Rethinking intelligence: A critical examination of the concept of “artificial intelligence”
Abstract
This article critically examines the use of the term “artificial intelligence” in education and argues that its widespread use can create conceptual and pedagogical confusion. Drawing on theoretical work by Pierre Lévy, Hubert Dreyfus, Sherry Turkle, and Kate Crawford, the article argues that systems currently described as “intelligent” do not think, understand, or possess intentionality. Rather, they operate through statistical pattern recognition based on data generated by human beings. The article analyzes the historical and philosophical origins of the concept of intelligence, as well as the evolution of the term “artificial intelligence,” to highlight the gap between what these technologies do and what the term implies. It also distinguishes among discriminative AI, generative AI, large language models, chatbots, and AI agents in order to avoid treating them as interchangeable concepts that involve different functions and pedagogical implications. In addition, the article questions terms such as “co-intelligence” and “co-creation,” arguing that they imply a problematic symmetry between humans and machines. Finally, the article proposes alternative terms for “artificial intelligence” to support more precise, critical, and ethically responsible language in educational contexts.
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References
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