🤖 AI Summary
This study re-examines Turing’s 1948 chess-based imitation game, investigating how constraining human players to weak chess skill levels renders their behavior more machine-like, thereby enhancing the comparability of human and artificial intelligence. Through historical textual analysis, conceptual reconstruction, and cognitive modeling, the work systematically integrates Turing’s early insights on fault tolerance, exclusion of physical interference, the adjudicator’s role, and the notion of “intelligence as search.” Innovatively adopting a “human-approaching-machine” perspective, the paper extends the theoretical framework of the imitation game and underscores Turing’s foundational contribution to AI evaluation paradigms, opening new avenues for understanding the machine-like characteristics of human intelligence in task-specific contexts.
📝 Abstract
This paper examines Turing's 1948 report, "Intelligent Machinery", as an important conceptual source for the later imitation games. Its first contribution is to identify and integrate the design concepts underlying the 1948 chess-based imitation game: the possibility that intelligent machines may make mistakes, the exclusion of irrelevant physical features, the role of the human judge, and Turing's claim that intellectual activity consists mainly of search. The paper's second contribution is to argue that restricting the human contestant to a rather poor chess player increases the role of intellectual search and makes human behaviour more comparable to machine behaviour. This interpretation presents the 1948 game as a human-approximates-machine game and suggests that the imitation game framework can be used not only to ask whether machines imitate humans, but also to examine when human intelligence becomes machine-like under specific task constraints.