Metaphor: AI systems are often described as “apprentices” learning from data, training, or guidance.
Problem / Misleading Aspect: This metaphor suggests intentional learning, comprehension, and curiosity, implying that AI can absorb lessons like a human student. It obscures the statistical, algorithmic, and relational nature of machine learning: patterns emerge from optimisation over data, not from reasoning or understanding. Misreading AI as an apprentice risks overestimating its agency and ethical responsibility.
Relational Ontology Correction: AI is a relational system of aligned potentials, adjusting parameters to minimise error or maximise performance according to a defined objective function. There is no intention, awareness, or comprehension. “Learning” is the emergent effect of relational constraints, not cognitive growth.
Parody / Conceptual Highlight: Taken literally, one might picture neural networks raising tiny hands in class, asking for hints on backpropagation, or an AI apprentice daydreaming about its future career. The humour highlights the conceptual misstep: the apprentice metaphor misleads by projecting human cognition onto relational, statistical processes.
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