This is my first time learning that AI-graded essays are a thing. Am I the only one who thinks that's insane? I feel like you'd probably have to have an AGI to meaningfully evaluate an essay.
I work in AI, and was very surprised when I heard about this (a few years ago). I don't think anyone who works in the area thinks the tech is ready for this kind of deployment. There is research on the subject [1], and NLP systems can do better than baseline methods, but the error rates are still pretty high. A thing you quickly find if you try to download off-the-shelf NLP tools and apply them to anything is how lit…
Hmmm. I also work in AI, in fact professionally in information retrieval and NLP. I disagree strongly with what you say. Basic topic summarization and keyword / named entity extraction on unstructured sources of text works reasonably well. It’s easy to modify BERT and GPT on smaller problems, language classification is borderline totally solved by extremely easy to train neural network models.
I still agree that automatic essay grading is beyond the reach of SOTA NLP models today, but youmake it sound like virtually nothing can be done in a production-grade manner that solves real world unconstrained NLP problems. This is manifestly false.
My mother worked grading standardized tests. It was a hellish job for many reasons (limited breaks, etc.) One question she had to grade was essentially, "What's something you want your teacher to know about you?" It was an essay answer, and she was supposed to grade it on grammar, etc. Just the mechanical aspects of writing. (The real question explained the details more, but that was the core of the question.) She sa…
Or...report it to the police? I’d gladly risk my job to do the right thing in that instance.
They should be mandatory reporters at least in the USA.
“In most machine scoring states, any of the randomly selected essays with wide discrepancies between human and machine scores are referred to another human for review”. And “between 5 to 20 percent” of essays are randomly selected for human review. So the takeaway is that if you’re one of the 80-95% of (typically black or female) people who the machine scored dramatically lower, but are not selected for human review,…
I work in AI, and was very surprised when I heard about this (a few years ago). I don't think anyone who works in the area thinks the tech is ready for this kind of deployment. There is research on the subject [1], and NLP systems can do better than baseline methods, but the error rates are still pretty high. A thing you quickly find if you try to download off-the-shelf NLP tools and apply them to anything is how lit…
Hmmm. I also work in AI, in fact professionally in information retrieval and NLP. I disagree strongly with what you say. Basic topic summarization and keyword / named entity extraction on unstructured sources of text works reasonably well. It’s easy to modify BERT and GPT on smaller problems, language classification is borderline totally solved by extremely easy to train neural network models. I still agree that auto…
It's completely possible I'm not fully up on recent progress, especially since a bunch of stuff seems to have moved in the past 6 months. But I haven't seen any general models that can solve open-domain problems, without specifically retraining on each domain. Do you have any pointers? E.g. a single pretrained BERT model that can reliably extract topics from: tweets, paragraphs from 19th-century novels, mathematics journal articles, and Wikipedia articles? All the systems with very low error rates that I know of target one specific domain. The last time I looked into sentiment analysis (a year or so ago), it wasn't even that great on many individual domains, e.g. it would get tripped up by sentences from novels that used "negative" keywords in a humorous or ironic way.
The thing is, you could be similarly screwed by a biased human whose grading is not checked by a less biased human. At least the machines offer the following hope: even if unbiased humans are rare among paper-grading teachers, those humans can be used to train the machines, so then bias-free or lower-bias grading becomes more ubiquitous. Basically, the system has the potential for systematically identifying and reduc…
AI has a lot more potential for bias than humans. It depends on the input data which is likely heavily biased based on other data set results like face detection. It will only amplify any small bias present in the data.
So will humans. With AI, the model and training data are auditable and, if necessary, modifiable. You can't audit a person's life history and you can only really modify a grader by replacing them, and it's much less socially damaging to retrain a model than to fire an employee.
AI certainly has a lot of potential for bias, but claims that AI bias is somehow worse than good old human bias always seem shoddily supported (Note I'm not claiming it's untrue. Just that it's never been shown to my satisfaction, which is not surprising given how quickly AI is changing. It may well be true.)
This is my first time learning that AI-graded essays are a thing. Am I the only one who thinks that's insane? I feel like you'd probably have to have an AGI to meaningfully evaluate an essay.
In a forum of CS people I'm surprised this is one of the top opinions. Our field is full of super surprising results like this -- that you don't have to actually understand the text at beyond basic grammar structures to reasonably accurately predict the score a human would give it.
Like this kind of thing should be cool, not insane. I mean wasn't it cool in your AI class when you learned that DFS could play Mario if you structured the search space right?
“In most machine scoring states, any of the randomly selected essays with wide discrepancies between human and machine scores are referred to another human for review”. And “between 5 to 20 percent” of essays are randomly selected for human review. So the takeaway is that if you’re one of the 80-95% of (typically black or female) people who the machine scored dramatically lower, but are not selected for human review,…
>So the takeaway is that if you’re one of the 80-95% of (typically black or female) people who the machine scored dramatically lower
It's quite funny how are some people manipulated to think that society and especially education is somehow biased against minorities or women when opposite is true[1][2].
My mother worked grading standardized tests. It was a hellish job for many reasons (limited breaks, etc.) One question she had to grade was essentially, "What's something you want your teacher to know about you?" It was an essay answer, and she was supposed to grade it on grammar, etc. Just the mechanical aspects of writing. (The real question explained the details more, but that was the core of the question.) She sa…
‘Poor sentence structure and grammar, 1 point out of five. Sorry your daddy touches you.’
The thing is, you could be similarly screwed by a biased human whose grading is not checked by a less biased human. At least the machines offer the following hope: even if unbiased humans are rare among paper-grading teachers, those humans can be used to train the machines, so then bias-free or lower-bias grading becomes more ubiquitous. Basically, the system has the potential for systematically identifying and reduc…
AI has a lot more potential for bias than humans. It depends on the input data which is likely heavily biased based on other data set results like face detection. It will only amplify any small bias present in the data.
It's amazing to see how the general opinion of CS people has completely shifted in the last few years from "algorithmic scoring is important in removing the bias from human graders" to the exact opposite.