Chess and Artificial Intelligence: A Cognitive Laboratory and an Ethical Challenge
Chess and Artificial Intelligence: A Cognitive Laboratory and an Ethical Challenge

Summary/Abstract: Chess has long served as a privileged model for studying human reasoning, offering insights into memory, strategy, and decision-making (the sport of the mind). From Alfred Binet’s pioneering psychological studies to Alan Turing’s exploration of machine intelligence, chess has mirrored humanity’s quest to understand cognition. The historic defeat of Garry Kasparov by IBM’s Deep Blue in 1997 marked a turning point, demonstrating that brute computational force could outmatch human intuition. However, it was with DeepMind’s AlphaZero (2017) that a profound paradigm shift occurred: a system capable of autonomously learning chess strategy, without reliance on human databases, achieving a style both dynamic and creative. AlphaZero’s success raises critical epistemological and ethical questions. It challenges traditional concepts of understanding, showing that expert-level competence can emerge without consciousness. Ethically, the evolution from human-machine rivalry to collaboration – epitomized by freestyle chess – suggests that synergy between humans and AI yields superior outcomes. Nevertheless, issues such as explainability, responsibility, and the preservation of human dignity remain pressing concerns, especially as AI systems extend into domains like medicine, law, and scientific research. This study argues that chess continues to serve as a prototype for broader societal reflections: how we define intelligence, how we govern technological power, and how we ensure that AI remains a tool for amplifying, rather than diminishing, human creativity and ethical responsibility. In the evolving landscape of AI, the greatest challenge is not technological, but moral: shaping a future where human values remain at the center of innovation.

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