Evaluating In Silico Creativity: An Expert Review of AI Chess Compositions

Vivek Veeriah, Federico Barbero, Marcus Chiam, Xidong Feng, Michael Dennis, Ryan Pachauri, Thomas Tumiel, Johan Obando Ceron, Jiaxin Shi, Shaobo Hou, Satinder P. Singh, Nenad Tomasev, Tom Zahavy

Advances in Neural Information Processing Systems 38 Creative AI pre-proceedings (NeurIPS 2025) Creative AI

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The rapid advancement of Generative AI has raised significant questions regarding its ability to produce creative and novel outputs. Our recent work investigates this question within the domain of chess puzzles and presents an AI system designed to generate puzzles characterized by aesthetic appeal, novelty, counter-intuitive and unique solutions. We briefly outline our methodology, with a detailed discussion in the technical paper. To assess our system's creativity, we presented a curated booklet of AI-generated puzzles to three world-renowned experts: International Master for chess compositions Amatzia Avni, Grandmaster Jonathan Levitt, and Grandmaster Matthew Sadler. All three are noted authors on chess aesthetics and the evolving role of computers in the game. They were asked to select their favorites and explain what made them appealing, considering qualities such as their creativity, level of challenge, or aesthetic design. This paper compiles these selected puzzles, integrating expert analysis to explore the elements that render them counter-intuitive and beautiful.