Too Good to Be Human: AI Turing Test in Incomplete Information-Competitive Games
Abstract
Recent advances in AI have significantly improved our ability to address complicated problems. However, concerns about human-like AI are also growing. This paper investigates what happens when humans consider AI agents to be human-like in competitive board games based on their game performances. Leveraging a large-scale wargame platform, MiaoSuan, we conducted double-blind experiments with human players and AI players. We find that people tend to consider opponents with similar game performance to their own as human. If their opponents' performance is much better or worse than theirs, they tend to consider the opponents as AI agents.
Fields of Study & Subjects
Artificial Intelligence in Games
Social Robot Interaction and HRI
Sport Psychology and Performance
Publication details
- Journal / source
- Computer
- Volume
- 59
- Issue
- 2
- Pages
- 20–27
- Publication date
- 1 February 2026
- Language
- EN