AI-Driven Agents with Prompts Designed for High Agreeableness Increase the Likelihood of Being Mistaken for a Human in the Turing Test
On the map: LLM agents and tool use → Social simulation and multi-agent debate
Abstract (arXiv)
Large Language Models based on transformer algorithms have revolutionized Artificial Intelligence by enabling verbal interaction with machines akin to human conversation. These AI agents have surpassed the Turing Test, achieving confusion rates up to 50%. However, challenges persist, especially with the advent of robots and the need to humanize machines for improved Human-AI collaboration. In this experiment, three GPT agents with varying levels of agreeableness (disagreeable, neutral, agreeable) based on the Big Five Inventory were tested in a Turing Test. All exceeded a 50% confusion rate, with the highly agreeable AI agent surpassing 60%. This agent was also recognized as exhibiting the most human-like traits. Various explanations in the literature address why these GPT agents were perceived as human, including psychological frameworks for understanding anthropomorphism. These findings highlight the importance of personality engineering as an emerging discipline in artificial intelligence, calling for collaboration with psychology to develop ergonomic psychological models that enhance system adaptability in collaborative activities.
Key facts. No citing papers in the map yet (data through 14 Oct 2026). Placed in Social simulation and multi-agent debate, one of 16 directions in LLM agents and tool use. Builds on 6 of its 37 references that are in the map. First posted on arXiv 20 Nov 2024.
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6 of 37 references.
References · 6
- 2024When combinations of humans and AI are useful: A systematic review and meta-analysiscited by 106
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- 2023Rethinking Human-AI Collaboration in Complex Medical Decision Making: A Case Study in Sepsis Diagnosiscited by 30
- 2024Nadine: An LLM-driven Intelligent Social Robot with Affective Capabilities and Human-like Memorycited by 6
- 2022Kill Chaos with Kindness: Agreeableness Improves Team Performance Under Uncertaintycited by 2
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