AI and the Problem of Knowledge Collapse

This paper by Andrew J. Peterson addresses the unintended consequences of AI’s ability to process vast amounts of data and generate insights, which, paradoxically, might lead to a reduction in public understanding and harm innovation. It introduces the concept of ‘knowledge collapse’ where reliance on AI for information can result in a convergence towards generalised, less varied perspectives. This risk could impact the diversity of human understanding and cultural richness. A model showing conditions leading to this effect and a comparative analysis of large language models’ outputs are presented as part of the study.

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