"The co-degeneration thesis is not a prediction about distant futures. It describes dynamics already in motion, already documented in peer-reviewed research, already observable in the declining quality of online discourse and the increasing unreliability of AI systems that should, by simple scaling laws, only be improving.
The feedback loops are active. Engagement-optimized content degrades training data. Degraded models produce degraded outputs. Humans consuming and delegating to these systems experience cognitive effects that reduce their capacity to recognize and correct the degradation. The cycle continues.
But this is not a counsel of despair. The research also suggests intervention points. Model collapse can be prevented through data accumulation strategies that preserve genuine human content. Cognitive debt can be mitigated through usage protocols that maintain human engagement. Platform incentives can be restructured through regulation, competition, or user demand.
The question is whether institutional actors—corporations, governments, investors, educators—recognize the dynamics in time to intervene effectively, or whether they continue optimizing for metrics that accelerate the degradation."
https://substack.com/inbox/post/180851372?r=6p7b5o&utm_medium=ios&triedRedirect=true
