A student came to me wanting to study AI. Our conversation saved him four years and a very expensive mistake.
He had already told his parents. Already researched universities. Already decided: artificial intelligence was the path.
I asked him to explain what a neural network does, in plain language. He couldn't. Not even roughly. Not even a sentence that gestured in the right direction.
He isn't a bad student. He's a bright, motivated sixteen-year-old who had watched enough YouTube videos about AI to feel genuinely excited by the idea of it, which is completely understandable, because AI is genuinely exciting. But excitement about a field and aptitude for the actual work that field demands are two very different things, and nobody had asked him to make that distinction yet.
AI at a university level is mathematics, statistics, linear algebra, probability theory, and a level of abstract reasoning that has to be built over years, not picked up once you arrive on campus. A student who can't explain a neural network in Grade 11 isn't necessarily incapable of studying AI, but he needs an honest audit of where he is versus where the course begins, and he needs it before he spends four years and sixty lakh rupees finding out the hard way.
We spent that session not telling him to abandon the interest, but stress-testing it properly.
- What draws you to AI specifically?
- Is it the building, the research, the application, the business side?
- Can your current mathematics foundation support where this goes?
- Do you have the patience for the kind of abstract problem-solving this actually involves, day to day?
By the end of that conversation, he hadn't lost his interest in AI. He'd found the version of it he was actually built for, and a path that gave him a real chance instead of an expensive collision.
That's the difference between career counseling and telling a child to follow their passion.