教学中的AI危机：“训练你自己的神经网络！”
The AI crisis for teaching: "Train your own neural network!"
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中文总结 AI 辅助
本文指出AI对教学构成生存危机，强调学生应使用AI工具辅助而非取代教育，核心是训练自己的神经网络以培养独立思考能力。
中文摘要 AI 辅助
如今，似乎每个人都在思考所谓的人工智能（AI）。作为科学家，我们明白我们并不会很快拥有一个有意识的计算机智能来接管世界，但我们仍然担心“大型语言模型”（LLM）和AI“智能体”正在影响我们做科学的方式。这种担忧已经催生了多篇关于AI对研究影响的近期文章，包括在我自己的天文学和天体物理学领域。这些观点文章往往忽略了那些将教学与研究相结合的工作者当前面临的最大担忧——尽管对我们所知的未来科学研究的威胁可能有点令人担忧，但对教学的影响现在正是一场生存危机！我们需要坚守我们认为处于教育核心的部分——这样从学位课程毕业的学生才能真正独立思考，“像天体物理学家一样”。这意味着要向学生强调，他们应该使用AI工具来支持他们的教育，而不是取代它。解释这一原则重要性的一个方法是指出，学生应该训练他们自己的神经网络。
英文摘要
Everyone seems to be thinking about so-called artificial intelligence (AI) these days. As scientists, we understand that we're not about to have a conscious computer intelligence taking over the world, but we're nevertheless concerned about how "large language models" (LLMs) and AI "agents" are impacting the way that we do science. This concern has generated several recent essays about the effects of AI on research, including in my own field of astronomy and astrophysics. These opinion pieces tend to miss the biggest current concern for those whose jobs combine teaching with research - although the threat to future scientific research as we know it is probably a bit concerning, the effect on teaching is an existential crisis right now! We need to hang on to the parts of education that we think are at its core - so that students coming out of degree programmes are actually able to think for themselves, "like an astrophysicist". This means emphasising to students that they should use AI tools to support their education and not to replace it. One way of explaining the importance of this principle is to point out that students should be training their own neural networks.
发表机构
- Dept. of Physics & Astronomy, University of British Columbia（不列颠哥伦比亚大学物理与天文系）
机构由 AI 辅助整理，请以论文原文为准。
