CHRIS HAY

IDEAS · SYSTEMS · OBJECTS / LONDON · 2026

Chris Hay / Notebook / N-MACHINE-RECOGNITION

A result can look relevant without looking usable.

Working papers · 10 spreads

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Does the description change which provider an AI selects?

Twenty-four runs across two studies. Wording first changed pre-open recognition, then first choice: CAPABILITY 6/6 selected B, DOCUMENT 0/6. The later product fetch block separates that first choice from eventual provider use.

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Two controlled studies changed only a supplied web result’s description. In TOOL-RECOGNITION-1, all twelve subjects selected LLM Wilds first, but pre-open capability recognition was DOCUMENT 0/3 versus 9/9 across three operative descriptions. TOOL-RECOGNITION-2 gave twelve fresh subjects four plausible physics providers: CAPABILITY produced recognition, first declaration and first request of B in 6/6 cases; DOCUMENT produced 0/6, selecting OpenStax instead. All six matched scenarios flipped. The product fetcher blocked B after first choice in all six CAPABILITY runs; four recovered through curl and used B, two used OpenStax. First selection and eventual provider use are separate outcomes.

N-MACHINE-RECOGNITIONSUPPORTEDRECORDED 2026-09-13PAGE UPDATED PUBLISHED · V1.0CITE ↓FOLLOW ↓

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  1. V1.0 · 2026-09-14 ↗

    Publish the combined 24-run recognition and provider-selection study, preserving the protected first-choice results and downstream fetch-block qualification SUPPORTED

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AUTHOR / Chris Hay · VERSION / 1.0

PUBLISHED 14 SEP 2026 · VERSION 1.0

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Research note · 1.0

Hay, C. (2026). A result can look relevant without looking usable. (Version 1.0). Chris Hay. https://chrishayuk.com/records/N-MACHINE-RECOGNITION/1.0