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This is the best articulation I've seen of why simply reviewing and copy-editing does not provide remotely the same value as writing from scratch. I spent a considerable amount of time over the past two weeks reviewing and improving a work document that was the output of an LLM. Given the number of people involved and the final level of effort, I'm firmly convinced that writing it manually would have been faster and resulted in a higher quality product. Getting the wording right matters.
Why would you think that asking someone else (that is, another human) to write something (and then reviewing it) is the same thing as writing it yourself?
You may trust the other writer's opinions and knowledge, but it will not have the same tone, structure, word choice, understanding, or narrative flow as it would if you were to write it yourself.
And when it's an LLM, you should not trust it's "opinions" and "knowledge", because it does not have either of those things. The appearance of those things is just that, an appearance.
But in professional settings, a lot more of the informativeness is about the author, and a lot more of the persuasiveness is I'm worth your time and money. So, if the author is an LLM, and obviously so, what exactly are you informing your audience of (about yourself), and what are you persuading them to do (with your article).
I think we now know.
Not that it's necessarily better but it's the kind of thing an editor might pick up and so why would you reject the advice if it's a machine giving it rather than a human?
See also this existing comment: https://news.ycombinator.com/item?id=49768564, which I completely agree with and which is complementary to the above root comment.
Don’t use AI to write things that you are producing for someone else to consume.
I'm not saying you should never do this: our time is valuable, and we shouldn't spend it on things that are not genuinely worthwhile to us if we can help it. But we're still losing something by having an LLM write for us, even if the intended audience is just ourselves.
They can be broken and jumbled, or terse AF, or combine to be Pulitzer-quality prose. Either way: I want to consume their own unique human expression of a concept.
There's value in raw human expression, including in the missteps.
If I instead want the regurgitated waggyings of a bot, then: I know how to get that on my own.
We've all got web browsers and pocket supercomputers. We've all (well, most of us) been alive and aware of LLMs since their recent rise from infancy.
It's a no-brainer for us to paste some paragraphs into our favorite chatbot and get a summary or an artificial expansion or whatever else we wish to have. If that's what our goal is, then we can do that on a whim -- and we can still retain the original expression.
But doing it on our behalf is deleterious, unsettling, and unhelpful. It has negative value to the beholder.
Elsewhere it’s painful and irksome when you didn’t ask for it
The same is true if the thing they both want is a stale cupcake bought from a gas station. But this still doesn't mean that person B wants to be presented with person A's stale thing, because the overhead of the social transaction isn't worth the object. Which is to say, it makes a terrible gift.
The other difference is that, if I get AI to write something for me, I expect something AI-written. If I am writing something for you, you expect something that I wrote, not something that AI wrote.
So the intellectual responsibility is diluted to a substantial degree: The text is not the opinion of anyone who can be expected to honestly defend it. It's bullshit in the technical sense.
The LLM will always give you a full rewrite — don't use it. It always does too much, and persuading it to tone it down is a constant battle.
One of the most egregious negation issues I run into a lot is when I (or someone) makes a statement of the form: "not X" or "X is thus not true", and the AI then proceeds to interpret or summarize this as 'whatever is the opposite of X is the case'". This will cause it to go down a useless path investigating or disputing the opposite of X, which generally has no relevance or bearing on anything.
It also often very harmfully will replace your carefully chosen words with weirdly specific academic operationalizations or formalisms, then again waste huge amounts of text refuting / showing "problems" that result from that formalism, all of which again have no bearing or relevance on the original statement. An example would be you saying something like "intelligence, generally, must surely explain some of the differences in X", and then it will go "actually IQ does not correlate with X", unless you specifically tell it not to conflate psychometric IQ with intelligence generally.
Sometimes this is helpful, but the more specific / technical the domain, the more often you specifically have to prevent it from going down stupid paths that should be obvious given the expert context and wording, because it can seem almost hungry to try to catch you in some kind of insipid 'gotcha'. Much of these issues often clearly arise immediately from the first-pass "reword what the user said" part, given the reasoning traces.
If we don't want to be writers, then we have to be editors. And editing is an entirely different job and it's not an easy one. In many ways it's harder.
Especially when LLMs love writing novels when all we need is a short story or less.
Only ever use AI to make yourself think harder, and more.
I agree that being lazy about writing and simply using a short prompt or list is detrimental if you are replacing your own output but you don't have to do that and you don't have to accept any of the output either. The best chats I've had usually start with a large amount of my own writing up front, thinking through the idea, listing several alternative ideas, asking a lot of questions, jotting down related topics, etc. and then reading the resulting output and critiquing it, asking for clarification, doing my own research on it, even just discussing it with the AI and doing this for a number of turns until I feel like I've exhausted the topic in the chat. I then often take what I've shaped in my own mind from that process and write something myself, either that or take the best parts of the output and edit, rearrange, reinterpret, and add to it in order to produce something.
