The important distinction here to my mind is whether you are engaging with the AI in a task that you can think of as weightlifting or forklifting (I heard this distinction elsewhere). The basic idea is whether your main goal is to get the job done by any means necessary, or if you're engaging in some sort of deliberate practice to increase your skills or knowledge. So your argument applies mostly to things that are like forklifting...you just have to get the job done. But when dealing with students using AI to sidestep aspects of assignments that were designed to help them develop their mental muscles, then we probably need to approach it a bit differently.
As a philosopher I’m of course interested in finding out what’s true, but I am also interested in developing my own point of view, understanding what I think about certain topics, and engaging in productive conversation with others through the journals. Those things have value too. I’m not going to outsource my own thinking, even if the subcontractor is better at it than I am.
1. I agree that it's useful and important to develop an understanding of certain things, and that can't be outsourced.
2. But I'm talking about publications. Do you think there's anything wrong with getting sharp and incisive comments from other philosophers that lead you to improve the work before sending it out? If you do, then we have a real disagreement here. And I think you'd be in the minority: Many (most?) philosophical articles credit others with discussion, suggestions, and feedback. If you agree there's nothing wrong with getting such feedback, why does it matter so much if the feedback is human?
With respect to publications, I do value feedback (referee #2 excepted!), and I don’t think I have anything against AI feedback in principle. Both human and AI feedback can reach a level where you realize that you now have a co-author. When it is a human co-author there is the pleasure of jointly working out our understanding of some problem or puzzle, and we are lifting each other up. That’s lacking with AI (whom am I lifting up?). So I’m less enthused about AI co-authorship.
But suppose having an AI co-author led to a better paper. No lifting each other up, no intellectual fusion, no delightful mingling of the minds -- just a better paper, in whatever sense you think of as "better". Does this provide ANY motivation for you to go that way?
I’m honestly not sure. Think about it like this: would you like to play in a band with three robots? Suppose they are really good music-making robots. Or would you rather play music with three friends, even if they are not quite as good as the robots? With the first option at some point I’d start to wonder what my contribution is. Maybe an all-robot quartet would sound better and I can just stay home.
I’d much rather play in a band with humans than robots. More fun! But—and this is one main point of my post—having fun isn’t the primary point of scholarly or scientific work.
That is true, but there is intrinsic value to making art that is more than just having fun, and I was trying to analogize that to the intrinsic value of finding truth. I’m going to think about this some more, though. I appreciate the interaction.
I've got a post coming out in the new year on why AI should be part of the peer-review process! I'm sure that will go over well among some of the academic audience.
The more that a philosopher relies on AI to write their paper, the less credit they deserve for the paper as a finished product (since the less of a causal contribution they make to it). This isn't a point unique to AI: the more your dissertation advisor helps you write your paper, the less credit you deserve. So one possible result of going down this path is that philosophers will deserve less and less credit for their publications. You can imagine that changing tenure and promotion decisions, but also various other things connected to credit. By the rationale of the post, maybe this is a price worth paying... You rack up 13 Ethics publications, and nobody gives you much credit for any of them (the credit largely goes to ChatGPT), but maybe it's worth it for the sake of producing the best papers possible and advancing truth.
One consideration, though. Suppose you get ½ credit for a paper written with AI help (or with your advisor’s help). Still, with this help, you might produce twice the number of papers in the same time, so it’s a wash …
I disagree! My view is that a virtuous epistemic agent should want to be an active producer of epistemic goods, not just a passive consumer. They should want not just to have true beliefs, but to deserve credit for the production of true beliefs, which involves making a substantial causal contribution to them. Still, journals might not care about cultivating epistemically virtuous authors. "We just want to spread true beliefs, and even if the authors are epistemic duds who deserve basically no epistemic credit for the papers we publish (because almost all the credit should got o ChatGPT), so be it!" they might declare.
Re: the analogy of using the second-best statistical test, that feels like it occupies an importantly different level of generality from “using AI”. Presumably in the stats case there’s some kind of consensus on why the best test is best and it’s likely formulated in a rather specific way (eg, mixed effects models are now preferred to an ANOVA because you can better account for multiple sources of nested variance, reduce false positives, etc).
Correspondingly we might ask more specific questions about responsible use of AI: is it irresponsible to use or not use for programming help? For writing? For hypothesis generation? And presumably the answer should depend primarily in each case on both the risks and the efficacy gains (in the same way it does with the stats example). I think that’s all consistent with what you’re arguing, it just feels relevant to me that the stats analogy involves a much more specific, targeted use case.
