Research shows AI-generated content is narrower than what humans create alone. If AI trains on AI content, the narrowing compounds over time.
This is what researchers call knowledge collapse — the gradual loss of specialist, niche, and unorthodox knowledge from our collective pool.
New post — third in our series on AI and human cognition: https://www.ctnet.co.uk/ai-knowledge-collapse-risk/
#AI #KnowledgeManagement #PKM #ArtificialIntelligence #KnowledgeCollapse
AI, Human Cognition and Knowledge Collapse
Daron Acemoglu, Dingwen Kong & Asuman Ozdaglar
"We study how generative AI, and in particular agentic AI, shapes human learning incentives and the long-run evolution of society’s information ecosystem. We build a dynamic model of learning and decision-making in which successful decisions require combining shared, community-level general knowledge with individual-level, context-specific knowledge; these two inputs are complements. Learning exhibits economies of scope: costly human effort jointly produces a private signal about their own context and a “thin” public signal that accumulates into the community’s stock of general knowledge, generating a learning externality. Agentic AI delivers context-specific recommendations that substitute for human effort. By contrast, a richer stock of general knowledge complements human effort by raising its marginal return. The model highlights a sharp dynamic tension: while agentic AI can improve contemporaneous decision quality, it can also erode learning incentives that sustain long-run collective knowledge. When human effort is sufficiently elastic and agentic recommendations exceed an accuracy threshold, the economy can tip into a knowledge-collapse steady state in which general knowledge vanishes ultimately, despite high-quality personalized advice. Welfare is generally non-monotone in agentic accuracy, implying an interior, welfare-maximizing level of agentic precision and motivating information-design regulations. In contrast, greater aggregation capacity for general knowledge—meaning more effective sharing and pooling of human-generated general knowledge—unambiguously raises welfare and increases resilience to knowledge collapse."
"The internet, as the primary source of knowledge for AI models, becomes recursively influenced by the very outputs those models generate. With each training cycle, new models increasingly rely on AI-generated content. This risks creating a feedback loop where dominant ideas are continuously amplified while long-tail or niche knowledge fades from view."
A thoughtful piece of genAI criticism by Deepak Varuvel Dennison, focusing on the loss of indigineous or otherwise diverse or non-standard knowledge. A Long Read in today's Guardian, originally published in Aeon.
https://aeon.co/essays/generative-ai-has-access-to-a-small-slice-of-human-knowledge
https://www.theguardian.com/news/2025/nov/18/what-ai-doesnt-know-global-knowledge-collapse
#noAI #StopTheAICorruption #IndiginousKnowledge #DeepakVaruvelDennison #KnowledgeCollapse #AndrewPeterson
CTNET
Miguel Afonso Caetano
the roamer