Cognitive Drift and Co-Cognition: How AI Reshapes Human Thought [pdf] (ia801602.us.archive.org)

A new framework detailed in "Cognitive Drift and Co-Cognition" by A. Jacobs explores how AI influences human thought processes, particularly in high-compression information environments. It introduces the concept of Cognitive Drift, which refers to the growing misalignment between a person's internal understanding and the realities represented by their mental models, exacerbated by the rapid changes in information that outstrip the ability to stabilize meaning. This highlights the impact of AI systems as they become integral to human reasoning, leading to iterative, compressed thought patterns that can hamper stability in interpretation and attention. This framework is significant for the AI/ML community as it addresses the structural changes in cognition when interfacing with AI, where thought processes are increasingly mediated and externalized. By defining terms such as Co-Cognition—a recursive loop of human-AI interaction—and Cognitive Compression Styles, it emphasizes the dual nature of AI's role: while it can enhance reasoning and innovation, it also raises concerns about cognitive coherence and continuity. Understanding these dynamics may help researchers and practitioners design AI tools that support cognitive stability, rather than contribute to cognitive overload and drift, thus illuminating the complex interplay between technology and human cognition.