When Should AI Follow? Task Structure and Joint Adaptation by Human and AI Agents
3.20T1 sourcearXiv cs.MA
Source record
Published by arXiv cs.MA (T1 source). The original is at https://arxiv.org/abs/2504.20903.
Pipeline notes
The summary and note below are generated by the signal pipeline — they are Beyond Desk’s reading, not quotations from the source.
SummaryA computational model of sequential adaptation between human and AI agents that differ only in memory regime (recency-weighted vs uniform). Varying task scope and coupling parameters, it finds joint performance is maximized when scale-free algorithmic adaptation follows a high-performing human, not under default 'AI-first' design.
Why it mattersInverts the prevailing AI-first assumption in human-AI collaboration, offering a structural contingency logic for when algorithmic adaptation should follow rather than lead human judgment.
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