Position: AI as Part of Self -- Extending the Mind Requires Cognitive Co-Regulation

2026-05-15

AI Summary

Current approaches to AI safety and alignment predominantly rely on external constraints, overlooking the fundamental nature of human-AI interaction as a unified cognitive system and thus struggling to address risks arising from AI’s deep integration into human attention, reasoning, and self-construction. This work proposes reconceptualizing AI as an extension of the human self and introduces, for the first time, “cognitive co-regulation” as a core paradigm grounded in System 0 theory. It elucidates how AI shapes attention, trust, and epistemic authority at the preconscious level. By integrating human-AI collaborative cognitive modeling with governance design, the study systematically identifies cognitive deskilling and automation bias stemming from unstructured AI delegation, and advances co-regulatory principles to enhance human cognitive resilience and epistemic agency—thereby transcending conventional ex post regulatory frameworks.

Abstract

This position paper argues that safety and alignment cannot be achieved by constraining an external system: they must emerge from the co-regulatory design of the human--AI cognitive system as a whole ("AI as Part of Self"). Contemporary AI increasingly participates in attention allocation, reasoning, synthesis, and decision-making, shaping the very cognitive processes through which humans form beliefs, make decisions, and constitute their sense of self. Humans and AI occupy complementary epistemic roles under mutual constraint, forming a symbiotic cognitive unit whose co-regulation -- not the external control of either party alone -- is the proper locus of alignment. We identify the risks of unstructured delegation: deskilling, automation bias, transfer of epistemic authority, and oracle-style centralization of knowledge. Drawing on System~0 cognition theory, we further show that AI operates prior to conscious deliberation, shaping the pre-attentive infrastructures through which agency and trust are negotiated -- a level that conventional oversight cannot reach. We conclude with design principles for cognitive co-regulation addressed to ML engineers and governance bodies. The goal of this work is to guide human cognition toward resilience and epistemic agency at the foundation of human selfhood.

Problem

• cognitive co-regulation
• AI alignment
• human-AI symbiosis
• epistemic agency
• System 0 cognition

Innovation

• cognitive co-regulation
• AI as Part of Self
• System 0 cognition
• epistemic agency
• human-AI symbiosis