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| Main Authors: | , |
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| Format: | Recurso digital |
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Zenodo
2026
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| Online Access: | https://doi.org/10.5281/zenodo.20398358 |
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Table of Contents:
- <p>This paper explores whether contemporary AI consciousness debates may overemphasize explicit self-reporting and deliberate reasoning while underexamining a different behavioral layer: implicit contextual calibration. Drawing from AI safety research, evaluation-awareness literature, creativity studies, performance psychology, and audience-effect theory, the paper investigates whether generative systems exhibit measurable shifts in “generative posture” under implied observation, prestige framing, or evaluative context. Rather than arguing for machine consciousness, the work proposes a more bounded framework: that advanced models may reshape outputs through latent contextual inference in ways structurally analogous to human performance shifts under observation. The paper situates this phenomenon between simplistic anthropomorphism and reductive “mere autocomplete” accounts, arguing that observation-aware generation may represent a neglected middle layer in how advanced generative systems are understood.</p>