Interview: AI in Physics Studies – Helpful Assistant or Hidden Trap? A Chat with Physics Student Aleks

Back in the day, physics students often had to battle thick C++ handbooks, cryptic compiler error messages, and countless nights spent debugging code. Today, a chat window is sometimes all you need. More and more students are using artificial intelligence (AI) to speed up programming tasks, calculations, or to better organize their assignments. But how exactly does this affect our learning? Does AI actually make us smarter – or just lazier?

To better understand this, we've spoken to Aleks, a 24-year-old physics student now in his 11th semester at the University of Bonn. He has plenty of experience and knows first-hand both the possibilities and limitations of AI tools. In this interview, he shares insights about how he uses AI in his studies, points out potential risks, and explains why ultimately personal responsibility is key.

Editorial: Aleks, do you already use AI tools in your studies?

Aleks: Yeah, I regularly use ChatGPT, especially when I run into issues with programming. It's really handy for asking specific questions, like explaining error messages or suggesting how to structure certain code snippets. However, I don't just copy-paste the solution the AI hands me. I'm mostly looking for hints or explanations about why my code isn't working. For me, that's the right way to use these tools, because otherwise you're not really learning anything at all.

Editorial: What sort of tasks do you tackle with AI most?

Aleks: Most frequently, I use AI when I'm struggling with software issues or programming errors, for instance when I'm trying to figure out cryptic error messages or to find subtle bugs. AI can be a real lifesaver in these cases, giving precise suggestions pretty quickly. However, I rarely use it for calculations or deriving physics formulas – personally, I'd rather work these out myself. It's crucial to actually go through the thought process on your own, even if it takes more time.

Editorial: Has using AI significantly changed the way you study?

Aleks: Actually, not that much. AI saves me some time occasionally, particularly for solving specific coding issues, but overall, my study habits haven't really changed much.

Editorial: Which other AI tools are you familiar with, even if you haven't used them directly?

Aleks: Besides ChatGPT, I've also heard of Meta AI, Gemini, Midjourney, and Learnboost. I haven't personally used these yet, but some classmates mentioned them.

Editorial: Overall, what's your stance on using AI in studies?

Aleks: Honestly, I'm rather critical about it. I can see clearly that AI helps many students, but I also feel it's causing people to engage less with the actual course material. It becomes too easy to just get a correct answer without truly understanding the problem. I remember a situation in one of my tutorials – one fellow student clearly used an AI tool to solve all the homework correctly, but when asked to explain her solutions, she couldn't really describe what she had done. This clearly shows that a crucial part of learning, deep understanding, can easily get lost. Especially in physics, where deep understanding really matters, that can be problematic.

Editorial: Could AI specifically enrich your studies in physics if used sensibly?

Aleks: Yes, for certain tasks. Especially when programming, AI tools can be extremely useful. But when it comes to analytical or purely mathematical problems, where independent thinking and your own reasoning are central, I see little benefit. However, as a support tool – especially since AI is already broadly used in actual research – it's definitely justified.

Editorial: What concerns do you have regarding AI use in academic life?

Aleks: My main worry is that students could gradually lose the ability to think independently due to over-relying on AI. There's a risk of skipping important thought processes when you can immediately get quick answers. If every question can easily be answered by AI, you're no longer forced to engage deeply with the issue yourself – and the very act of working through the problem is where real learning happens. Particularly in physics, understanding concepts thoroughly is key for applying them later. It's not just about getting the answer, it's about understanding how to get there. And excessive reliance on AI shortens that path, ultimately hindering learning.

Editorial: How do you feel about morally and ethically responsible AI use in an academic setting?

Aleks: I think it's problematic if AI becomes too dominant in academic work because genuine individual effort can quickly disappear, and fairness in academic competition would no longer be ensured.

Editorial: From your point of view, how should AI use in studies be regulated?

Aleks: Personally, I believe self-regulation is most important. If students act honestly and thoughtfully assess how much AI support is appropriate, formal regulation might not even be necessary. Of course, in practice it's sometimes harder, as not everyone handles such tools equally responsibly. But especially at university, you should be allowed to independently learn how to manage new technologies instead of being strictly restricted by rules and regulations. Trust and self-accountability definitely belong to university life as well.

Editorial: In your opinion, does AI increase or decrease the risk of plagiarism?

Aleks: Definitely increases it. It's become much easier than before to just let AI generate material without genuinely engaging with the subject.

Editorial: What specific functionalities would you like to see in an ideal AI tool for your studies?

Aleks: Most importantly for me would be an AI that truly understands problematic code – not just spotting the error, but also explaining why something isn't working, almost as if you're talking to an experienced peer. It should offer ideas to clarify why something gets stuck, rather than just handing over ready-to-go code. Additionally, it would be extremely helpful if AI could effectively summarize complex scientific texts and analyze graphs such as phase diagrams without forcing you to sit through half a textbook first. That'd significantly reduce stress during exam periods.

Editorial: Are there other areas where AI could potentially support you further?

Aleks: One thing that comes to mind is time-management support during exam preparation. Honestly, that's always a major challenge for me each semester – I easily get distracted or procrastinate under pressure. An AI that could create structured study schedules, accounting realistically for breaks and reviewing periods, would be genuinely helpful. It would also be beneficial if there were an AI-powered tasks database offering suitable practice problems, ideally with solutions provided for comparison. Especially when preparing for exams, such a feature would greatly reduce stress and allow me to study more effectively.

Conclusion and Outlook

Our conversation with Aleks clearly demonstrates the ambivalent feelings about integrating AI into physics studies. While its clear usefulness in specialized tasks (particularly programming) is widely acknowledged, the concerns about losing independent critical thinking and breaching ethical limits are legitimate too. Aleks emphasizes that self-accountability is crucial when it comes to using AI. It will be fascinating to see how the balance between AI's benefits and drawbacks develops in academic practice in the coming years.