The whole premise of checking for human writing is daft(mohammedshehu.com) |
The whole premise of checking for human writing is daft(mohammedshehu.com) |
Case in point, this insipid blog post which I didn't bother to read.
Wait, that wasn't the plan? Sorry, with all this fantastic new content flooding the internet, I just don't have time to read whatever this guy or his LLM are trying to say.
Well, the promise of AGI and current LLM trajectory looks like this is how it's going to be. This is part of the reason that juniors or university students feel animosity towards LLMs.
Have you looked at the recent prompts mathematicians use to disprove conjectures? One of the last ones related to graph theory was basically: continue research...enough partial results, give me a breakthrough...
Not exactly skillful prompting...
There is SO MUCH STUFF that you could read. You could read all day every day and not keep up with the human-written output in just a single sub-niche of writing within a niche sector. That being the case, you must use some heuristics to determine what should be read. Whether the entity publishing a piece felt it was worth human time to write that piece seems like a fine heuristic.
The privilege argument is so bad! We aren't doing this any more! The tyranny of edge cases is over. It ended some time in 2023. I am not going to feel obligated to read every piece of slop out there because 0.01% of authors have lost the use of their hands. Stephen Hawking somehow managed to write without AI.
From the title, I expected a different argument, that it's going to be increasingly difficult to determine. Many people have demonstrated that careful prompting can already produce prose that passes as human, and this will only increase as models get better and inevitably are trained to bypass checkers. Maybe someday we'll have novel-writing rooms where, like grandmasters coming into a tournament, the writers must relinquish all their digital tools at the door. Because it's difficult to imagine any other system that will guarantee human authenticity.
I do think that there is a gate against poorly written comments.
I don’t exactly care about whether or not the actual bits on my screen came directly from a human’s fingers on a keyboard or from an LLM, but I do care about whether or not the material is good, well-written, appropriately concise (which varies both on the content and the audience), fact-checked, and I’m sure a bunch more factors. Some humans fail at these criteria as well.
Human authorship is an imperfect proxy for quality, but saying it’s imperfect doesn’t mean that it’s worthless… quite the opposite, I’d argue. Even if there are flaws in the writing, it at least shows that the author tried, which I do personally put value on. Copy & pasting Claude output without even fact-checking… that’s inherently low effort and if that’s what I wanted to read, I’d just ask Claude myself.
I use LLMs in my workflow to varying degrees depending on the task, but their output never makes it into the wild without serious scrutiny. Sometimes their code is better than what I’d have written, which is great. Sometimes it completely misses the point and needs significant re-steering several times, to the point where it’s easier if I write it myself. For writing, I’ll happily have an LLM harness put together a document explaining a dataflow through a complex system; I ask it to include source filenames and line numbers and can do my own validation before accepting it as truth.
Are there infinitely many primes p such that p − 1 is a perfect square? In other words: Are there infinitely many primes of the form n2 + 1?
Answer: [ ]
( ) I don't know
Alright, compare the following degrees of autonomy:
- I wrote it, made sure everything's correct, let the LLM proofread it/translate it to English, and checked it afterwards
- I had brief scattered notes with no coherent idea, then threw it at an LLM to make it an article in whatever way it feels best because I don't care
- I had a three word prompt "Write about X", then a deep research agent spent ungodly amount of tokens and search and scraping requests, and put up an article (at least some grounding and it can depend on the harness quality)
- I had a three word prompt "Write about X", then a model did it in a single call with no real-life grounding at all
You're looking at my clearly generated article. Can you tell what is mine, what is collected from the web or another source by the agent, and what is sourced from the model's own knowledge? Sourcing is exactly what the generated text obfuscates.
Completely apart from that, I also hate posts that look like a 15-year-old on /r/thisisdeep, whether or not they used an LLM to wrap a lot of words around their absence-of-much-of-an-idea.
So I can hate posts on more than one axis. I hate the lack of decent writing, and I hate the lack of decent thinking.
I can make an exception for LLM translation, if the thinking is good. Even if the writing isn't perfect, it's better than LLM-generated-from-a-prompt text, because it has something with a real voice to start from.
Although there are some niche uses where LLMs assist or enhance the creative process, the vast majority of machine writing exists specifically because it takes zero effort and allows you to spam human cognition at an unprecedented scale. There is no redeeming quality to 99%+ of AI-generated LinkedIn posts, AI-generated books on Amazon, and so on.
The style-based heuristics we previously had at our disposal to filter zero-effort content no longer work here, so detecting LLM text is the next fallback.
Pangram found the breaks properly too.
