Also, don't use AI to translate into a language you can't read back. It glosses over assumptions you didn't know you made, and the output might not mean what you intended.
Once upon a time the word processor was invented, and it made it so much easier to arrange your words on paper. iIf bits were wrong, you could just delete them, or copy and paste them across pages. It was actually pretty amazing what you could do; especially if you didn't mind dot-matrix type on fan-fold paper. Of course if you wanted to make a better impression, you'd type it on a typewriter, or better yet, hand-calligraph your writing with a fountain pen.
So LLMs allow you to work at the speed of reading, if not faster. So you can try a paragraph here, completely rewrite the tone. Start a chapter in 1PP and just have it rewritten to 3PP. And sofort and so on. The number of new transformations you can do is endless.
What do a lot of people do? Write a one line prompt and show everyone the oneshot result.
Ok fine, sometimes you don't need to write amazing prose. But you can also be like the early writers who adopted the word processor. If you put the same amount of elbow-grease into using an LLM as you did writing before, you can get some pretty cool results.
Once upon a time the word processor was invented, and it made it so much easier to arrange your words on paper.
It’s easier to rearrange and rethink and tinker. Hard to imagine now but it was more efficient in the days when you would have to pencil out a memo and have someone type it up, you would make corrections and the final copy would be done in a couple passes. This has been studied, efficiency has actually gone down, in favor of immediacy and direct control.
What it frees you from is organizing your thoughts ahead of time, which takes practice and discipline. Using an LLM is just taking that further, you can avoid organizing your thoughts and ideas a bit more.
If someone uses LLM to help wording their idea in a way that's easier to understand, I am fine with it as long as they don't copy-paste it verbatim into their blogpost.
I am getting a little ranty here, but the usual LLM-isms like "not this, but that" or "that's the real footnote here" simply add zero value to the text, and I can't imagine anyone who has proofread the LLM-generated text even once will opt to keep those sloppy paragraphs. If I see them, I can't help but to think that the author had oneshotted the text. And it strongly suggests to me that the author has put zero effort into their work.
I disagree, the problem is the tool. Generating text instead of thinking about what text to use explicitly is not writing, and it's not worthy of someone else reading it.
Fundamental to exchanging ideas is discovering which ideas should be exchanged and how to express them. The process of writing itself is that exercise. If you use a tool to outsource the thinking then you're not thinking.
I definitely think that "not thinking about what you're writing" is a big danger with AI-generated text, but it's not a given. If you generate a block of text and then go through and edit it to better reflect your ideas and voice - that's the thinking process in action. It's also entirely possible to generate slop by manually typing every word - see any corporate communication ever.
You will NEVER be a good to great writer if you use AI to seed your writing and then edit it.
_Everything_ AI generates, is generalized slop. All of your ideas will be boring and derivative. Mediocre writers will be improved, but the best would only have their ability to think dulled.
Just think through it from the perspective that AI is generating art for you instead of writing. What would all art look like if good artists used it for ideas and "edited" it? It would look like generic, derivative shit. A perpetual crutch that the person can never abandon.
I just fundamentally do not agree with you. If you are editing AI generated text to "better reflect your ideas and voice" you are still not using your ideas or your voice. There's no 'thinking process in action' if you've delegated the hardest part of the task to a text predictor!
It really bothers me that people think it's ok to use AI as the starting point for writing. In my mind, it's the worst thing you can do. It poisons the entire effort, and frankly it's disrespectful to give it to anyone to read. Stop doing it!
Well said, the issue being, the form factor of many AI products disincentivises this behaviour. To give an example, using a CLI tool with a frontier model to write a blog (actually fairly common), you have to re-open it in another editor, potentially reformat it or convert MD>DOCX, etc etc. There's a lot of noise and mess, and people naturally tend towards "not bother" and 1-shot some "amazing" prompt (because the value of their elbow grease is disproportionately low, unless they actually have something to say- many do not).
