I agree that falling back on Pangram - or any other AI detector - is ultimately a dead end that's likely to have as many distorting effects on what and how we produce text as LLMs themselves, but I have a tangential question about one of the points on your chart, the "literature review."
I'm not interested in the ethics so much as the purpose of the activity. Isn't the point of a literature review to personally process the ideas and concepts of the other source material? For me, I would think that means reading them and then writing my own summaries as an artifact of what I've taken from the experience. An AI summary of the literature means I don't do any of that work.
This seems like an example of the AI is like bringing a forklift to the gym critique of LLM use. The point of the literature review isn't just so a literature review exists. It's to build the knowledge of the reviewer, right?
Good questions. I think “literature review” covers several different activities, and the ethics vary across them. I mostly agree when we are talking about deep lit reviews, especially for teaching or learning: if the assignment is meant to make you read, process, and synthesize the field yourself, AI replacement defeats the point. I’ve written before about my own worries about skill atrophy here.
For research writing, I’d distinguish two kinds of citations. Some papers are essential to your argument: they provide evidence, define the disagreement, or shape the frame. Those need to be read carefully. Other citations are more symbolic or positional: “this relates to a broader literature on X,” “similar work exists in Y,” “for background, see...” Academics already treat those differently, with or without AI.
So my view is that AI can help with the second kind of lit-review prose, especially when you already know the area and are placing your work among neighboring literatures. It should not create the impression that you deeply engaged with papers you only skimmed or did not read. My guess is that hallucinations become much more likely when people use AI to simulate engagement with arguments they have not actually understood.
I use AI very much the way that you do, with a lot of iteration, back-and-forth, dictating, and heavily editing. When I finish with it, I consider it mine. We need to teach people to use it that way and not just hit publish.
I don't think disclosing it is the answer because people have knee-jerk reactions to AI, even when it's well written. I know you use AI because I've read some of your previous articles where you've talked about it. But I'll be honest with you, my AI radar doesn't go off when I read your stuff the way it does with many other people who don't edit the output and simply provide it as is.
If the final result still sounds like the person who wrote it, isn't that the whole point?
As for the winners of literary competitions, that's a whole other situation, and I don't know how they're going to deal with that. What exactly are we judging at that point: the writing, the editing, the prompting, or some combination of all three?
In the end, I don't think any detector is going to be foolproof. The bigger question is what constitutes AI-generated content. Is the way you write AI-generated? Is the way I use it AI-generated? How do we determine authorship? At some point, almost everybody is going to be using AI to help them write in some capacity.
Thanks, Betty, that’s flattering. I agree with almost all of this. When I go back to some of my earlier AI-assisted writing though, I can see plenty of things I would handle differently now, including little phrases and rhythms that would annoy me today. The funny part is that the strongest AI radar often belongs to people who use these tools a lot themselves :)
In any case, my guess is that all this becomes much less interesting in a couple of years because the incentives all point toward widespread use. What I’m trying to do is speed up the awkward transition, including less moral panic and better social norms.
I think I'm still less of a pessimist on disclosure and *more* of a pessimist on detectors, but I recognize that both are moving targets with sometimes pernicious incentives baked in.
I hope this landscape levels out before the decade is over.
I agree that falling back on Pangram - or any other AI detector - is ultimately a dead end that's likely to have as many distorting effects on what and how we produce text as LLMs themselves, but I have a tangential question about one of the points on your chart, the "literature review."
I'm not interested in the ethics so much as the purpose of the activity. Isn't the point of a literature review to personally process the ideas and concepts of the other source material? For me, I would think that means reading them and then writing my own summaries as an artifact of what I've taken from the experience. An AI summary of the literature means I don't do any of that work.
This seems like an example of the AI is like bringing a forklift to the gym critique of LLM use. The point of the literature review isn't just so a literature review exists. It's to build the knowledge of the reviewer, right?
What am I missing?
Good questions. I think “literature review” covers several different activities, and the ethics vary across them. I mostly agree when we are talking about deep lit reviews, especially for teaching or learning: if the assignment is meant to make you read, process, and synthesize the field yourself, AI replacement defeats the point. I’ve written before about my own worries about skill atrophy here.
For research writing, I’d distinguish two kinds of citations. Some papers are essential to your argument: they provide evidence, define the disagreement, or shape the frame. Those need to be read carefully. Other citations are more symbolic or positional: “this relates to a broader literature on X,” “similar work exists in Y,” “for background, see...” Academics already treat those differently, with or without AI.
So my view is that AI can help with the second kind of lit-review prose, especially when you already know the area and are placing your work among neighboring literatures. It should not create the impression that you deeply engaged with papers you only skimmed or did not read. My guess is that hallucinations become much more likely when people use AI to simulate engagement with arguments they have not actually understood.
I use AI very much the way that you do, with a lot of iteration, back-and-forth, dictating, and heavily editing. When I finish with it, I consider it mine. We need to teach people to use it that way and not just hit publish.
I don't think disclosing it is the answer because people have knee-jerk reactions to AI, even when it's well written. I know you use AI because I've read some of your previous articles where you've talked about it. But I'll be honest with you, my AI radar doesn't go off when I read your stuff the way it does with many other people who don't edit the output and simply provide it as is.
If the final result still sounds like the person who wrote it, isn't that the whole point?
As for the winners of literary competitions, that's a whole other situation, and I don't know how they're going to deal with that. What exactly are we judging at that point: the writing, the editing, the prompting, or some combination of all three?
In the end, I don't think any detector is going to be foolproof. The bigger question is what constitutes AI-generated content. Is the way you write AI-generated? Is the way I use it AI-generated? How do we determine authorship? At some point, almost everybody is going to be using AI to help them write in some capacity.
Thanks, Betty, that’s flattering. I agree with almost all of this. When I go back to some of my earlier AI-assisted writing though, I can see plenty of things I would handle differently now, including little phrases and rhythms that would annoy me today. The funny part is that the strongest AI radar often belongs to people who use these tools a lot themselves :)
In any case, my guess is that all this becomes much less interesting in a couple of years because the incentives all point toward widespread use. What I’m trying to do is speed up the awkward transition, including less moral panic and better social norms.
Nuanced and well reasoned as usual, sir.
I think I'm still less of a pessimist on disclosure and *more* of a pessimist on detectors, but I recognize that both are moving targets with sometimes pernicious incentives baked in.
I hope this landscape levels out before the decade is over.
Thanks, Quinn!