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The debate surrounding the topic of Artificial Intelligence (ai), and its different meanings, seems to be ever-growing. This paper aims to deconstruct the seemingly problematic nature of the ai debate, revealing layers of ambiguity and misperceptions that contribute to a pseudo-problematic narrative. Through a review of existing literature, ethical frameworks, and public discourse, this essay identifies key areas where misconceptions, hyperbole, and exaggerated fears have overshadowed the genuine concerns associated with ai development and deployment. To identify these issues I propose three general criteria that are based on Popper’s and Ayer’s work and adjusted to my needs. The subsequent sections categorize ai issues into ontological, methodological, and logical-grammatical problems, aligning with Cackowski’s typology. In addition, I introduce «» signs to distinguish behavioural descriptions from cognitive states, aiming to maintain clarity between external evidence and internal agent states. My conclusion is quite simple: the ai debate should be thoroughly revised, and we, as scholars, should define the concepts that lie at the bottom of ai by creating a universal terminology and agreeing upon it. This will give us the opportunity to conduct our debates reasonably and understandably for both scholars and the popular public.
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