I use it to write in German, because my German sucks.
I first write the thing myself, then feed it through Deepl Write to see how the AI would write it. It's been very helpful.
I write everything else myself. However I don't know how I feel about spending my time on Earth typing personal responses to AI-generated messages. Do those people deserve my time and energy?
AI for proofreading/spelling correction and reordering works quite well. My words, but perhaps structured in a way which makes more sense, with sentiment replaced by synonyms.
Basically an automatic "second-pass" which I would've caught had I re-read it, but automatically.
- You can use AI to look through docs and do research.
- You can use AI to structure your argument.
- You can NOT use AI to actually write the prose.
- You can use AI to proofread, especially for how effectively you've communicated.
I don't know, man, that sounds a lot like using AI to write. Your writing probably says "load-bearing" less than Claude's outputs, but I'm not sure it's much less AI.
Reading through docs and doing research: of course. They're like much better search engines in that regard. It would be silly not to use them. Obviously, you need to review their search results against their sources.
Structuring arguments: bad idea. Here you're having the model do your thinking for you. The problems that occur with having it write text recur at a macro level; too-obvious patterns. Readers just want to know what the prompt was.
Writing the prose: obviously not.
Proofreading: I think this works pretty great, as long as you have a structure to how you're doing it. "How do I make this better or sharper": bad, you're having the model structure your arguments for you. But for a predefined rubric of stylistic things --- writing you know how to do, that's just tedious to check manually? Hard to see a downside.
Most people apparently still don't get that using AI for mere proofreading is the same as using it as a mere knowledge base summary tool. Instead of proofreading, have it be adversarial. Let it try to take apart your argument. The latest generation is extremely good at calling out half-truths and circumstantial evidence across many fields. These days I would not dare to put anything in front of a human peer that hasn't passed at least an AI sanity check review.
Giving the compiling evidence of how addictive generative AI is actually, it actually makes perfect sense that people are looking for strategies to excuse their AI-usage. I think no matter the strategy (and given AI is actually as addictive as evidence are suggesting), chances are the usage patterns will all converge to “Just use AI dummy“.
This reminds me a lot of smokers who all have a great strategy beat the nicotine addiction. Only smoke on the weekends when out partying with friends, only smoke to use the extra sense of energy, only smoke to suppress my appetite, go to the gym 5 hours a week to offset the negative health impacts of smoking etc. etc.
In reality most smokers will converge to about a pack a day.
The likes of Sir Walter Scott, Peter Ackroyd, Stephen King, Tim Ferris, Robert Greene, Tucker Max, Catherine Asaro, Neil Gaiman, Charlaine Harris, Nancy Holder etc... all rely heavily on research assistants in various capacities including proofreading.
Honest question - where does an Author like the above place in your authenticity framework?
Writing requires thinking, don't let an AI do the thinking for you.
Okay, but reading also requires substantial thinking. Moreover, we can say the same about, say, coding. And I am sure there are people who will say, yes, don't use AI to code. But I do, and the results are amazing, and I still think very deeply: in fact, I spend more time with AI coding (and thinking) than before as I do not get hamstrung on, how do I convert this Word doc to PDF in code again? I spend more time in higher order thinking. Same with when I read text written by an AI. I don't believe that writing is any more sacrosanct that coding. And reading and adjusting AI output requires substantial thinking.
Anyone who has learned a language knows this anecdotally. The linguistic structures need to be marshalled by active cognition (editing and writing). Merely reading and watching is not enough.
Perhaps not 1:1, but, personally, I can read for much longer than I can write. And so I'd argue that this duration increase matches any deeper thought that comes with shorter writing bursts.
I've been watching chess videos for many years but my own chess playing is just recreational.
Writing/programming as a specialization of just going through the damn thing is actually sacrosanct IMO. Spectatorship as a generalization of reading is second-class. You do become a worse programmer as you move to "higher order thinking", it just matters less in a world where LLMs exist.
