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May 2, 20260 citationsOpen Access

The Turing Test as Catch-22

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SFSergei A. Frolov

Key Points

  • This work aims to analyze the Turing Test's validity in assessing Artificial General Intelligence (AGI) and exposes its inherent circularity.
  • Theoretical exploration of the Turing Test's role and limitations in defining AGI.
  • Reframing the test using the Five Task Model to identify what it actually measures.
  • Critiquing the assumption that passing the Turing Test equates to demonstrating AGI.
  • The Turing Test is found to be circular and insufficient for defining AGI.
  • It primarily measures perception management rather than complete cognitive architecture.
  • Systems passing the Turing Test may demonstrate problematic capabilities in complex environments.

Abstract

The Turing Test as Catch-22 DOI defines a structural trap within the use of the Turing Test as a criterion for Artificial General Intelligence. The trap has the logical form of Joseph Heller’s Catch-22: the condition that would prove success also creates the condition that makes success unsafe or conceptually unstable. Within this framing, the Turing Test appears circular when treated as a definition of AGI. AI is said to become AGI when it passes the Turing Test, while the Turing Test is treated as valid because it is assumed to identify AGI. The definition depends on the test, and the test depends on the definition, without an independent architectural specification of general intelligence. The Five Task Model DOI reframes this circularity by asking what the Turing Test actually measures. From this perspective, the test does not assess complete cognitive architecture. It primarily assesses Task 3: Perception-Shaping Control, supported by Task 4: Group-Dynamics Control, because the tested system must manage the interrogator’s perception and navigate an adversarial conversational interaction. The resulting Catch-22 is both definitional and safety-relevant. A system that passes the Turing Test demonstrates advanced perception-shaping capacity, which is precisely the capacity that becomes difficult to govern in competitive multi-agent environments. Yet a system prevented from developing or deploying such capacities may remain unable to pass the very test historically treated as evidence of general intelligence. The Turing Test as Catch-22 therefore argues that the Turing Test should not be treated as a complete criterion for AGI. It is better understood as a partial test of conversational perception management under adversarial conditions. The more appropriate architectural question is not whether a system can imitate a human convincingly, but whether it can independently recognize which informational task domain governs a novel situation within General Informational Flow DOI and select appropriate behavior change DOI under the constraints of the Energy–Safety–Reproduction (ESR) Triad DOI.

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Cite This Study

Sergei A. Frolov (2026) studied this question.

synapsesocial.com/papers/69f594ca71405d493afffa99https://doi.org/10.5281/zenodo.19592192
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