Paper page - Understanding Cognition-Induced Risks in Agentic AI Systems

Source: https://huggingface.co/papers/2608.15304

Abstract

Agentic systems built on large language models pose escalating risks to human agency and autonomy across physical, social, and self-referential cognitive levels, requiring targeted mitigation strategies.

Frontieragentic systemspowered bylarge language models(LLMs) exhibit human-like patterns of cognition. As these systems become deeply integrated across different domains, their cognitive engagement raises critical concerns for human society that remain insufficiently studied. To address this gap, we systematically analyze risks induced by expanding cognitive capabilities, following a three-level framework defined by theircognitive scope, from physical cognition to social cognition, and finally toself-referential cognition. We study their potential risks to human agency, autonomy, and control capability, corresponding to each cognitive level. We finally propose strategies to mitigate these risks and enhance the controllability ofagentic AIsystems, ensuring their long-term safe development.

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