Re: risks, one additional counter argument could be that the increased use of AI will lead to something like “epistemic gaps” in scientific literature that will be hard to identify in any given case but which contribute, long term, to some decline in research quality or utility. But that’s totally speculative and by definition hard to falsify—basically a version of Chesterton’s fence applied to adopting this new tool.
To be clear, I think LLMs specifically are a great tool for scientific research. I use Claude regularly for programming help and I’ve also done research on using LLMs to obtain psycholinguistic norms/ratings.
Yeah this is making me think of other comparisons - is it “irresponsible” to try to publish a paper you haven’t given as a talk at a conference to get feedback on?
These days I try to credit the R package I used to run a particular analysis. I don’t know if there’s a clear line, but if your contribution depended on some tool/resource developed by someone else I think it makes sense to credit it. I’m not sure how tools like ChatGPT fit in here exactly or for what purposes (tightening the language in an abstract vs generating hypotheses).
On the other hand, I don’t credit Donald Knuth and LaTeX for everything I write, and most people don’t have acknowledgments for the Microsoft corporation in their work.
That's a good point. I wonder whether there's some set of fuzzy descriptive criteria one could identify here that people seem to follow within a given field—I assume there must be someone working on this kind of question (maybe in science and technology studies?).
Using AI as an academic is kind of fraudulent. Way better to develop one's human intelligence and not artificial.
One should be conversant with its use, and vigilant of its failings. But relying on another entity to do work on your behalf, especially if you didn't program it, is pretty suspect.
AI definitely has uses. Drudgery is a good place to use it. But the hype is misplaced.
Why fraudulent? This implies deception, and I’m totally against that. Like I say in my post, if you use AI (or get substantial help from another person), you should say so.
The important distinction here to my mind is whether you are engaging with the AI in a task that you can think of as weightlifting or forklifting (I heard this distinction elsewhere). The basic idea is whether your main goal is to get the job done by any means necessary, or if you're engaging in some sort of deliberate practice to increase your skills or knowledge. So your argument applies mostly to things that are like forklifting...you just have to get the job done. But when dealing with students using AI to sidestep aspects of assignments that were designed to help them develop their mental muscles, then we probably need to approach it a bit differently.
As a philosopher I’m of course interested in finding out what’s true, but I am also interested in developing my own point of view, understanding what I think about certain topics, and engaging in productive conversation with others through the journals. Those things have value too. I’m not going to outsource my own thinking, even if the subcontractor is better at it than I am.
I like this, but two ideas are blurred together.
1. I agree that it's useful and important to develop an understanding of certain things, and that can't be outsourced.
2. But I'm talking about publications. Do you think there's anything wrong with getting sharp and incisive comments from other philosophers that lead you to improve the work before sending it out? If you do, then we have a real disagreement here. And I think you'd be in the minority: Many (most?) philosophical articles credit others with discussion, suggestions, and feedback. If you agree there's nothing wrong with getting such feedback, why does it matter so much if the feedback is human?
With respect to publications, I do value feedback (referee #2 excepted!), and I don’t think I have anything against AI feedback in principle. Both human and AI feedback can reach a level where you realize that you now have a co-author. When it is a human co-author there is the pleasure of jointly working out our understanding of some problem or puzzle, and we are lifting each other up. That’s lacking with AI (whom am I lifting up?). So I’m less enthused about AI co-authorship.
But suppose having an AI co-author led to a better paper. No lifting each other up, no intellectual fusion, no delightful mingling of the minds -- just a better paper, in whatever sense you think of as "better". Does this provide ANY motivation for you to go that way?
I’m honestly not sure. Think about it like this: would you like to play in a band with three robots? Suppose they are really good music-making robots. Or would you rather play music with three friends, even if they are not quite as good as the robots? With the first option at some point I’d start to wonder what my contribution is. Maybe an all-robot quartet would sound better and I can just stay home.
I’d much rather play in a band with humans than robots. More fun! But—and this is one main point of my post—having fun isn’t the primary point of scholarly or scientific work.
That is true, but there is intrinsic value to making art that is more than just having fun, and I was trying to analogize that to the intrinsic value of finding truth. I’m going to think about this some more, though. I appreciate the interaction.
I love this post!
I've got a post coming out in the new year on why AI should be part of the peer-review process! I'm sure that will go over well among some of the academic audience.
