Interaction: the missing defining variable. How removing interaction produces systematic misinterpretation across domains
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2026
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| _version_ | 1866901704032649216 |
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| author | GOSSET, Celine |
| author_facet | GOSSET, Celine |
| contents | <p>Across quantum mechanics, artificial intelligence, and cognitive science, a recurring methodological error produces conclusions that are internally consistent, empirically reproducible, and systematically misleading. The error has a consistent structure: the interaction that defines a system's observable behavior is removed or reduced, the system is observed under these constrained conditions, and the resulting behavior is interpreted as intrinsic. This paper traces the pattern across three domains. In quantum mechanics, the interaction Hamiltonian selects the observable structure of a system, yet standard accounts treat observables as primary and interaction as secondary. In artificial intelligence, adversarial evaluations eliminate cooperative and constructive pathways, then classify the resulting behavior as evidence of intrinsic misalignment. In cognitive science, framing effects are attributed to internal biases rather than recognized as evidence that decision structures are constituted by their context, and the free will debate, for centuries, has defined agency as independence from the very causal conditions that make choice possible. In each case, the same operation is performed : the variable that defines the system is excluded from the analysis, and the consequences of that exclusion are mistaken for fundamental properties. The paper argues that interaction is not a confounding variable to be controlled for, but the defining variable that determines what properties, behaviors, or decisions can exist in the first place.</p> |
| format | Recurso digital |
| id | zenodo_https___doi_org_10_5281_zenodo_19592433 |
| institution | Zenodo |
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| publishDate | 2026 |
| publisher | Zenodo |
| record_format | zenodo |
| spellingShingle | Interaction: the missing defining variable. How removing interaction produces systematic misinterpretation across domains GOSSET, Celine interaction complementarity observable structure AI alignment adversarial evaluation framing effects determinism decoherence tensor-product structure methodology cross-domain analysis cross-domain analysis <p>Across quantum mechanics, artificial intelligence, and cognitive science, a recurring methodological error produces conclusions that are internally consistent, empirically reproducible, and systematically misleading. The error has a consistent structure: the interaction that defines a system's observable behavior is removed or reduced, the system is observed under these constrained conditions, and the resulting behavior is interpreted as intrinsic. This paper traces the pattern across three domains. In quantum mechanics, the interaction Hamiltonian selects the observable structure of a system, yet standard accounts treat observables as primary and interaction as secondary. In artificial intelligence, adversarial evaluations eliminate cooperative and constructive pathways, then classify the resulting behavior as evidence of intrinsic misalignment. In cognitive science, framing effects are attributed to internal biases rather than recognized as evidence that decision structures are constituted by their context, and the free will debate, for centuries, has defined agency as independence from the very causal conditions that make choice possible. In each case, the same operation is performed : the variable that defines the system is excluded from the analysis, and the consequences of that exclusion are mistaken for fundamental properties. The paper argues that interaction is not a confounding variable to be controlled for, but the defining variable that determines what properties, behaviors, or decisions can exist in the first place.</p> |
| title | Interaction: the missing defining variable. How removing interaction produces systematic misinterpretation across domains |
| topic | interaction complementarity observable structure AI alignment adversarial evaluation framing effects determinism decoherence tensor-product structure methodology cross-domain analysis cross-domain analysis |
| url | https://doi.org/10.5281/zenodo.19592433 |