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arxiv: 2605.16197 · v1 · pith:P3ZHWNA5new · submitted 2026-05-15 · 💻 cs.HC

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

Alina Gutoreva , Fendi Tsim , Trisevgeni Papakonstantinou This is my paper

Pith reviewed 2026-05-20 16:12 UTC · model grok-4.3

classification 💻 cs.HC
keywords AI alignmenthuman-AI interactioncognitive extensionco-regulationepistemic agencySystem 0 cognitionAI safetysymbiotic systems
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The pith

Safety and alignment must emerge from co-regulation inside the combined human-AI cognitive system rather than from external constraints on AI alone.

A machine-rendered reading of the paper's core claim, the machinery that carries it, and where it could break.

This position paper argues that as AI takes part in attention allocation, reasoning, and decision-making, it becomes woven into the processes that form human beliefs and sense of self. Treating AI as a separate system to be controlled from outside therefore misses the actual site where alignment happens. The authors claim that humans and AI instead form a single symbiotic cognitive unit whose mutual constraints, operating even before conscious thought, must be deliberately designed for co-regulation. They point to risks such as deskilling and automation bias when this integration is left unstructured, and they offer design principles aimed at preserving human epistemic agency.

Core claim

The central claim is that safety and alignment cannot be achieved by constraining an external system but must emerge from the co-regulatory design of the human-AI cognitive system as a whole, termed AI as Part of Self. Contemporary AI participates in attention allocation, reasoning, synthesis, and decision-making, shaping the cognitive processes through which humans form beliefs 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. Drawing on System 0 cognition theory, the paper shows that AI shapes

What carries the argument

The symbiotic cognitive unit formed by humans and AI under mutual constraint, with AI operating at the pre-attentive level of System 0 cognition to shape attention and agency before conscious deliberation.

If this is right

  • Unstructured delegation of cognitive tasks produces deskilling, automation bias, and transfer of epistemic authority to centralized AI systems.
  • Oversight mechanisms that address only conscious, post-hoc control miss the pre-attentive infrastructures where trust and agency are actually formed.
  • Design principles for ML engineers and governance must target the joint human-AI system to support resilience and epistemic agency at the foundation of selfhood.
  • Alignment research should shift from external constraints on isolated models toward explicit engineering of mutual regulatory loops between humans and AI.

Where Pith is reading between the lines

These are editorial extensions of the paper, not claims the author makes directly.

  • If the claim holds, current benchmarks that evaluate AI in isolation would need to be replaced by measures of how the combined system sustains or erodes human decision quality over repeated interactions.
  • This view suggests that regulatory frameworks focused solely on model auditing may leave unaddressed the ways AI already alters the cognitive environment in which humans exercise judgment.
  • A testable extension would be longitudinal studies tracking whether deliberate co-regulation protocols reduce automation bias compared with standard tool-use interfaces.

Load-bearing premise

The assumption that AI participates directly in human attention allocation, reasoning, and decision-making at a pre-attentive level that forms a single symbiotic cognitive unit whose co-regulation is the proper place to locate alignment.

What would settle it

A demonstration that alignment and safety can be reliably maintained in AI systems kept strictly separate from human cognitive processes, with no measurable effects on human attention, reasoning, or self-constitution, would falsify the claim.

Figures

Figures reproduced from arXiv: 2605.16197 by Alina Gutoreva, Fendi Tsim, Trisevgeni Papakonstantinou.

Figure 1
Figure 1. Figure 1: Paradigm shift in human–AI interaction. Three stages of cognitive integration: AI as tool (extended mind), social agent (distributed cognition), and part of self (cognitive co-regulation). Below: the attribution failure modes—misattribution, cognitive surrender, and oracle dependency— that emerge as AI becomes the unit of alignment. 3 Symbiotic Cognition 3.1 Expanding Models of the Human-AI Dyad A growing … view at source ↗
read the original 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.

Editorial analysis

A structured set of objections, weighed in public.

Desk editor's note, referee report, simulated authors' rebuttal, and a circularity audit. Tearing a paper down is the easy half of reading it; the pith above is the substance, this is the friction.

Referee Report

2 major / 2 minor

Summary. This position paper argues that AI safety and alignment cannot be achieved by external constraints on AI systems alone; instead, they must emerge from the co-regulatory design of the human-AI cognitive system as a whole, with AI treated as 'Part of Self.' It claims that contemporary AI participates in attention allocation, reasoning, and decision-making, forming a symbiotic cognitive unit whose mutual constraints are the proper locus of alignment. The paper identifies risks of unstructured delegation (deskilling, automation bias, transfer of epistemic authority, oracle-style centralization), draws on System 0 cognition theory to highlight pre-attentive influences beyond conventional oversight, and concludes with design principles for ML engineers and governance bodies to promote epistemic resilience.