The more that a philosopher relies on AI to write their paper, the less credit they deserve for the paper as a finished product (since the less of a causal contribution they make to it). This isn't a point unique to AI: the more your dissertation advisor helps you write your paper, the less credit you deserve. So one possible result of going down this path is that philosophers will deserve less and less credit for their publications. You can imagine that changing tenure and promotion decisions, but also various other things connected to credit. By the rationale of the post, maybe this is a price worth paying... You rack up 13 Ethics publications, and nobody gives you much credit for any of them (the credit largely goes to ChatGPT), but maybe it's worth it for the sake of producing the best papers possible and advancing truth.
I agree with all of that.
One consideration, though. Suppose you get ½ credit for a paper written with AI help (or with your advisor’s help). Still, with this help, you might produce twice the number of papers in the same time, so it’s a wash …
Credit may be what people who want a job care about, but it’s not the point of the endeavor!
I disagree! My view is that a virtuous epistemic agent should want to be an active producer of epistemic goods, not just a passive consumer. They should want not just to have true beliefs, but to deserve credit for the production of true beliefs, which involves making a substantial causal contribution to them. Still, journals might not care about cultivating epistemically virtuous authors. "We just want to spread true beliefs, and even if the authors are epistemic duds who deserve basically no epistemic credit for the papers we publish (because almost all the credit should got o ChatGPT), so be it!" they might declare.
These are good points.
Re: the analogy of using the second-best statistical test, that feels like it occupies an importantly different level of generality from “using AI”. Presumably in the stats case there’s some kind of consensus on why the best test is best and it’s likely formulated in a rather specific way (eg, mixed effects models are now preferred to an ANOVA because you can better account for multiple sources of nested variance, reduce false positives, etc).
Correspondingly we might ask more specific questions about responsible use of AI: is it irresponsible to use or not use for programming help? For writing? For hypothesis generation? And presumably the answer should depend primarily in each case on both the risks and the efficacy gains (in the same way it does with the stats example). I think that’s all consistent with what you’re arguing, it just feels relevant to me that the stats analogy involves a much more specific, targeted use case.
Re: risks, one additional counter argument could be that the increased use of AI will lead to something like “epistemic gaps” in scientific literature that will be hard to identify in any given case but which contribute, long term, to some decline in research quality or utility. But that’s totally speculative and by definition hard to falsify—basically a version of Chesterton’s fence applied to adopting this new tool.
To be clear, I think LLMs specifically are a great tool for scientific research. I use Claude regularly for programming help and I’ve also done research on using LLMs to obtain psycholinguistic norms/ratings.
Yeah this is making me think of other comparisons - is it “irresponsible” to try to publish a paper you haven’t given as a talk at a conference to get feedback on?
The people in the comments all seem to assume you would be doing something fraudulent with AI.
acknowledge the help of the AI—it’s dishonest to take credit for work that’s not your own
I wonder -- I don't credit a thesaurus or calculator -- what, specifically, is different here (unless directly quoting)?
These days I try to credit the R package I used to run a particular analysis. I don’t know if there’s a clear line, but if your contribution depended on some tool/resource developed by someone else I think it makes sense to credit it. I’m not sure how tools like ChatGPT fit in here exactly or for what purposes (tightening the language in an abstract vs generating hypotheses).
On the other hand, I don’t credit Donald Knuth and LaTeX for everything I write, and most people don’t have acknowledgments for the Microsoft corporation in their work.
That's a good point. I wonder whether there's some set of fuzzy descriptive criteria one could identify here that people seem to follow within a given field—I assume there must be someone working on this kind of question (maybe in science and technology studies?).
Is it irresponsible to use AI to summarize / normal-language-ize academic papers?
;-)
Using AI as an academic is kind of fraudulent. Way better to develop one's human intelligence and not artificial.
One should be conversant with its use, and vigilant of its failings. But relying on another entity to do work on your behalf, especially if you didn't program it, is pretty suspect.
AI definitely has uses. Drudgery is a good place to use it. But the hype is misplaced.
Why fraudulent? This implies deception, and I’m totally against that. Like I say in my post, if you use AI (or get substantial help from another person), you should say so.
Non-disclosure is one side of the fraud.
The other is the false equivalence to personal endeavour.
“ relying on another entity to do work on your behalf, especially if you didn't program it, is pretty suspect.”
That sounds like an argument that it is pretty suspect to read a paper someone else wrote, especially if they’re not a grad student you helped train!