And reading and adjusting AI output requires substantial thinking.
It does, but less of that thinking translates to skills transferred. What amount of the creativity and magic of Tolkien transferred to his editor? I'm sure it took substantial thinking to edit Tolkien's work.
I said this once in my recent "Trustworthy AI" class that... "I think writing with AI is one of the most detrimental things you can do".
The reaction was pretty much silence and most people probably thought I was some angry, arrogant, anti-ai purist... which isn't the case. It can be acceptable to use a language model in code generation but requires new forms of discipline and tooling.
But for for just regular old writing... Should never, ever be generated. I'll likely never change that stance.
I'm on version 6 of a writing an agent voice, style, tone, and orientation guide I have been developing over the course of the past year. Every time the agent writes something using the guide, I edit it and then update the guide where needed. Slowly, the agent is beginning to sound eerily close to my natural writing voice. No, I didn't use it for this comment :)
That's not the argument in the article. Not only that but coding is deterministic up to a certain point. Once the project becomes complex, it becomes harder and harder to account for all edge cases. Sometimes it requires heuristics that are not deterministic, etc. There are infinite ways to implement the same requirements.
That argument is like saying that weather is deterministic. It is if you know every single variable, but that's impossible.
Just this morning I used Claude to build an "omit needless words" app, which lets me paste in text and then marks up that text with strikes through the words that I can leave out.
I used it to edit a document I'm working on, where I accepted about a third of its suggestions. I feel pretty good about it.
If you have a Claude account you should be able to access the artifact I built here: https://claude.ai/artifact/RK7XfnaoxVV1Uji84ETaLr - it uses "Claudeception" - the feature of Claude artifacts that lets them use Claude prompts - so it will be billed against your Claude account (at a cost of probably a fraction of a cent per run.)
While I do agree with the premise of the article, if find this way of thinking applicable for writing code as well. Your code is meant to not only be read by machines, but also other fellow humans. Writing code requires substantial amount of thinking as well. Shouldn't we write code without AI as well?
Writing code requires substantial amount of thinking as well. Shouldn't we write code without AI as well?
You absolutely should. Using an LLM to write your code for you is not a good idea. It produces bad code, and it also robs you of understanding which will be valuable down the line.
I'm not sure where people are going with using LLMs for research on a topic.
LLMs construct documents like a middle manager trying to get you fired, so it's a bad idea to get a system to try to research something for you. Anytime I've used the ol' panopticon-homunculus for something applied and niche I always follow the source linked to verify it. And the source is vague and generally unverifiable. Humans can actually link other documents that are actually readable to a greater degree.
I think a large part of the blame is the dataset for large scale LLMs being thoroughly and disproportionality poisoned with popular media sites like Reddit.
Also, don't use AI to translate into a language you can't read back. It glosses over assumptions you didn't know you made, and the output might not mean what you intended.
this SPECIALLY for arabic the shit I see everyday
[delayed]
Once upon a time the word processor was invented, and it made it so much easier to arrange your words on paper. iIf bits were wrong, you could just delete them, or copy and paste them across pages. It was actually pretty amazing what you could do; especially if you didn't mind dot-matrix type on fan-fold paper. Of course if you wanted to make a better impression, you'd type it on a typewriter, or better yet, hand-calligraph your writing with a fountain pen.
So LLMs allow you to work at the speed of reading, if not faster. So you can try a paragraph here, completely rewrite the tone. Start a chapter in 1PP and just have it rewritten to 3PP. And sofort and so on. The number of new transformations you can do is endless.
What do a lot of people do? Write a one line prompt and show everyone the oneshot result.
Ok fine, sometimes you don't need to write amazing prose. But you can also be like the early writers who adopted the word processor. If you put the same amount of elbow-grease into using an LLM as you did writing before, you can get some pretty cool results.
Why do people feel the need to invent the past that never existed?
