Theoretical analysis reveals scientific coordination challenges under AI-driven knowledge abundance, highlighting the enduring institutional role of journals for verification and curation.
Artificial intelligence can lower the cost of producing plausible research outputs without proportionally lowering the cost of verification and accumulation. This position paper defines the Knowledge Abundance Paradox, develops a quality-adjusted lifecycle framework for comparing paper-centered coordination with a DGP-hybrid treatment inherited from DGP Multiverse Science, separates matched-task processing effects from total institutional effects, and specifies an adoption-equilibrium gate. Papers remain narrative interfaces and journals remain institutions of curation and judgment.
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Xiaonan Fu (2026) studied this question.
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