Professors who use AI detection incorrectly are failing their students
Not sure if this has been discussed before but I think it is worth talking about.\n\nHere is what prompted this post – something happened in my class this week that made me realize how big this issue has become. I am not going to share specifics to protect privacy but the general situation is probably familiar to a lot of you.\n\nI think we need to have a more honest conversation about this because the current approach is not working for anyone.\n\nAnyone have additional resources or experiences to share? The more information we pool together the better.
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Log In to ReplyI think the bigger issue here is that universities are using these tools as definitive proof when they should be treated as one data point among many.
I tried three of these tools last week and my results were pretty close to what you found. The variance between detectors is honestly absurd.
Yeah I ran into the same thing. It is frustrating.
Just went through this exact situation last month. Ended up having to do an oral defense of my paper which was actually fine because I wrote every word myself.
Interesting take. I wonder if this varies by institution.
I had a completely different experience with this. For me the results were actually pretty good but I think it depends on what kind of content you are testing.
I showed this to my study group and we had a great discussion about it. Thanks for sparking the conversation.
This is why I always self-check my papers before submitting. Takes 5 extra minutes but saves so much stress.