I lived in that past myself, what are you thinking about?
It’s easier to rearrange and rethink and tinker. Hard to imagine now but it was more efficient in the days when you would have to pencil out a memo and have someone type it up, you would make corrections and the final copy would be done in a couple passes. This has been studied, efficiency has actually gone down, in favor of immediacy and direct control.
What it frees you from is organizing your thoughts ahead of time, which takes practice and discipline. Using an LLM is just taking that further, you can avoid organizing your thoughts and ideas a bit more.
You nailed it on what I've always wanted to say.
If someone uses LLM to help wording their idea in a way that's easier to understand, I am fine with it as long as they don't copy-paste it verbatim into their blogpost.
I am getting a little ranty here, but the usual LLM-isms like "not this, but that" or "that's the real footnote here" simply add zero value to the text, and I can't imagine anyone who has proofread the LLM-generated text even once will opt to keep those sloppy paragraphs. If I see them, I can't help but to think that the author had oneshotted the text. And it strongly suggests to me that the author has put zero effort into their work.
Agree completely. The problem is not the tool, it's all the pointless filler (or even hallucinations) that the tool generates that people leave in.
I disagree, the problem is the tool. Generating text instead of thinking about what text to use explicitly is not writing, and it's not worthy of someone else reading it.
Fundamental to exchanging ideas is discovering which ideas should be exchanged and how to express them. The process of writing itself is that exercise. If you use a tool to outsource the thinking then you're not thinking.
I definitely think that "not thinking about what you're writing" is a big danger with AI-generated text, but it's not a given. If you generate a block of text and then go through and edit it to better reflect your ideas and voice - that's the thinking process in action. It's also entirely possible to generate slop by manually typing every word - see any corporate communication ever.
You will NEVER be a good to great writer if you use AI to seed your writing and then edit it.
_Everything_ AI generates, is generalized slop. All of your ideas will be boring and derivative. Mediocre writers will be improved, but the best would only have their ability to think dulled.
Just think through it from the perspective that AI is generating art for you instead of writing. What would all art look like if good artists used it for ideas and "edited" it? It would look like generic, derivative shit. A perpetual crutch that the person can never abandon.
I just fundamentally do not agree with you. If you are editing AI generated text to "better reflect your ideas and voice" you are still not using your ideas or your voice. There's no 'thinking process in action' if you've delegated the hardest part of the task to a text predictor!
It really bothers me that people think it's ok to use AI as the starting point for writing. In my mind, it's the worst thing you can do. It poisons the entire effort, and frankly it's disrespectful to give it to anyone to read. Stop doing it!
Well said, the issue being, the form factor of many AI products disincentivises this behaviour. To give an example, using a CLI tool with a frontier model to write a blog (actually fairly common), you have to re-open it in another editor, potentially reformat it or convert MD>DOCX, etc etc. There's a lot of noise and mess, and people naturally tend towards "not bother" and 1-shot some "amazing" prompt (because the value of their elbow grease is disproportionately low, unless they actually have something to say- many do not).
Are people really publishing blogs in docx format?
I use it to write in German, because my German sucks.
I first write the thing myself, then feed it through Deepl Write to see how the AI would write it. It's been very helpful.
I write everything else myself. However I don't know how I feel about spending my time on Earth typing personal responses to AI-generated messages. Do those people deserve my time and energy?
Similar recent discussion: https://news.ycombinator.com/item?id=49767937
AI for proofreading/spelling correction and reordering works quite well. My words, but perhaps structured in a way which makes more sense, with sentiment replaced by synonyms.
Basically an automatic "second-pass" which I would've caught had I re-read it, but automatically.
Proofreading yes, automatic "corrections" no
- why stop at writing? put this advice for coding too
- sure its good to ask AI feedback about your module or code review or identify vulnerabilities or better ways of doing your existing code
- but maybe stop asking AI to generate entire projects from scratch?
