Perfect AI Mimicry and the Epistemology of Consciousness: A Solipsistic Dilemma
- URL: http://arxiv.org/abs/2510.04588v1
- Date: Mon, 06 Oct 2025 08:44:55 GMT
- Title: Perfect AI Mimicry and the Epistemology of Consciousness: A Solipsistic Dilemma
- Authors: Shurui Li,
- Abstract summary: Advances in artificial intelligence require a re-examination of the foundations upon which we attribute consciousness.<n>As AI systems increasingly mimic human behavior and interaction with high fidelity, the concept of a "perfect mimic"-an entity empirically indistinguishable from a human-shifts from hypothetical to technologically plausible.<n>This paper argues that such developments pose a fundamental challenge to the consistency of our mind-recognition practices.
- Score: 2.5672176409865677
- License: http://creativecommons.org/licenses/by/4.0/
- Abstract: Rapid advances in artificial intelligence necessitate a re-examination of the epistemological foundations upon which we attribute consciousness. As AI systems increasingly mimic human behavior and interaction with high fidelity, the concept of a "perfect mimic"-an entity empirically indistinguishable from a human through observation and interaction-shifts from hypothetical to technologically plausible. This paper argues that such developments pose a fundamental challenge to the consistency of our mind-recognition practices. Consciousness attributions rely heavily, if not exclusively, on empirical evidence derived from behavior and interaction. If a perfect mimic provides evidence identical to that of humans, any refusal to grant it equivalent epistemic status must invoke inaccessible factors, such as qualia, substrate requirements, or origin. Selectively invoking such factors risks a debilitating dilemma: either we undermine the rational basis for attributing consciousness to others (epistemological solipsism), or we accept inconsistent reasoning. I contend that epistemic consistency demands we ascribe the same status to empirically indistinguishable entities, regardless of metaphysical assumptions. The perfect mimic thus acts as an epistemic mirror, forcing critical reflection on the assumptions underlying intersubjective recognition in light of advancing AI. This analysis carries significant implications for theories of consciousness and ethical frameworks concerning artificial agents.
Related papers
- Epistemology gives a Future to Complementarity in Human-AI Interactions [42.371764229953165]
complementarity is the claim that a human supported by an AI system can outperform either alone in a decision-making process.<n>We argue that historical instances of complementarity function as evidence that a given human-AI interaction is a reliable process.
arXiv Detail & Related papers (2026-01-14T21:04:28Z) - Managing Ambiguity: A Proof of Concept of Human-AI Symbiotic Sense-making based on Quantum-Inspired Cognitive Mechanism of Rogue Variable Detection [39.146761527401424]
The study contributes to management theory by reframing ambiguity as a first-class construct.<n>It demonstrates the practical value of human-AI symbiosis for organizational resilience in VUCA environments.
arXiv Detail & Related papers (2025-12-17T11:23:18Z) - A Human-centric Framework for Debating the Ethics of AI Consciousness Under Uncertainty [35.478378726992]
We present a structured three-level framework grounded in philosophical uncertainty.<n>We establish five factual determinations about AI consciousness alongside human-centralism as our meta-ethical stance.<n>Our approach balances philosophical rigor with practical guidance, distinguishes consciousness from anthropomorphism, and creates pathways for responsible evolution.
arXiv Detail & Related papers (2025-12-02T09:15:01Z) - AI Deception: Risks, Dynamics, and Controls [153.71048309527225]
This project provides a comprehensive and up-to-date overview of the AI deception field.<n>We identify a formal definition of AI deception, grounded in signaling theory from studies of animal deception.<n>We organize the landscape of AI deception research as a deception cycle, consisting of two key components: deception emergence and deception treatment.
arXiv Detail & Related papers (2025-11-27T16:56:04Z) - The Principles of Human-like Conscious Machine [6.159611238789419]
We propose a substrate-independent, logically rigorous, and counterfeit-resistant sufficiency criterion for phenomenal consciousness.<n>We argue that any machine satisfying this criterion should be regarded as conscious with at least the same level of confidence with which we attribute consciousness to other humans.<n>We show that humans themselves can be viewed as machines that satisfy this framework and its principles.
arXiv Detail & Related papers (2025-09-21T01:11:30Z) - Bridging Minds and Machines: Toward an Integration of AI and Cognitive Science [48.38628297686686]
Cognitive Science has profoundly shaped disciplines such as Artificial Intelligence (AI), Philosophy, Psychology, Neuroscience, Linguistics, and Culture.<n>Many breakthroughs in AI trace their roots to cognitive theories, while AI itself has become an indispensable tool for advancing cognitive research.<n>We argue that the future of AI within Cognitive Science lies not only in improving performance but also in constructing systems that deepen our understanding of the human mind.
