Do we know less because of AI? The problem of the knowledge collapse
Manage episode 441689651 series 3153807
In this episode, we delve into the critical issue of "Knowledge Loss" as highlighted in the insightful article "AI and the Problem of Knowledge Loss." The discussion will focus on the potential consequences of deploying artificial intelligence, particularly large language models (LLMs), in knowledge creation. Although AI can process vast amounts of data and generate new insights, its widespread use may lead to a phenomenon the authors describe as "knowledge loss." This occurs because LLMs, trained on enormous datasets, tend to produce outcomes centered on the most likely responses, overlooking niche knowledge and unconventional perspectives.
We'll explore the societal impacts of an overreliance on AI-generated content, which could narrow human knowledge and decrease innovation, much like the "streetlight effect" where people only search where it's easiest. The episode also addresses human agency in countering knowledge loss by actively seeking diverse information sources and valuing niche knowledge, despite potential higher costs.
Join us as we navigate the complexities of AI integration and its implications for preserving the diversity and richness of human knowledge.
This podcast is based on the research paper by Peterson, A.J. (2024) Ai and the problem of knowledge collapse, arXiv.org. Available at: https://arxiv.org/abs/2404.03502 (available here)
Disclaimer: This podcast is generated by Roger Basler de Roca (contact) by the use of AI. The voices are artificially generated and the discussion is based on public research data. I do not claim any ownership of the presented material as it is for education purpose only.
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