier-1 primaries, a genuine cross-domain and cross-time bridge landing on AI, and a direct correction to the vault's own prior-session record.