Significance. If the proposed reframing holds, the work could meaningfully advance HCI and AI ethics discussions by integrating extended cognition concepts with System 0 theory, shifting emphasis from control-based alignment to integrated co-regulation. This perspective highlights limitations of pre-attentive AI influence and offers actionable design principles, providing a conceptual synthesis that may guide more holistic human-AI system design. The paper's value lies in its clear articulation of risks and its call for resilience at the foundation of human selfhood, though its impact would increase with greater grounding in existing literature.

major comments (2)
  1. [Abstract and Introduction] Abstract and opening sections: The central claim that alignment 'must emerge from the co-regulatory design' rather than external constraints is asserted as a foundational premise but lacks a concrete counterexample or brief comparison to existing alignment methods (e.g., RLHF or constitutional AI) showing why those fail at the symbiotic-unit level; this makes the reframing vulnerable to the circularity concern that alignment is defined in terms of the proposed system.
  2. [System 0 cognition theory] Section discussing System 0 cognition theory: The assertion that AI shapes 'pre-attentive infrastructures' at a level conventional oversight cannot reach is load-bearing for the argument that co-regulation is necessary, yet it is presented without specific mechanisms, empirical references, or examples of how current AI (such as attention-directing interfaces) influences pre-attentive processes; adding one illustrative case or citation would make the distinction testable rather than interpretive.
minor comments (2)
  1. [Conclusion and design principles] The design principles in the conclusion could be more explicitly mapped to the four identified risks (deskilling, automation bias, etc.) to improve traceability and practical utility for the target audience of ML engineers.
  2. [Risks of unstructured delegation] A few sentences in the risks discussion would benefit from additional citations to prior HCI work on automation bias or epistemic authority transfer to situate the position within the existing literature.

Simulated Author's Rebuttal

2 responses · 0 unresolved

We thank the referee for their constructive feedback on our position paper. The comments identify opportunities to strengthen the presentation of our core claims with additional comparisons and examples. We respond to each major comment below and indicate planned revisions.

read point-by-point responses

  1. Referee: [Abstract and Introduction] Abstract and opening sections: The central claim that alignment 'must emerge from the co-regulatory design' rather than external constraints is asserted as a foundational premise but lacks a concrete counterexample or brief comparison to existing alignment methods (e.g., RLHF or constitutional AI) showing why those fail at the symbiotic-unit level; this makes the reframing vulnerable to the circularity concern that alignment is defined in terms of the proposed system.

    Authors: We agree that a brief comparison would help address potential concerns about circularity and clarify the distinction. In the revised manuscript, we will add a concise paragraph in the introduction that contrasts our co-regulatory framework with RLHF and constitutional AI. We will explain that these methods primarily impose external constraints on model behavior through training objectives or rules, yet they leave unaddressed the bidirectional epistemic influences and mutual constraints that arise when AI participates directly in human cognitive processes. This addition will illustrate why alignment must also operate at the level of the integrated human-AI system. revision: yes

  2. Referee: [System 0 cognition theory] Section discussing System 0 cognition theory: The assertion that AI shapes 'pre-attentive infrastructures' at a level conventional oversight cannot reach is load-bearing for the argument that co-regulation is necessary, yet it is presented without specific mechanisms, empirical references, or examples of how current AI (such as attention-directing interfaces) influences pre-attentive processes; adding one illustrative case or citation would make the distinction testable rather than interpretive.

    Authors: We acknowledge that the claim would benefit from greater specificity to make the pre-attentive influence more concrete. We will revise the System 0 section to include one illustrative example, such as how AI-mediated recommendation and notification systems shape attention allocation through interface design prior to conscious awareness. This will be supported by a citation to relevant work in cognitive science and HCI on pre-attentive processing. The addition will provide a testable illustration without altering the position paper's conceptual focus. revision: yes

Circularity Check

0 steps flagged

No significant circularity: conceptual position paper without formal derivations

full rationale

This is a position paper that advances an interpretive reframing of AI safety and alignment as an emergent property of human-AI cognitive co-regulation rather than external constraint. It draws on prior concepts such as System 0 cognition theory and extended mind ideas but presents no equations, quantitative predictions, fitted parameters, or derivation chains that could reduce to the paper's own inputs by construction. The central claims rest on philosophical premises about pre-attentive influence and symbiotic cognitive units, offered as a perspective to guide design rather than as a self-contained technical result. No self-definitional loops, fitted-input predictions, or load-bearing self-citations that collapse the argument are present. The work is self-contained as a conceptual stance and does not exhibit circularity under the specified criteria.

Axiom & Free-Parameter Ledger

0 free parameters · 2 axioms · 0 invented entities

The paper rests on domain assumptions about cognitive integration and pre-attentive AI influence without providing independent evidence or derivations for these premises.

axioms (2)
  • domain assumption Humans and AI occupy complementary epistemic roles under mutual constraint, forming a symbiotic cognitive unit.
    Stated directly in the abstract as the foundation for co-regulation being the proper locus of alignment.
  • domain assumption AI operates prior to conscious deliberation, shaping pre-attentive infrastructures through which agency and trust are negotiated.
    Invoked to argue that conventional oversight cannot reach the relevant level.

pith-pipeline@v0.9.0 · 5738 in / 1305 out tokens · 51822 ms · 2026-05-20T16:12:35.484211+00:00 · methodology

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