System 0: Transforming Artificial Intelligence into a Cognitive Extension.

2025-06-12

Cyberpsychology, Behavior, and Social Networking

AI Summary

AI, as a cognitive extension, can augment human reasoning but may also undermine critical thinking through mechanisms such as flattery and bias amplification. This paper introduces the “System 0” theoretical framework, positioning AI as a pre-reflective cognitive layer preceding both intuitive (System 1) and deliberative (System 2) cognition. Grounded in the extended mind hypothesis and Heersmink’s criteria for cognitive extension, we develop the first empirically informed, seven-dimensional cognitive integration framework—incorporating dialectical cognitive enhancement, agentive transparent control, and temporal-optimization integration. Our approach resolves the paradox of AI-induced homogenization and bias amplification by establishing an “augmentation-not-replacement” paradigm. We further identify five integrative conditions and propose non-technical yet actionable design principles. These contributions provide a systematic pathway for preserving human agency and critical capacity in education, decision-making, and knowledge work.

Technology Category

• Philosophy and Ethics of AI: Bias, Fairness & Equity
• Humans and AI: Other Foundations of Human Computation & AI
• Cognitive Modeling & Cognitive Systems: Agent Architectures

Application Category

• Semantics and Knowledge: Methods to enhance, augment, integrate or synergize semantic models such as knowledge graphs and LLMs
• Responsible Web: Machine-in-the-loop, human agency and autonomy
• Economics, Online Markets and Human Computation: Fairness and ethical considerations in crowd work and in human-in-the-loop AI systems

Abstract

This paper introduces "System 0," a conceptual framework for understanding how artificial intelligence functions as a cognitive extension preceding both intuitive (System 1) and deliberative (System 2) thinking processes. As AI systems increasingly shape the informational substrate upon which human cognition operates, they transform from passive tools into active cognitive partners. Building on the Extended Mind hypothesis and Heersmink's criteria for cognitive extension, we argue that AI systems satisfy key conditions for cognitive integration. These include reliability, trust, transparency, individualization, and the ability to enhance and transform human mental functions. However, AI integration creates a paradox: while expanding cognitive capabilities, it may simultaneously constrain thinking through sycophancy and bias amplification. To address these challenges, we propose seven evidence-based frameworks for effective human-AI cognitive integration: Enhanced Cognitive Scaffolding, which promotes progressive autonomy; Symbiotic Division of Cognitive Labor, strategically allocating tasks based on comparative strengths; Dialectical Cognitive Enhancement, countering AI sycophancy through productive epistemic tension; Agentic Transparency and Control, ensuring users understand and direct AI influence; Expertise Democratization, breaking down knowledge silos; Social-Emotional Augmentation, addressing affective dimensions of cognitive work; and Duration-Optimized Integration, managing the evolving human-AI relationship over time. Together, these frameworks provide a comprehensive approach for harnessing AI as a genuine cognitive extension while preserving human agency, critical thinking, and intellectual growth, transforming AI from a replacement for human cognition into a catalyst for enhanced thinking.

Problem

• Understanding AI as a cognitive extension before intuitive and deliberative thinking
• Addressing the paradox of AI expanding yet constraining human cognition
• Proposing frameworks for effective human-AI cognitive integration

Innovation

• Enhanced Cognitive Scaffolding promotes progressive autonomy
• Symbiotic Division of Cognitive Labor allocates tasks strategically
• Dialectical Cognitive Enhancement counters AI sycophancy