Noosemia: toward a Cognitive and Phenomenological Account of Intentionality Attribution in Human-Generative AI Interaction

2025-08-04

AI Summary

This study identifies and formalizes “Noosemia”—a cognitive phenomenon wherein users unconsciously ascribe intentionality, subjectivity, and interiority to generative AI during interaction. To address this, the paper introduces the first formal definitions of Noosemia and its inverse, a-Noosemia, grounded in an interdisciplinary framework integrating linguistic holism, contextual cognitive field theory, and phenomenological analysis. Distinguishing Noosemia from related constructs—such as Dennett’s intentional stance, animism, and the uncanny valley—the authors elucidate its dual psychotechnical origins: (1) language-based representational affordances that privilege agentive interpretation, (2) model opacity reinforcing anthropomorphic inference, and (3) interactive context amplifying subjective immersion. Empirical and theoretical analysis reveals how these factors jointly engender a “quasi-agential illusion.” The work provides foundational conceptual tools and methodological guidance for human–AI interface design, ethical assessment of agency attribution, and future empirical investigation into user cognition in AI-mediated contexts. (149 words)

Technology Category

• Cognitive Modeling & Cognitive Systems: Social Cognition And Interaction
• Humans and AI: Intelligent User Interfaces
• Philosophy and Ethics of AI: AI & Epistemology

Application Category

• Semantics and Knowledge: Data modeling to support human-machine intelligence, including LLMs agents, intelligent system behavior, explanations, and user-friendly interactions
• Social Networks and Social Media: Generative AI / large language models and their impact on social systems
• Responsible Web: Machine-in-the-loop, human agency and autonomy

Abstract

This paper introduces and formalizes Noosemia, a novel cognitive-phenomenological phenomenon emerging from human interaction with generative AI systems, particularly those enabling dialogic or multimodal exchanges. We propose a multidisciplinary framework to explain how, under certain conditions, users attribute intentionality, agency, and even interiority to these systems - a process grounded not in physical resemblance, but in linguistic performance, epistemic opacity, and emergent technological complexity. By linking an LLM declination of meaning holism to our technical notion of the LLM Contextual Cognitive Field, we clarify how LLMs construct meaning relationally and how coherence and a simulacrum of agency arise at the human-AI interface. The analysis situates noosemia alongside pareidolia, animism, the intentional stance and the uncanny valley, distinguishing its unique characteristics. We also introduce a-noosemia to describe the phenomenological withdrawal of such projections. The paper concludes with reflections on the broader philosophical, epistemological, and social implications of noosemic dynamics and directions for future research.

Problem

• Understanding intentionality attribution in human-AI interaction
• Exploring cognitive-phenomenological effects of generative AI systems
• Analyzing linguistic and epistemic factors in agency perception

Innovation

• Multidisciplinary framework for intentionality attribution
• LLM Contextual Cognitive Field for relational meaning
• Phenomenological withdrawal concept a-noosemia introduced