I guess it all comes down to whether you are actively engaging with the material, regardless if that material is the result of a Google search, pulled from a book or generated by AI. If you just read it or copy paste it and don't engage with it and think about it then it doesn't do much good.
LLMs are helpful because their idiom-list is vast and they are indefatigable and infinitely patient. You can keep iterating on a sentence and it will keep giving you fresh takes. Eventually, whether through careful steering or brute-force iteration, it will come up with something that has the right resonance. Like a word on the tip of your tongue, you recognize it when you hear it.
For me, the end result of this writing-process is often a document where much of the language first came from the agent, but the voice is recognizably mine, and I feel a clear sense of authorship. It is still my work because of the microscopic attention I paid to every word. The marble is the agent's, but the chisel and mallet are in my hands.
This expresses quite well an experience that I have sometimes had. Your first words can trap you in a box that you know isn't right, but you can't figure out how to escape.
https://www.pangram.com/history/3d55b442-d151-4490-9c71-28d0...
Writing code is thinking, AI code is often vague and wrong in hard-to-notice ways, and the (human) reader of code is the one that pays the cost for this later.
The cost/benefit analysis may still work out differently for code though...
My reason: code can be checked objectively. I can run it and confirm it works. I don't get attached to it. I don't feel pride in it (even when I write it by hand). Code just is. It's lifeless, inert, and entirely replaceable.
How do I do the equivalent for prose? How can I tell if my words "work"? Do they clearly convey my ideas to the intended audience? There's an element of subjectivity here forces me to identify personally with the prose.
Code has no such personality. I don't tie my identity or ego to code the same way I would an essay.
Running the code only confirms that it works with the precise input, in the precise environment, under the precise circumstances you run it under. It doesn’t ensure that the code is correct. Thinking through the code, on the other hand, lets you consider all possible cases. It’s the difference between experiment and (mathematical) proof.
For an objective correctness proof, using a formal language is indispensable.
Hard for me to imagine. You feel no pride in using a tool to accomplish a goal?
> Code has no such personality. I don't tie my identity or ego to code the same way I would an essay
Code certainly does have a personality. When working with teams for a while you can absolutely get a sense for which person wrote what code in a codebase, just by subtle little tells.
You may not tie your identity or ego to it, bully for you, but for me I take a lot of pride in writing clear and maintainable code that contributes to big projects in meaningful ways.
Maybe the problem with software is there's too many people who treat writing code as a mere means to an end, instead of a very important part of the process.
That said, I have a lot of situations at work where I am asked to simplify something I am an expert in or convey something for a different audience, particularly as I prepare for presentations and I do find it helpful in helping me step down my writing or work. YMMV.
I also skip words a lot and can miss that even after 2-3 editorial passes and it's very helpful at that vs. say normal spellcheck.
1. Agree writing process is essential, but just getting your thoughts down is the start.
2. Human writing is very often vague and wrong in hard to notice ways, but I would say it's more likely to be wrong in easy to notice ways, which is ... better?
3. I think it's rude to not use the best tools to convey the message most clearly and most respectfully of my time. I often use AI to help me write emails and nearly every time it provides more concise well structured versions of what I have to say. 99% of the time I'm just trying to convey a message clearly, that's all. When I write my draft there is often words I can delete or phrases that I can shorten. It's hard to spot but when you have AI point them out it's obvious. This is the role of an editor (check out Stephen King book On Writing which makes this point). Unfortunately I don't have an editor, but I have AI that helps trim the fat, get to the point and save my readers time.
If these tools are available to you and you don't use them, then I think that would be disrespectful. I don't take any solace thinking how much time and effort went into what someone wrote me. If I could save them time and have AI write or edit, and save me time reading it since it would be more concise and better structured, it's a win-win.
I would have much preferred if the rep had written a shorter document and reached out about things they were uncertain about. Instead thet wasted my and my team's time as we first tried to make sense of the document on good faith before realizing the problem.
I don't care if people use LLMs per se, but if this is functionally the result, then in this aspect of my work things would go much better if people did not use them. They are a great interface for talking to a machine, but due to the laziness they breed, they are a terrible interface for talking to other humans unless approached with a great deal of discipline.
I think you should write down your thoughts, tell it to make the points you spelled out and be concise and respectful of the reader's time and attention. When I do this, it works very well. But I agree if you just have it respond and reason it tends to often produces bad responses.
I think “cutting down on words” depends on personal writing style. AI tends to write more than I would, so I usually have the opposite problem.
The only cure: be the person people can turn to instead of the machine, whether that's helping them write or helping them become better writers. And, yeah, you'll have to do that cheaper than the AI (netted against the social cost of being the guy/gal who got caught slopping).
Anti-AI people want things to go back to the way they were before; I want a 600-pound bench. Neither are happening without expending a massive amount of effort and dealing with no small amount of sociopathic socieconomic upheaval. Decide what you want.
