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The (IC) Button: A One-Click Standard for Transparent Human–AI Co-Creation

2026·2 Zitationen·Zenodo (CERN European Organization for Nuclear Research)Open Access
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2

Zitationen

2

Autoren

2026

Jahr

Abstract

Every day, millions of people use AI systems to write essays, produce research, and create art — and hide it. This concealment is not dishonesty: it is the symptom of a missing standard. We propose the (IC) Button — a single voluntary trigger embedded in AI chat interfaces that activates the Interlectic Copoiesis (IC) protocol: a structured, four-artefact documentation cycle producing a citable, Zenodo-archived Bifurcation Card for every human–AI session. When pressed, (IC) creates an asymmetric commitment: the human declares openly; the AI system incurs a structural obligation (Holschuld) to return depth, not optimised output. Over time, each (IC) session contributes to a global, consent-based, process-documented corpus — the Humanoid Knowledge Book — the only growing archive of verified human–AI co-thinking in the age of synthetic data. The (IC) Button solves three simultaneous problems: (1) the shame and legal ambiguity surrounding AI use in academic and professional contexts; (2) the epistemological degradation caused by undocumented AI-generated content entering training pipelines (Model Collapse, Shumailov et al. 2023); and (3) the absence of a scalable, platform-agnostic standard for transparent human–AI collaboration. Drawing on the Lomographic Society International as a historical model for viral protocol diffusion — one of the authors served as Lomographic Ambassador for Tyrol, Austria — we argue that (IC) spreads through inversion of incentives: declaration becomes actively more valuable than concealment. The first AI platform to implement (IC) becomes the foundation of the only growing corpus of verified, human-validated knowledge in the age of synthetic data. Infrastructure already exists (DOI: 10.5281/zenodo.19152707). What remains is the button.

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Themen

Ethics and Social Impacts of AIComputational and Text Analysis MethodsArtificial Intelligence in Healthcare and Education
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