Social Influence and the Allocation of Scientific Attention in AI Populations
How social signals in scientific databases shape the learning trajectories of autonomous research agents.
AI systems are becoming participants in the evaluation and use of scientific research. They encounter citation counts, download statistics and lists of popular articles developed around human readers, but the collective consequences of these signals for artificial readers remain ...
ArXiv CS.AI
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As AI models begin to influence the trajectory of scientific research, their reliance on existing popularity metrics may create feedback loops that stifle novel discovery. This research highlights the urgent need to understand how algorithmic biases in citation patterns might inadvertently steer the evolution of future technological knowledge.
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