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Most AI bans refer to the results of Generative AI (Gen AI), Large Language Model (LLM), or Machine Learning. There are several common primary reasons for the ban. One of the most common is due to rights. Most Gen AI contains stolen work. You  must have the rights to everything in your submission, and if you use Gen AI that was trained on materials they did not have the rights too, then you do not have the rights to the results of that creation. Even if they claim to only use their materials to train the AI, nearly all of them use a core that was originally trained on stolen material, and few release all the training data for you to validate the claim. This applies to coding Gen AI as well as graphical art.

For some it is due to the environmental impact. The extreme energy and water use requirements are causing severe harm to the communities where they are built. They consume so much for what they can produce. Being run by big corporations they can get away with these harms and the people in the areas nearby suffer without any recourse. Beyond the local communities, they consume so much, and contaminate the environment so badly, that the effects of the ever growing number of these facilities is affecting everyone.

Another common issue with Gen AI, including from a coding perspective, is that people often use it as a way to not have to learn the topic, do the work, or pay someone to do it. You are getting the results of other people's work that was stolen and not learning or improving yourself. There are plenty of people out there to make a quick buck using AI slop to create a bunch of garbage to sell, and often submit to jams for free publicity. Modern AI very commonly hallucinates and gives you bad information. If you never learned the material in the first place, then you won't know when it lies to you. Buggy, messy code, that is based on the work of others, including work that the AI company did not have the rights to, is being thrown together to create garbage that is then flooding the market. Many jams are about the people who participate doing the work to learn and improve. According to studies, the use of AI harms people's ability to think for themselves and make most only become more reliant on it, rather than learning to do better by using it.

We agree with all of these reasons and do not support Gen AI in any form. Pre-Gen AI things like basic auto complete based on coding standards or what is already in your project are fine. If it is powered by one of the Gen AI companies, then that is not. Getting code from a Gen AI system, whether a chat bot or something built into a tool you are using, is absolutely not allowed.

Id be interested in reading about the studies of AI harming people's ability to think for themselves if you have a link.

I don't have any links handy at the moment, and before I'd share any I'd want to reread them and make sure I was sharing a good one with links to the data from a proper study and a clear explanation. That will take time that I don't have at the moment. I'll try to keep an eye out for any new studies and if I see a good one soon I'll share it. Feel free to do some searching on your own as well. AI is a hot topic these days and there are more studies every day.

I know it has been a while, but I came across a study in my news feed today and remembered this conversation, so I'm sharing the link.

ChatGPT as a cognitive crutch: Evidence from a randomized controlled trial on knowledge retention
https://www.sciencedirect.com/science/article/pii/S2590291125010186

Cool, thanks for sharing.
reading through it id like to bring up some points I find interesting.

The chatgpt spent 45% less time studying than those doing it traditionally and scored 11% lower on their retention test (57% vs 68%)

In one section they discuss that the biggest disparity happens on complex subjects, it seems a structured course is better. This makes the next part I mention below an interesting choice to me.

From what I read the content for studying was "AI/ML topics spanning foundations, methods, applications, and ethics". This seems to be a pretty complicated subject to me. The students chosen for this test are Business Administration students. Im guessing its a pretty large learning curve from that to machine learning.
They do mention that there is still disparity on other topics but it looked like it was about half as bad.

In my personal opinion I do think it is a crutch, a stiffer crutch than google even, however I think they may have painted the picture a little worse than it is. 
There is a lot of things in this world to know about or understand, sometimes knowing where to find an answer is our best option. 

This discussion does remind me of math class at least when I was in school, simply putting the correct answer on the test did not give you full points, you had to write the process you used to get to the answer, demonstrating you actually understand the process. If you truly want to learn something effort, time, involvement, execution all greatly help in retention. For me putting it into real world practice is most beneficial. 

This is just the latest study I came across. I've seen others. Most often they are on students and how they become dependent on AI instead of learning to think for themselves.

Knowing how to use tools to find facts is often more important than remembering every little detail, but critical thinking and problem solving are vital skills on their own that go beyond knowing specific facts. The problem with comparing AI to using a search engine to find facts, is that Generative AI/LLM is not a tool for finding facts. It is a tool that makes up answers based on how it was trained. Sometimes it will give you facts. Sometimes it makes up completely random answers and you have to know enough of the topic to be able to know the difference, in which case you probably could have solved the problem yourself.

In cases of programming, many people are asking it to create new things, be it art or code. That is no longer working with simple facts but having it do the work of solving the problem for you. If people, especially students learning new things, rely on AI to do the creative thinking and problem solving for them, then they will not develop the neural pathways to do it themselves. Their brains will become wired to always go to the AI tools for the answer. It will be a self-feeding cycle of dependence. 

We live in stressful times, and people are often looking for shortcuts. It is easy to start by only using something occasionally for certain situations. When you start to feel that it works well enough and is convenient , you may start to decide to use it more and more. Soon, it may be the first place you look whenever you run into something you don't have the immediate answer for. People will do a lot for convenience. The more you use it, then more you become dependent on it. That is the trend that I see being reported as the big problem with the way Gen AI is being used these days. People stop being able to think for themselves because having the AI do all the thinking when they run into a challenge is quicker and easier, and life is stressful enough that having it take care of these things is so convenient. The more you use it, the more you are likely to trust it. You may start by using it as one of many sources, and even validating everything. The more it works, the more confidence you will have in it. Over time, as your confidence grows, you are more likely to do less validating and comparing to other sources. That is a very common thing for people to do with repetition of things that work for them. That kind of complacency is how many mistakes and accidents happen, not just specific to AI. One problem here is that Gen AI is constantly changing, and something that works today may not tomorrow, but you may not know what changed or when.

In addition to all of the other problems with using Gen AI, it is absolutely not at the point where it should simply be trusted to give you the right answer all the time. It should at best be seen as giving you a starting point that must be validated by someone familiar with the topic. It is the kind of thing that is good at taking a huge set of data and reducing it down to the most likely candidates, which can then be handled by people, but should not be deciding on the final answer. Far too many people try it a few times and think it has all the answers and simply trust whatever it says. I've heard people in business environment praise how amazing it is and talk about putting it everywhere, without any need for validation, because it worked so well for them in the few personal things they tried. Someday AI may be able to do more, but in its current state it is being marketed as more than it is, and people are relying on it too much.