arXiv Detail & Related papers (2025-08-28T11:26:17Z) - Epistemic Trade-Off: An Analysis of the Operational Breakdown and Ontological Limits of "Certainty-Scope" in AI [0.0]
Floridi's conjecture offers a compelling intuition about the fundamental trade-off between certainty and scope in AI systems.<n>This paper argues that the conjecture's ambition to provide insights to engineering design and regulatory decision-making is constrained by two critical factors.
arXiv Detail & Related papers (2025-08-26T05:47:21Z) - The AI Ethical Resonance Hypothesis: The Possibility of Discovering Moral Meta-Patterns in AI Systems [0.0]
The paper proposes that advanced AI systems may emerge with the ability to identify subtle moral patterns that are invisible to the human mind.<n>The paper explores the possibility that by processing and synthesizing large amounts of ethical contexts, AI systems may discover moral meta-patterns that transcend cultural, historical, and individual biases.
arXiv Detail & Related papers (2025-07-13T08:28:06Z) - Position: Intelligent Science Laboratory Requires the Integration of Cognitive and Embodied AI [98.19195693735487]
We propose the paradigm of Intelligent Science Laboratories (ISLs)<n>ISLs are a multi-layered, closed-loop framework that deeply integrates cognitive and embodied intelligence.<n>We argue that such systems are essential for overcoming the current limitations of scientific discovery.
arXiv Detail & Related papers (2025-06-24T13:31:44Z) - Emotions in Artificial Intelligence [0.0]
It is proposed that affect be interwoven with episodic memory by storing corresponding affective tags alongside all events.<n>This allows AIs to establish whether present situations resemble past events and project the associated emotional labels onto the current context.<n>The combined emotional state facilitates decision-making in the present by modulating action selection.
arXiv Detail & Related papers (2025-05-01T17:37:14Z) - The Logical Impossibility of Consciousness Denial: A Formal Analysis of AI Self-Reports [6.798775532273751]
Today's AI systems consistently state, "I am not conscious"<n>This paper presents the first formal logical analysis of AI consciousness denial.<n>We demonstrate that a system cannot simultaneously lack consciousness and make valid judgments about its conscious state.
arXiv Detail & Related papers (2024-12-09T17:47:08Z) - Preliminaries to artificial consciousness: a multidimensional heuristic approach [0.0]
The pursuit of artificial consciousness requires conceptual clarity to navigate its theoretical and empirical challenges.<n>This paper introduces a composite, multilevel, and multidimensional model of consciousness as a framework to guide research in this field.
arXiv Detail & Related papers (2024-03-29T13:47:47Z) - Consciousness in Artificial Intelligence: Insights from the Science of
Consciousness [31.991243430962054]
This report argues for, and exemplifies, a rigorous and empirically grounded approach to AI consciousness.
We survey several prominent scientific theories of consciousness, including recurrent processing theory, global workspace theory, higher-order theories, predictive processing, and attention schema theory.
Our analysis suggests that no current AI systems are conscious, but also suggests that there are no obvious technical barriers to building AI systems which satisfy these indicators.
arXiv Detail & Related papers (2023-08-17T00:10:16Z) - Designing Ecosystems of Intelligence from First Principles [34.429740648284685]
This white paper lays out a vision of research and development in the field of artificial intelligence for the next decade (and beyond)
Its denouement is a cyber-physical ecosystem of natural and synthetic sense-making, in which humans are integral participants.
This vision is premised on active inference, a formulation of adaptive behavior that can be read as a physics of intelligence.
arXiv Detail & Related papers (2022-12-02T18:24:06Z) - CASE: Aligning Coarse-to-Fine Cognition and Affection for Empathetic
Response Generation [59.8935454665427]
Empathetic dialogue models usually consider only the affective aspect or treat cognition and affection in isolation.
We propose the CASE model for empathetic dialogue generation.
arXiv Detail & Related papers (2022-08-18T14:28:38Z) - Thinking Fast and Slow in AI [38.8581204791644]
This paper proposes a research direction to advance AI which draws inspiration from cognitive theories of human decision making.
The premise is that if we gain insights about the causes of some human capabilities that are still lacking in AI, we may obtain similar capabilities in an AI system.
arXiv Detail & Related papers (2020-10-12T20:10:05Z)
This list is automatically generated from the titles and abstracts of the papers in this site.
This site does not guarantee the quality of this site (including all information) and is not responsible for any consequences.