AI Doesn’t Learn – And That’s Your Problem, Not Its
AI is like that one coworker who nods along but forgets everything after the meeting. Large language models don’t “learn” the way humans do; they predict, mimic, and regurgitate.
If we keep calling that learning, we’re setting ourselves up for a dangerous misunderstanding.
Despite what AI tools (and their marketing teams) claim, they don’t actually learn. Unlike humans, AI doesn’t refine knowledge through experience. Instead, it predicts patterns based on vast datasets, and once trained, it’s stuck in time.
ChatGPT, for instance, doesn’t improve after your interactions. It’s pre-trained, not evolving. This matters because it means AI isn’t gaining wisdom, it’s just recycling past knowledge, often outdated or inaccurate.:
- AI “learning” is just pre-training, not adaptation.
- Even when AI seems to improve, it’s external tweaks, not inherent learning.
- Users must refine prompts, validate outputs, and remain the actual thinkers in this equation.
So, are we treating AI as a tool or mistakenly seeing it as a growing mind? How we define “learning” could shape the future of AI ethics, governance, and expectations.
Read the full article on The Conversation.
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