I strongly disagree, for reasons that are different from what's discussed in the thread.
It doesn't matter if LLMs can't hold a candle to some of the finest human writing. What matters is that before you become a world-renowned writer, you need to pay your bills, often for a long time. And that's what LLMs take away. All the mundane literature-adjacent works: journalism, translations, technical writing / corporate comms, copyediting.
The same goes for many other forms of art. A budding painter or a musician could support themselves off commissioned / commercial work while working on their grand opus... but now, the customers just prompt gen AI.
matherial
There may well be some writing jobs that are safe for the reasons given in this post, but that doesn't help all the writers I know who have already lost their jobs and are struggling to find work.
It's not enough that humans can tell the difference and feel an ick, there also need to be enough organizations willing to pay money for that difference. From my vantage point, there are not. It turns out that for a ton of the writing produced by companies, the quality of the prose wasn't really "load-bearing" as Claude puts it. That writing is there to occupy a space and look professional at a glance, the same way elevator music is tolerable for the duration of an elevator ride.
muvlon
This argument can be applied to anything AI does. AI can do bad writing, bad code, bad graphics and bad music.
But AI cannot (yet?) do the job of a skilled writer, coder, graphical artist and musician.
And it is the same problem every time, LLMs lack intention. That's essentially what the article is about, writers choose every word because they have something to convey. Something complex, deliberate, that can't fit in a simple prompt, a LLM can't get these nuances, it is all in the writer's head, so you get something generic, the information to do it better simply isn't there.
But it apply to other arts as well, ChatGPT flyers, Suno music, etc.. they all look and sound the same, because there is no intention behind them, besides all the technical issues, like inconsistent images and instruments blending into each others, the model just can't work with information it doesn't have, so it just generate something generic that looks like its training dataset.
And it is the same with code. Coding is not about the programming language, it is about expressing with precision what the machine has to do, and programming languages are really good at that, that's why they exist. LLMs let you use English instead, but it doesn't change the fact that everything has to be intentional, otherwise, the LLM will just put something that may or may not be what you want.
Most success stories of LLM coding are ports. Because someone already did most of the job with the original code, sometime even twice if we count the tests.
GuB-42
I have a feeling the author framed this the wrong way.
my take is - the author wanted to express that there's always a demand for human prose / writing that captures the subtleties of expression, thought & ideas. which is very true. & we can already see this e.g by people opting out of LinkedIn for it's A.I driven long posts. whereas engagement is high on X where posts are likely to be human generated.
I wouldn't say writing as a job is protected - as corporations will always take shortcuts.
dzonga
A lot of the replies are insisting AI will get better at writing with more development but I don't see it. Even if you have a mathematically perfect writing AI you still run into the same problems you would have if you handed off your writing task to someone on fiverr or something. It can't magically know what you want to say, it only has the information you gave it. A prompt complex enough where it won't get any wrong ideas has to contain as much information as the output would have.. so just write it.
unleaded
Workaday copywriting is dead (was moribund, now has been shot in the head). Prestige literary writing is zero-sum and therefore eternal, in the same way that equities trading (not formation and not business-building) is zero-sum and therefore the actual success of LLM has not given anyone a signal advantage anywhere there, because everyone else has LLM too.
curuinor
No. Below is my emotional opinion based on my own experience:
Currently the models are totally helpless with plot and emotions.
They make epistemic, logistical and temporal mistakes.
But:
They are very good in finding _your_ epistemic, logistical and temporal mistakes. They are great as adversarial reviewers. They can validate grounding. They can test voices. They can build complex parallel reconstructions representing timestamped inner monologues, dialogues and events.
A process consisting of many models representing characters + states + epistemic isolation + reviewers could be great to validate or disprove ideas.
Models can write you formal models of your writing. They can run solvers against your formal models to - again - validate and disprove ideas. Literally, you could validate your writing with TLA+, SAT solvers, queries against formal ontologies.
They can build corkboards of unimaginable complexity.
A moderately good writer who plays well as a part of human-machine writing apparatus could be a competitor even for a top-tier author.
When you write with a model, you define disciplines. You write your prose. You let your model turn your prose into formal systems and verify it. You let your model criticize you. Sometimes you let your model to polish your crude language into something sleek.
So, at current state of LLM development, writer as source of ideas and governing process is safe. Writer as a vision-expansion machine is not.
I've been very hostile to LLMs in literature. I've started to write a short novel about that. As a joke I tried to use models after half of the text was done. I've applied my engineering skills. That changed both me and my opinion. Models are awesome if you know their advantages and weaknesses.
A so-so writer with a good model and a good approach to prose development could produce epic stuff.
pshirshov
I think writing will go the way of software development. Really good writers and devs will probably thrive with AI but most of us do fairly mundane, repetitive work that will get done by AI.
I remember, when I used ChatGPT the first time to write some E-mails and other documents, I suddenly realized that I sound exactly like corporate communications or most tech writers. That made me realize that these guys are also working off templates and basically produce variations of the same thing. Same as developers do.
vjvjvjvjghv
> The stuck-in-slop state of LLM writing is not from lack of trying. AI labs already tried hard on improving prose and hit a wall. LLM giants would have loved to ship better writing capability to conquer marketing, copywriting, and publishing at zero marginal cost.