I think one of the underappreciated things about writing "substantive" work is that the work you see at the end isn't the first attempt. And I don't mean the first draft of the piece. I mean that almost always, writers iterate on the same topic many times, either with complete published pieces or abandoned drafts or even just conversations and sessions of unproductive daydreaming. It's a cliche that your best work typically also comes out fastest, but it's not because of divine inspiration, it's because you've whittled the big idea you actually care about down so much in your mind that you instinctively know exactly how to write it.
My experience has been that for people who don't work this way or don't write a lot, LLMs can give them this incredible feeling of leaping straight from inkling to "substantive" writing. And because they haven't built up those muscles or "taste", they don't immediately recognize that it's imprecise and hard to follow.
That's not to say they're not brilliant in their own right, just that they haven't spent a lot of time on this particular thing. Sort of like a very gifted programmer who doesn't have a ton of experience yet (speaking as someone who is gifted at nothing and frequently has to do things they're inexperienced at).
So I don't think the problem is that LLMs just write bad. It's that LLMs are so wonderfully powerful that they allow you to confidently leap forward to create something that is a little beyond your experience.
And that's why I have different reactions to heavily AI generated writing. When it feels like marketing at scale, it grosses me out. But when I feel like it's just someone who is excited to write an idea and maybe doesn't have a lot of experience doing it, I'm not judgemental. My hope is that it makes them more excited about writing, and that trying to make their next piece better will lead them inevitably to start thinking about where the last piece fell short. And if there's some slop along the way, eh, I'm not compelled to read it.
https://news.ycombinator.com/item?id=49747070
I think people are stuck in the idea that the way you "use AI to write" is to let it generate alternative words for your thoughts. That's a terrible way to write. I advocate for a rule: "any word an LLM suggests to you is disqualified, even if it's better than the word you've chosen". Nobody is vigilant enough to keep LLM word selection from bleaching out their personal style.
But LLMs can do things for language (natch) that deterministic programs can't. Those things are helpful and you should consider taking advantage of them. Here's a short list of ways an LLM can potentially improve your writing:
* It can instantly spot overused words and turns of phrase, or, better still, worthless filler and throat-clearing like "just" and "very" and "it's important to note".
* It can rescue active verbs trapped inside nouns, where sentences are wrapped in zombie verbs like "make" or "reach" or "start" or "have", carbonite-frozen verbs like "decision" or "agreement" or "distortion".
* It can match the subjects of your sentences with actual characters in the action of your story or argument, flagging all the times you accidentally nail the subject of a sentence down to some random part of the scenery. It can check to see whether the new detail each sentence adds (if it adds any at all --- something else it can check) is in the stress position of the sentence.
* It can check your transitions and flag places where the openings of sentences and paragraphs are abrupt. For that matter: it can check the topic sentences of paragraphs and the flow from graf to graf.
* It can check for passive voice, but also note the (many) instances where passive is the right call for what you're trying to say.
The model never gets tired. It generally never forgets the rules. It can instantaneously diagram out a sentence and work out an accurate model of the semantics of your writing. It's doing things you cannot do with a grammar checker.
You're not going to want to act on everything an LLM flags. LLMs have an idiosyncratic sense of style (I keep saying they write every sentence like it's the headline of a magazine article). Some of these quirks of writing will be part of your voice, and you'll need to keep them.
You're not going to want the LLM to give you alternate words and sentences. That way lies Velveeta. And many times, the LLM will flag a usage issue and your response won't be to act on the suggestion, but just to rewrite the sentence or paragraph entirely --- or, better yet: just delete it, which is an awesome feeling.
This is using an LLM as a copyeditor. I've worked with professional copyeditors, and the feeling of working with an LLM copyeditor is comparable, except that the LLM is much more thorough, and I don't feel bad about ignoring it when we disagree. This style of working doesn't allow the model to infect your writing; it's just making you better informed about the words you're choosing. I think more people should try it.
I think people massively over-rely on AI and I really worry about the consequences of this. But there is nothing baffling at all about the basic appeal, IMO.
Anyway, I completely agree. Writing isn't something to be delegated.
The problem is not new with LLMs. Businesses have been delegating writing to idiots who don't really care for the entire history of business. Authors and musicians have traded their souls for inauthentic crowd-pleasing results for about as long.
No, the problem with LLMs is that people are all using the same generic models. This only further shows that the future of LLMs is locally trained and locally run. Personal LLMs on a personal computer. Business LLMs on-prem. We will continue see them flourish in ways that generate absolutely no money whatsoever on their own, but do add marginal value when combined with a heavy dose of human creativity.
All the clueless old farts that are still alive by this point will continue to lecture the rest of us with more condescending gee whiz "whaddyaknow" and "whodathunkit" nonsense. As if they've even had their finger on the pulse since the early 2000s.
I'm genuinely not sure what you're implying here. Can you expand?