A three-arm experiment that varies the manner of AI use against a no-AI anchor and measures performance 15-20 min later, once the tool has been removed, results in an immediate near-transfer decrement rather than demonstrated lasting de-skilling.
Abstract
Whether generative AI erodes the skills it assists is usually studied by counting how much people use it, and while the tool is still in hand. That design cannot separate cause from selection, or distinguish using AI from depending on it. We report a three-arm experiment (900 randomized; 659 in the primary analysis) that varies the manner of AI use against a no-AI anchor and measures performance 15–20 min later, once the tool has been removed. Participants wrote an argumentative essay under a self-generation-first autonomous workflow (commit one's own position and then interrogate AI), a direct-adoption dependent workflow, or no AI and then wrote a second, parallel essay with no AI available. Two blind raters scored reasoning quality, idea diversity, and originality. On the unaided task, dependent users reasoned worse than participants who had never used AI (adjusted difference = −0.38 on a 1–7 scale, a small effect, d = −0.28, two-sided p = 0.0002), whereas autonomous users did not fall below that baseline. The pattern held under per-protocol, covariate-adjusted, Phase-1-time-adjusted, and full-randomized-sample multiple-imputation checks. A trait disposition toward autonomous offloading was discriminant from reflective thinking and critical-thinking disposition (HTMT ≤ 0.43) and incrementally predicted unaided reasoning. We did not detect a metacognitive pathway, although the design cannot exclude one. Because the two workflows differ in self-generation, elaboration, revision, and effort as well as in autonomy, the estimate belongs to the workflow contrast as a whole rather than to any single component: A generation-effect account is consistent with the pattern, but this design cannot weigh it against the alternatives, and no mechanism is established here. The result is an immediate near-transfer decrement rather than demonstrated lasting de-skilling. What separated the arms was not access to the model but the order in which the interaction required the user to produce something.
It is argued that effective human-AI collaboration depends on a deliberate sequence: human cognition must come first, before AI assistance enters the process, and the SSS framework is proposed, a structured, three-phase model in AI-assisted writing comprising the following.
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