This doesn't ring true to me.
LLM prose can be greatly improved with the right prompts.
Now, prose with the right prompts may well still not be as good as a good human writer would write – but it is a lot better than what LLMs produce by default.
If the model can perform better with the right prompts, it suggest they haven't actually done everything they could in the post-training to maximise writing quality.
skissane
“Writing will remain valuable” and “writing is a safe job” are two very different claims.
AI doesn't need to write better than the best humans. It only needs to be good enough to replace a large part of the mundane paid writing that used to support writers while they developed their craft.
comments (10)
It doesn't matter if LLMs can't hold a candle to some of the finest human writing. What matters is that before you become a world-renowned writer, you need to pay your bills, often for a long time. And that's what LLMs take away. All the mundane literature-adjacent works: journalism, translations, technical writing / corporate comms, copyediting.
The same goes for many other forms of art. A budding painter or a musician could support themselves off commissioned / commercial work while working on their grand opus... but now, the customers just prompt gen AI.
matherial
It's not enough that humans can tell the difference and feel an ick, there also need to be enough organizations willing to pay money for that difference. From my vantage point, there are not. It turns out that for a ton of the writing produced by companies, the quality of the prose wasn't really "load-bearing" as Claude puts it. That writing is there to occupy a space and look professional at a glance, the same way elevator music is tolerable for the duration of an elevator ride.
muvlon
But AI cannot (yet?) do the job of a skilled writer, coder, graphical artist and musician.
And it is the same problem every time, LLMs lack intention. That's essentially what the article is about, writers choose every word because they have something to convey. Something complex, deliberate, that can't fit in a simple prompt, a LLM can't get these nuances, it is all in the writer's head, so you get something generic, the information to do it better simply isn't there.
But it apply to other arts as well, ChatGPT flyers, Suno music, etc.. they all look and sound the same, because there is no intention behind them, besides all the technical issues, like inconsistent images and instruments blending into each others, the model just can't work with information it doesn't have, so it just generate something generic that looks like its training dataset.
And it is the same with code. Coding is not about the programming language, it is about expressing with precision what the machine has to do, and programming languages are really good at that, that's why they exist. LLMs let you use English instead, but it doesn't change the fact that everything has to be intentional, otherwise, the LLM will just put something that may or may not be what you want.
Most success stories of LLM coding are ports. Because someone already did most of the job with the original code, sometime even twice if we count the tests.
GuB-42
my take is - the author wanted to express that there's always a demand for human prose / writing that captures the subtleties of expression, thought & ideas. which is very true. & we can already see this e.g by people opting out of LinkedIn for it's A.I driven long posts. whereas engagement is high on X where posts are likely to be human generated.
I wouldn't say writing as a job is protected - as corporations will always take shortcuts.
dzonga
unleaded
curuinor
Currently the models are totally helpless with plot and emotions.
They make epistemic, logistical and temporal mistakes.
But:
They are very good in finding _your_ epistemic, logistical and temporal mistakes. They are great as adversarial reviewers. They can validate grounding. They can test voices. They can build complex parallel reconstructions representing timestamped inner monologues, dialogues and events.
A process consisting of many models representing characters + states + epistemic isolation + reviewers could be great to validate or disprove ideas.
Models can write you formal models of your writing. They can run solvers against your formal models to - again - validate and disprove ideas. Literally, you could validate your writing with TLA+, SAT solvers, queries against formal ontologies.
They can build corkboards of unimaginable complexity.
A moderately good writer who plays well as a part of human-machine writing apparatus could be a competitor even for a top-tier author.
When you write with a model, you define disciplines. You write your prose. You let your model turn your prose into formal systems and verify it. You let your model criticize you. Sometimes you let your model to polish your crude language into something sleek.
So, at current state of LLM development, writer as source of ideas and governing process is safe. Writer as a vision-expansion machine is not.
I've been very hostile to LLMs in literature. I've started to write a short novel about that. As a joke I tried to use models after half of the text was done. I've applied my engineering skills. That changed both me and my opinion. Models are awesome if you know their advantages and weaknesses.
A so-so writer with a good model and a good approach to prose development could produce epic stuff.
pshirshov
I remember, when I used ChatGPT the first time to write some E-mails and other documents, I suddenly realized that I sound exactly like corporate communications or most tech writers. That made me realize that these guys are also working off templates and basically produce variations of the same thing. Same as developers do.
vjvjvjvjghv
This doesn't ring true to me.
LLM prose can be greatly improved with the right prompts.
Now, prose with the right prompts may well still not be as good as a good human writer would write – but it is a lot better than what LLMs produce by default.
If the model can perform better with the right prompts, it suggest they haven't actually done everything they could in the post-training to maximise writing quality.
skissane
AI doesn't need to write better than the best humans. It only needs to be good enough to replace a large part of the mundane paid writing that used to support writers while they developed their craft.
wainguo