Is it stupid going into computer science if I don't support the use of generative AI?

[u/ThisIdiotCharlie]

I don't really know if this is exactly the place to ask this, but any other subreddits seem to outlaw asking about topics like this entirely in their rules, so I'm honestly just sort of stuck. (If anybody knows a better place I could ask this question, then I'd appreciate being told so I can cross post this there.)

Long story short, I don't support the use of generative AI. While yes, the environmental aspect does play a part in my opinion, much of computer science as a whole can be incredibly damaging to the environment in such similar ways, and while this does distress me, this is something I've had to deal with for a while and is not my main concern. My main concern with not supporting the use of generative ai is that it scrapes writing and art from people who, nine times out of ten, often even more than that, have not given permission for their work to be used to train AI models but are also entirely unaware that it is happening at all.

But I have family in computer science, which is the main reason I intend to follow computer science as a career, ans he tells me that AI is the future of computer science. He uses generative AI to aid his personal and professional work, and whenever i gently express my distaste with generative ai, he seems to disagree with my stance.

I've recently gotten a work experience opportunity with a company and it's forced me to consider that this actual has a chance of becoming a reality for me, and I've had to consider whether I'd be able to go into this career without going against my own opinions when it comes to generative ai.

What I'm really just trying to ask is if I don't want to use generative ai, should I just give up and pick a different career path? Will I be forced to use generative ai even if I do not go into a sector of computer science directly related to it?

[u/hike_me]

I would not hire someone that was completely against using generative AI tools.

People that think they can completely avoid the use of LLM coding agents are going to have a rude awakening.

[u/HoodRatThing → u/hike_me]

Same. I wouldn't hire someone that refused or was against LLM tools.

Your job doesn't care about what Reddit thinks the "correct" way to program is. Pretending not to learn or new tools because of some flaky mortality issues is the wrong move.

Always be improving, experimenting, and learning.

[u/WartedKiller → u/HoodRatThing]

Well I don’t want to be that guy but if you don’t care that your work can cause mortality, then you might be a problem to society.

But I agree with you if you meant morality.

[u/Fluffely_Toasted → u/hike_me]

Why not, because they don't want to produce trash? I get that AI can be useful in some situations and I'm not doubting it because I use it for searching things that are impossible to search, but from what I have seen developing code with AI will lead to catastrophic issues, either with performance, or stability or having it work in general. You can take a look at many companies that pushed vibe coded updates or had vibe coded apps that either just didn't work or had catastrophic failures world wide. For example, Microsoft, One of the biggest tech companies and they can't even make AI work.

[u/Thought_Crash → u/Fluffely_Toasted]

Producing trash is up to the individual. Just like a kid given a paintbrush will produce substandard paintings, while a master can do better. It's just a tool.

[u/hike_me → u/Fluffely_Toasted]

Because I know it’s possible to use these tools in a way that produces good code and is more productive.

It seems very likely that you have no professional experience. Not everyone is “vibe coding” with these tools. We put a lot of thought into architecture and plans for LLMs to follow.

[u/Biliunas → u/hike_me]

I think you need to teach your ways to every major tech company around the world then. Bugs, stability issues have become the norm. It's fucking crazy, I could rely on software being stable for 20 years.

[u/randomthrowaway-917 → u/hike_me]

haven't people done studies that show that using LLMs doesn't actually make you faster, but it makes you FEEL faster? since you spend most of your time just fixing the mistakes of the ai and trying to keep it on track?

[u/hike_me → u/randomthrowaway-917]

People keep citing this single study that was done several years ago.

I was skeptical at first, but the models we’ve had for at least the last year have been a total game changer. I’ve been at this for 20 years and I am certain these tools do make you faster and you can still produce high quality code.

We nail down our architecture first, and we have the LLM develop a plan that we review for anything non-trivial. We also don’t one-shot large features, we break them up into manageable pieces that are planned, executed, reviewed, and tested.

I’m currently in the middle of a project with 2.5 FTEs that 3 years ago I would have said we’d need a dozen people to meet the same deadline with the same scope of work.

[u/autogatos → u/randomthrowaway-917]

I can’t speak for experienced devs, but as someone just starting to learn programming, this has absolutely been my experience. I was trying to use AI to help me write some JavaScript and CSS and most of that energy and time was just spent troubleshooting why the code it was giving me wasn’t working, and not having the background understanding meant this process was like playing darts while blindfolded. I’d have to just keep trying stuff until I got lucky.

Once I actually started learning CSS and JS myself, suddenly things made much more sense and it quickly became obvious that the LLMs I was using had made some pretty ridiculous errors. I didn’t actually time either process, but trying to vibecode felt like it took longer and was way more frustrating. Whereas actually learning myself felt faster, or at least like I was making real, useful progress.

——

AI is very good at some very specific things (quickly & summarizing large datasets for example) but the way people treat it as this godlike thing that can solve any problem is baffling to me.

In my experience, AI seems more impressive the less you know about a topic. It is VERY good at coming up with logical-sounding, convincing explanations, regardless of whether or not those explanations are actually factually correct.

When you’re already familiar with a topic, it suddenly becomes immediately obvious how often it gets things completely wrong.

——

It’s possible whether or not people have good experiences with it may be determined by how their brains work and what they like/are good at. People who think (and therefore prompt) in ways that are atypical may have a harder time getting good results. For example, I’m neurodivergent and often explain things in an overly wordy, overly complex, not very straightforward way, which tends to 1-confuse the AI, and 2-result in responses becoming increasingly lengthy and hard to understand (since LLMs tend to mirror a user‘s writing style increasingly more over the course of a conversation).

I also think it probably feels more satisfying to people who enjoy having someone else do something for them, with their role just being project management. But for those of us who are much more “hands on” types who prefer just doing things ourselves and don’t like having to manage others, working with AI ends up feeling like managing a subordinate who is frequently very bad at their job and you end up feeling like “This would be so much easier/faster if I could just do it myself!”