this post was submitted on 10 Aug 2023
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Why should anyone care? I don't go around telling people every time I use stack overflow. Gotta keep in mind gpt makes shit up half the time so I of course test and cross reference everything but it's great for narrowing your search space.
I did some programming assignments in a group of two. Every time, my partner sent me his code without further explanation and let me check his solution.
The first time, his code was really good and better than I could have come up with, but there was a small obvious mistake in there. The second time his code to do the same thing was awful and wrong. I asked him whether he used ChatGPT and he admitted it. I did the rest of the assignments alone.
I think it is fine to use ChatGPT if you know what you are doing, but if you don't know what you are doing and try to hide it with ChatGPT, then people will find out. In that case you should discuss with the people you are working with before you waste their time.
I've had partners like that in the past. If ChatGPT didn't exist they would've found another way to cheat or avoid work.
The type of partner who takes the task you asked them to complete, posts the task description on an online forum and hope someone gives them the answer.
Yes but I think it is a bit different because it just lowers the bar for this a lot. You also really lose trust in everything once you realize that you have spent a lot of time interacting with and checking AI generated stuff without knowing.
I get that. Before ChatGPT if I had a bad partner it is very quickly obvious that their work is bad.
Now you might be tricked into thinking they're competent, which I can imagine is more frustrating because it's unpredictable.
I guess that right now people are overusing it as it's so new, but in the end the people who want to graduate without trying to learn will always try to abuse whatever tools they have to cheat. Usually they face the consequences at some point in their lives.
To really be successful you need to be curious enough to want to understand things at a deep level. With LLMs people who don't really care well learn even less than before.
This is the key with all the machine learning stuff going on right now. The robot will create something, but none of them have a firm understanding of right, wrong, truth, lies, reality, or fiction. You have to be able to evaluate its output because you have no idea if the robot's telling the truth or not at that moment. Images are pretty immune to this because everyone can evaluate a picture for correctness or realism, and even if it's a misleading photorealistic image, well, we've already had Photoshops for a long time. With text, you always have to keep in mind that the robot might be low quality or outright wrong, and if you aren't equipped to evaluate its answers for that, you shouldn't be using it.
Even with images, unless you're looking for it most people will miss glaring problems. It's like that basketball video psychology experiment.
The problem is definitely bigger with LLMs though since you need to be an expert to check the output for validity. I will say when it's right it saves a ton of time, but when it's wrong you need to know enough to tell.
Yes, LLMs are great as a research assistant if you know what to look for, but they're a horrible learning tool. It's even worse if you don't know the correct way to search for an answer, it will set you down a completely wrong path. I don't use any answer without cross referencing and testing it myself. I also rewrite most of the code it spits out too since a lot of it follows terrible programming patterns and outdated standards.
He should've at least looked at the code and tested it before sending it to you. Ugh. Hate doing assignments with people who do the bare minimum and just waste your time.
The problem with using it is that you might be sending company proprietary or sensitive information to a third party that's going to mine that information and potentially expose that information, either directly or by being hacked. For example, this whole thing with Samsung data: https://techcrunch.com/2023/05/02/samsung-bans-use-of-generative-ai-tools-like-chatgpt-after-april-internal-data-leak/
We've been instructed to use ChatGPT generically. Meaning, you ask it generic questions that have generic usage, like setting up a route in Express. Even if there is something more specific to my company, it almost always can be transformed into something more generic, like "I have a SQL DB with users in it, some users may have the 'age' field, I want to find users that have their age above 30" where age is actually something completely different (but still a number).
Just need to work carefully on ChatGPT.