So let me get this straight:
- You can use AI to look through docs and do research.
- You can use AI to structure your argument.
- You can NOT use AI to actually write the prose.
- You can use AI to proofread, especially for how effectively you've communicated.
I don't know, man, that sounds a lot like using AI to write. Your writing probably says "load-bearing" less than Claude's outputs, but I'm not sure it's much less AI.
Reading through docs and doing research: of course. They're like much better search engines in that regard. It would be silly not to use them. Obviously, you need to review their search results against their sources.
Structuring arguments: bad idea. Here you're having the model do your thinking for you. The problems that occur with having it write text recur at a macro level; too-obvious patterns. Readers just want to know what the prompt was.
Writing the prose: obviously not.
Proofreading: I think this works pretty great, as long as you have a structure to how you're doing it. "How do I make this better or sharper": bad, you're having the model structure your arguments for you. But for a predefined rubric of stylistic things --- writing you know how to do, that's just tedious to check manually? Hard to see a downside.
Most people apparently still don't get that using AI for mere proofreading is the same as using it as a mere knowledge base summary tool. Instead of proofreading, have it be adversarial. Let it try to take apart your argument. The latest generation is extremely good at calling out half-truths and circumstantial evidence across many fields. These days I would not dare to put anything in front of a human peer that hasn't passed at least an AI sanity check review.
They are much worse at citing sources compared to search engines
If you can't find the source and verify it, don't use it. Seems simple.
I didn't see in the article where he recommended AI to structure an argument? He did suggest it can be helpful for structuring data.
Giving the compiling evidence of how addictive generative AI is actually, it actually makes perfect sense that people are looking for strategies to excuse their AI-usage. I think no matter the strategy (and given AI is actually as addictive as evidence are suggesting), chances are the usage patterns will all converge to “Just use AI dummy“.
This reminds me a lot of smokers who all have a great strategy beat the nicotine addiction. Only smoke on the weekends when out partying with friends, only smoke to use the extra sense of energy, only smoke to suppress my appetite, go to the gym 5 hours a week to offset the negative health impacts of smoking etc. etc.
In reality most smokers will converge to about a pack a day.
The likes of Sir Walter Scott, Peter Ackroyd, Stephen King, Tim Ferris, Robert Greene, Tucker Max, Catherine Asaro, Neil Gaiman, Charlaine Harris, Nancy Holder etc... all rely heavily on research assistants in various capacities including proofreading.
Honest question - where does an Author like the above place in your authenticity framework?
Okay, but reading also requires substantial thinking. Moreover, we can say the same about, say, coding. And I am sure there are people who will say, yes, don't use AI to code. But I do, and the results are amazing, and I still think very deeply: in fact, I spend more time with AI coding (and thinking) than before as I do not get hamstrung on, how do I convert this Word doc to PDF in code again? I spend more time in higher order thinking. Same with when I read text written by an AI. I don't believe that writing is any more sacrosanct that coding. And reading and adjusting AI output requires substantial thinking.
We have copious evidence for behaviors like note taking and writing creates deeper thinking and retention that passively watching / reading
https://www.scientificamerican.com/article/why-writing-by-ha...
Anyone who has learned a language knows this anecdotally. The linguistic structures need to be marshalled by active cognition (editing and writing). Merely reading and watching is not enough.
I don't think anyone would argue reading a book takes as much thinking as writing one…
Perhaps not 1:1, but, personally, I can read for much longer than I can write. And so I'd argue that this duration increase matches any deeper thought that comes with shorter writing bursts.
I've been watching chess videos for many years but my own chess playing is just recreational.
Writing/programming as a specialization of just going through the damn thing is actually sacrosanct IMO. Spectatorship as a generalization of reading is second-class. You do become a worse programmer as you move to "higher order thinking", it just matters less in a world where LLMs exist.
