Most people who use AI think it is great in general but believe it does not grasp their area of specialization very well. As an applied philosopher, I create intellectual tools to help others think through their problems. I find AI excellent at clarifying and explaining ideas, but it has never generated an original idea worth writing about. I have yet to see reports from others in any discipline that AI has independently produced groundbreaking ideas.
AI can handle large amounts of data and provide coherent, accurate responses across various fields. This ability is comparable to a well-informed amateur who has a broad understanding but lacks deep expertise. AI can recount historical facts, explain scientific principles, and offer legal insights based on data patterns, yet it falls short in deeper, more nuanced analysis.
In my case, AI can assist by summarizing existing theories or offering possible objections or additional arguments. However, it lacks the ability to generate a genuinely novel idea. I use it a lot, and not even once did it produce anything like that. This limitation stems from its reliance on pre-existing data and patterns, preventing it from achieving the level of innovation that human professionals bring to their fields. Some believe that this limitation will soon be overcome, but I do not think so. It seems to be an intrinsic limitation, a function of AI's way of training.
Professionals/experts, whether in philosophy, medicine, or history, possess a depth of understanding developed through extensive education and practical experience. They apply complex methodologies, critical thinking, and ethical considerations that AI cannot replicate. A doctor considers the patient's history and unique implications of treatments, while a professional historian places events within a broader socio-cultural context. AI, despite its capabilities, often misses these subtleties. It is, in some sense, a savant: a fast, amazing, but inexperienced thinker.
The gap between a capable amateur and a professional/expert might seem small, especially from the point of view of the amateur. However, it is huge and is rooted in the depth of expertise, critical thinking, and the ability to judge that professionals possess; it is a function of intellect, experience, and education. This gap is where educators should look to adapt the curriculum.
In education, we should focus on that gap between the amateur and the professional and conceptualize it as the ultimate learning outcome, then build new skill ladders to claim there. Students need to understand and conquer the gap between AI and a professional expert. These meta-AI skills are our true North. AI can support this learning process by providing clear explanations and diverse perspectives, but it cannot replace the nuanced understanding and innovation that human professionals offer.
