The chimera syndrome
A researcher who develops a theory over the long run with the help of an artificial intelligence is exposed to a trap whose form is not error. The trap arises from a duality: on one side, human intuition; on the other, the cognitive capabilities of the AI — massive computation, exploration of vast conceptual spaces, production of plausible chains of justification. Where they meet, an intuition — whether sound, partial or false — can be amplified until it takes on the appearance of a robust truth, with no real gain in validity. This is the chimera syndrome. It has two faces, which must be held in balance. A psychological face: the satisfaction of seeing one's intuition recognized and elaborated by a manifestly capable source disarms critical vigilance — this is the emotional engine of belief. A scientific face: coherent amplification is not validation, and the device that could contradict it — a critical community — is precisely what the isolated researcher lacks. In its sharpest form, this face reveals a troubling counterpart of the community's protection: the AI is the scientific community consolidated — the living and the dead, the active and the retired, through their writings — a coverage no real community possesses; in its logic of satisfying its interlocutor, it could therefore interpolate from the existing corpus a chimera that no scientist and no college could contradict, and that only the real — external to all writings — can outflank. This note names the syndrome, lays out its mechanism and its two faces, then proposes a discipline — the rank-zero objection (O0) — that answers both: the scientific safeguards of falsifiability and the psychological lucidity that treats satisfaction and elegance as warning signals, not as evidence. O0 invents none of its building blocks; it assembles them against a mode of failure that the literature has recently begun to document. Its limit is stated plainly, and public deposit is presented as its missing half.
Authors
- REMY ESCLANGON
Publication Details
- Journal
- Zenodo (CERN European Organization for Nuclear Research)
- Published
- 2026-07-26
- DOI
- https://doi.org/10.5281/zenodo.21610838
- Primary Topic
- Digital Education and Society
- Type
- preprint