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This presentation offers a critical analysis of the integration of Artificial Intelligence within the educational ecosystem, starting from the premise that true Artificial Intelligence does not yet exist. What we currently use are powerful statistical systems, although fluent and fast, they that lack human understanding, causal reasoning, and the ability to verify truth. The discussion focuses on the intellectual danger of substituting verification with speed and reasoning with trust, which leads a society to stop questioning. Instead of genuine education, we are witnessing the emergence of dependency training, where students are taught to use tools to generate ideas or summaries, rather than learning how to refute, reason, or ask why. The narrative that AI is a finished product is a curiosity-killer; in reality, we are only at the beginning of a process filled with unsolved problems regarding bias and explainability. Therefore, it is argued that every AI output should be treated as a hypothesis rather than a definitive answer, and every model as a study case instead of an oracle. The ultimate goal is to ensure that learners do not become passive users of alien intelligence, but remain curious minds engaged in the sovereign act of discovery.
Descrição
Palavras-chave
Digital literacy Critical thinking Technology dependence Knowledge construction
Contexto Educativo
Citação
Gouveia, L. B. (2026). Artificial intelligence as unfinished work: challenges and misconceptions in contemporary education. In A. A. Taubayev (Ed.), Artificial Intelligence, Inclusion, and Academic Integrity: Balance of Innovation and Educational Values: Materials of the International Educational and Methodological Conference (pp. 5–9). Esil University. Astana. Kazakhstan.