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This seems to me like one of those things where people go into it with widely different initial assumptions. 1. AI is for cheating and doing the work for you.
by simonw 6mo ago
This seems to me like one of those things where people go into it with widely different initial assumptions.
1. AI is for cheating and doing the work for you. Obviously it won't help you learn faster because you won't have to do any thinking at all.
2. AI is an always-available question answering machine. It's like having a teaching assistant who you can ask about anything at any time. This means you can greatly accelerate the process of learning new things.
I'm in team 2, but given how many people are in team 1 (and may not even acknowledge team 2 as even being a possibility) I suspect there may be some core values or different-types-of-people factors at play here.
- runarberg 6mo agoThis is also a testable hypothesis. I would like to see usage statistics before making assumptions here but my gut feeling is that an overwhelming AI usage (like > 90%) would fall into your category 1. But even with category 2. I think that still does not absolve AI as a cheating machine. Doing research is a skill and if you ask AI to do the research for you that is a skill a junior developer simply never learns.
- simonw 6mo agoThis is interesting and relevant: https://www.sciencedirect.com/science/article/pii/S0959475225000660 https://www.sciencedirect.com/science/article/pii/S095947522... "The expertise reversal effect is present when instructional assistance leads to increased learning gains in novices, but decreased learning gains in experts." There's a whole lot of depth to the question of how AI tools support or atrophy learning for different levels of expertise.
- deleted 6mo ago[deleted]