Please see the general NYU policy.
Any violations of the NYU or course policy on academic integrity may result in punishment. Depending on severity, this could range from receiving a zero on the homework, quiz, or project to failure of the course. Severe violations will be reported to the University.
The quizzes are designed to reinforce specific key concepts from the course.
The general rule of thumb is that you must write up the solutions yourself and you should be able to explain anything you turn in. Your code should be written entirely by you.
You are encouraged to work together with peers. This not only helps to cut down on the workload, but strengthens your own understanding of the topics. This is because explaining concepts forces you to engage with them in a deeper way, thereby building a better understanding of the material.
However, you must still write up your solutions on your own, and you should understand everything you write. For each assignment, you must include who you worked with (first name+last name) or whether you worked alone.
Figuring out how to effectively search for information on the internet is an extremely useful skill. At the same time, at some point in your career you will probably come across problems without solutions. Without having developed the proper problem solving skills, it will be much harder to come up with a solution. To balance these two possibilities, you are allowed to use the internet to search for solution to a problem after (i) you have been to office hours or used the discussion board to ask about this problem, and (ii) you have spent at least 24hr on the problem after office hours/receiving a response on the discussion board.
If you use the internet or other external sources, you must cite the source and include a description of how you used the source. Failure to do this is a violation of the course policy and will be penalized.
The use of LLMs such as chatGPT is a bit of a grey area with respect to many existing norms on academic integrity, particularly plagiarism. My view is that such tools are only likely to grow in prevalence, so it is important for students to gain experience using them now. However, it is also my belief that we should all be transparent about where we are getting information. As such, you must clearly explain how you used such tools on each problem.
Every tool has uses and limitations. Since LLMs are relatively new, we are still learning about both. One major limitation of current LLMs is that they do not truly understand anything they are saying. Rather they generate responses based on text they have been trained on, and are therefore prone to confidently stating incorrect information. As with all tools, the user must understand when and how to wield them.
The use of LMMs in other classes may treated differently, so you should check with each instructor about their policy.