Independent Researcher, London, United Kingdom
Review Article
The Amplification and Perpetuation of AI-Derived Biases Through Automation Dependency: A Framework for Understanding the Long-Term Cognitive and Social Implications of LLM Over-Reliance
Author(s): Christopher Cleverly*
This research introduces a framework to elucidate how automation bias in Large Language Models (LLMs) amplifies biases through human over-reliance, leading to critical thinking atrophy and the propagation of biases into human cognition and social systems. Automation bias, defined as the tendency to excessively trust AI outputs while ignoring contradictory evidence or personal judgment, drives a three-phase cycle: (1) initial dependency development, fueled by perceived AI efficiency; (2) critical thinking atrophy via cognitive offloading; and (3) bias internalization and propagation, where AI biases are inherited and reproduced in human decisions, even without AI support. Drawing on evidence such as the impact of AI on 40% of global jobs and cognitive offloading in education, we challenge the notion that technical fixes alone can mitigate these effects. We propose Wisdom as a Service (.. View More»
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