It does, but less of that thinking translates to skills transferred. What amount of the creativity and magic of Tolkien transferred to his editor? I'm sure it took substantial thinking to edit Tolkien's work.
I said this once in my recent "Trustworthy AI" class that... "I think writing with AI is one of the most detrimental things you can do".
The reaction was pretty much silence and most people probably thought I was some angry, arrogant, anti-ai purist... which isn't the case. It can be acceptable to use a language model in code generation but requires new forms of discipline and tooling.
But for for just regular old writing... Should never, ever be generated. I'll likely never change that stance.
I'm on version 6 of a writing an agent voice, style, tone, and orientation guide I have been developing over the course of the past year. Every time the agent writes something using the guide, I edit it and then update the guide where needed. Slowly, the agent is beginning to sound eerily close to my natural writing voice. No, I didn't use it for this comment :)
I agree. Writing manually and thoughtfully and then letting the AI figure out the nitty gritty implementation works very well.
My brain immediately went to "I wonder how many people got this article and used AI to summarize it for them."
The article opens with
And then the author goes on to admit that they use AI for coding. Does coding not require thinking or what?
I agree that we shouldn't be delegating thinking to AI, but stopping at writing seems disingenuous.
Code is deterministic, and language is not. If I write:
total = 0 for x in [1, 2, 3]: total += x
…nobody is going to argue with me that “total” is anything but 7.
But language is different. What you perceive and what I perceive from the written word can be completely different (e.g https://youtube.com/watch?v=naleynXS7yo&ra=m )
That's not the argument in the article. Not only that but coding is deterministic up to a certain point. Once the project becomes complex, it becomes harder and harder to account for all edge cases. Sometimes it requires heuristics that are not deterministic, etc. There are infinite ways to implement the same requirements.
That argument is like saying that weather is deterministic. It is if you know every single variable, but that's impossible.
Yes but on the sliding scale of how deterministic is this task- writing, not very. coding, can execute and write some tests (even if gamed/bad).
Just this morning I used Claude to build an "omit needless words" app, which lets me paste in text and then marks up that text with strikes through the words that I can leave out.
I used it to edit a document I'm working on, where I accepted about a third of its suggestions. I feel pretty good about it.
If you have a Claude account you should be able to access the artifact I built here: https://claude.ai/artifact/RK7XfnaoxVV1Uji84ETaLr - it uses "Claudeception" - the feature of Claude artifacts that lets them use Claude prompts - so it will be billed against your Claude account (at a cost of probably a fraction of a cent per run.)
This is a neat workflow. Incentivises you to proactively think about your writing, even as you cut it.
While I do agree with the premise of the article, if find this way of thinking applicable for writing code as well. Your code is meant to not only be read by machines, but also other fellow humans. Writing code requires substantial amount of thinking as well. Shouldn't we write code without AI as well?
If the point of the code is to be read, maybe.
I don't write code for my colleague's pleasure, I do it to solve a problem as fast and efficiently as possible.
I write code to be read by just one guy.
He’s five years older, a bit more tired than me, more going on in his life. Easily annoyed by bad code.
Weirdly enough he has exactly the same name and birthday as me.
You absolutely should. Using an LLM to write your code for you is not a good idea. It produces bad code, and it also robs you of understanding which will be valuable down the line.
Here is a good explanation in a deeper way of why using AI to write is not a good thing
https://markgreville.ie/2024/12/10/generative-ai-is-digital-...
I'm not sure where people are going with using LLMs for research on a topic.
LLMs construct documents like a middle manager trying to get you fired, so it's a bad idea to get a system to try to research something for you. Anytime I've used the ol' panopticon-homunculus for something applied and niche I always follow the source linked to verify it. And the source is vague and generally unverifiable. Humans can actually link other documents that are actually readable to a greater degree.
I think a large part of the blame is the dataset for large scale LLMs being thoroughly and disproportionality poisoned with popular media sites like Reddit.
Indeed, even the best models output needs to be checked thoroughly