GPT-4 is judged more human than humans in displaced and inverted Turing tests
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Abstract (arXiv)
Everyday AI detection requires differentiating between people and AI in informal, online conversations. In many cases, people will not interact directly with AI systems but instead read conversations between AI systems and other people. We measured how well people and large language models can discriminate using two modified versions of the Turing test: inverted and displaced. GPT-3.5, GPT-4, and displaced human adjudicators judged whether an agent was human or AI on the basis of a Turing test transcript. We found that both AI and displaced human judges were less accurate than interactive interrogators, with below chance accuracy overall. Moreover, all three judged the best-performing GPT-4 witness to be human more often than human witnesses. This suggests that both humans and current LLMs struggle to distinguish between the two when they are not actively interrogating the person, underscoring an urgent need for more accurate tools to detect AI in conversations.
Key facts. Cited by 7 papers in the map (data through 7 Oct 2026). Builds on 14 of its 37 references that are in the map. First posted on arXiv 11 Jul 2024.
Builds on
14 of 37 references.
References · 14
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- 2024People cannot distinguish GPT-4 from a human in a Turing testcited by 46
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- 2023Does GPT-4 pass the Turing test?cited by 37
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Citing papers per year: 2024: 1; 2025: 3; 2026: 3.
7 papers.
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- 2025Assessing LLMs in Art Contexts: Critique Generation and Theory of Mind Evaluationcited by 3
- 2026How Open Must Language Models be to Enable Reliable Scientific Inference?cited by 2
- 2025WHERE and WHICH: Iterative Debate for Biomedical Synthetic Data Augmentationcited by 1
- 2026Human or Machine? A Preliminary Turing Test for Speech-to-Speech Interactioncited by 1
- 2025Conversation Games and a Strategic View of the Turing Testcited by 0
- 2026Identity from the Outside: A Conceptual Framework and Research Program for AI Personality Clonescited by 0
- 2026Identity from the Outside: A Conceptual Framework and Research Program for AI Personality Clones27 Jul 2026
- 2026How Open Must Language Models be to Enable Reliable Scientific Inference?27 Mar 2026
- 2026Human or Machine? A Preliminary Turing Test for Speech-to-Speech Interaction27 Feb 2026
- 2025Assessing LLMs in Art Contexts: Critique Generation and Theory of Mind Evaluation17 Apr 2025
- 2025WHERE and WHICH: Iterative Debate for Biomedical Synthetic Data Augmentation31 Mar 2025
- 2025Conversation Games and a Strategic View of the Turing Test30 Jan 2025
- 2024Lies, Damned Lies, and Distributional Language Statistics: Persuasion and Deception with Large Language Models22 Dec 2024