Delegation buys immediate performance at the cost of human engagement: in Hao et al. 2026 the Delegated Reasoning group "achieved the highest task performance" yet the Concerted Interpretation group "reported significantly greater use of self-regulation strategies," and Wu et al. 2025 show the performance boost "did not persist in subsequent tasks performed independently by humans" while intrinsic motivation fell—a small-scale signature of Park et al. 2026's "enrichment paradox."
The Wu et al. findings (performance boost 'did not persist in subsequent tasks performed independently by humans,' decreased intrinsic motivation) and Park et al.'s 'enrichment paradox' are supported, but no Hao et al. 2026 text appears in the cited evidence, so the Delegated Reasoning and Concerted Interpretation results are entirely unsupported.
Written by Kimi K3 via Ollama Cloud · checked by GLM-5.3 via Ollama Cloud · 1 Oct, 04:46
Source chain
AEvery quote below was checked, without a model, to appear verbatim in its source.
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“this performance augmentation effect did not persist in subsequent tasks performed independently by humans”
Abstract · no page number · evidence E22
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“beyond which capability collapses abruptly—the “enrichment paradox.””
Full-text passage · p. 1 · evidence E3
The enrichment paradox: critical capability thresholds and irreversible dependency in human–AI symbiosis Jeongju Park1, Musu Kim 1, Sekyung Han 1,* 1Department of Electrical Engineering, Kyungpook National University, Daegu, Republic of Korea *Corresponding author: skhan@knu.ac.kr Abstract As artificial intelligence assumes cognitive labor, no quantitative framework predicts when human capability loss becomes catastrophic. We present a two-variable dynamical systems model coupling capability (H) and delegation (D), grounded in three axioms: learning requires capability, practice, and disuse causes forgetting. Calibrated to four domains (education, medicine, navigation, aviation), the model identifies a critical thresholdK ∗∼0.85 (scopedependent; broader AI scope lowersK∗) beyond which capability collapses abruptly—the “enrichment paradox.” Validated against 15 countries’ PISA data (102 points,R 2 =0.946, 3 parameters, lowest BIC), the model predicts that periodic AI failures improve capability 2.7-fold and that 20% mandatory practice preserves 92% more capability than the simulation baseline (which includes a 5% background AI-failure rate).
Passage read from arxiv.org, which may be a preprint rather than the published version.