LLMs are fundamentally different from other writing tools because they attempt to construct meaning in a way that is not done by the author. A main purpose of writing is to convey meaning, so LLM writing defeats that purpose.
Now though, it undercuts itself, because if the world is filled with authors using AI to express their interesting thoughts, then how come--this post included--it's always the same regurgitation and bloviation?
We know by now--have had countless examples--that people using AI to produce text do not care for the quality of that text. It's a path-of-least-resistance tool, and that's what people use it for.
This isn’t the common case. How many of the thoughts produced while working on the words have much novelty or high quality may be an open question, but it’s rare to type or handwrite 3000 words and not have any thoughts.
> Another can dictate an idea, argue with a language model for an hour, reject six drafts, rearrange the whole piece, rewrite half of it, and publish something they understand down to the final comma
Also probably not the common case. And so far my experience is that models make decent to good editors/critics, but average originators (though with remarkable breadth and sometimes outlier originations).
At any rate even if you wish to judge the idea rather than the way someone wrote it down then I still think LLMs don't help.
Because the one thing I definitely agree with, the bull of the effort behind putting an idea in writing isn't the act of writing itself.
I get this is tongue in cheek, but it's so wrong that it needs pointing out. Even if that is a thought in their head, they clearly have to have others in order to produce the text.
But in general, checking that a human wrote it is economic as much as anything else: attention is currency limited by time and energy, AI effort is abundant and therefore low value, human effort is less abundant and therefore more valued. Pyrite can look pretty but it's not what people want.
Those who favor human writing are looking for writing where the words are the product of a human mind rather than an LLM. The requirement for every character to be the product of a finger pressing a key is not something I've seen. Alternative input methods doesn't make a writing non-human. Spellcheck and probably even some amount of auto-complete are also generally considered to be fine. Anyone checking for keystrokes is using it as a proxy for human creation, not valuing the physical motion itself.
The pro-AI example is a writer spending hours tweaking a single AI output then later re-arranging and rewriting the piece before publishing. While this would probably still set off some AI-detectors, it does at least include some human effort. Presumably this effort will not be appreciated and readers will assume that the poster simply copied the response directly from their LLM of choice. It may seem a bit unfair to ignore the human effort in revising, but it's a reasonable assumption to make because almost nobody is using LLMs in this way.
Perhaps there's a reasonable amount of LLM use which would be considered a writing aid rather than a writing replacement, but the vast majority are simply mass producing slop so I sympathize with those who favor a blanket ban as a response.
But when they do that, you can tell.
Plagiarism will always be plagiarism.
When I get materials that are clearly AI generated, I look at them as if there was less effort put into it.
But that is irrational. If it was verified for accuracy, and edited for conciseness, and addresses the task at hand, does it matter?
Another thing though. How many times does it happen to you to start writing after having an idea, but scrapping it because you realize it’s wrong/bad/unhelpful. To me, quite often. But if you prompt an LLM, there is no time to have that realization.
The whole point of using AI to write for you is that you don't care to or can't be bothered to do any significant work yourself. If you care enough to do the research required to ensure all of the AI's output is accurate, that's like 80% or more of the work done right there, so why avoid the remaining 20%?
Nobody talks about using AI to gain a 20% productivity boost. They brag about 100% or even 1000%, which only makes sense if you're not doing any of that time-consuming "verification" at all.
So, yes, humans can also expand text in a mechanical way. I just don’t want to read expanded text. So really the question is “is this text expanded?”. Pre-LLM very little was. Post-LLM much is and has certain distinct flavours that are detectable.
But I’m happy to say that I also don’t like human expanded text and the content in OP certainly reads expanded. It’s like inlining functions everywhere and then writing unrelated comments around them. Not interesting.
After all, if I just want to read text there are reams of content marketing blog posts and SEO keyword concatenations that I could go read. Or to put it in a different way: SaaS dropshipping shemale singles near you this one mother found a puppy buy crypto toys cheap car loans zero down furniture sale foreclosure mesothelioma lawyers car Trump USAID ethereum get rich quick
And when you put it that way, it makes me think of steganography. That's a form of "expanding" the text, and it seems like it might be a useful way to think about the problem. Somewhere hidden in that wall of text is an actual message... but I don't want to have to go find it.
I like this “steganography” interpretation.
The craft of writing is part of the interesting part. The words you choose are important,same as brush strokes in a painting. Offloading the act of writing to llms takes away that whole part.
When it comes to something like a LinkedIn post however who cares. Everyone uses AI cause the content itself is mercenary anyway right. Thought leadership.
But I have been using Sonnet to write some Youtube narrations and I think I've discovered a kind of value that is not 'AI slop'. I already posted one of them -- about the giant pink hologram in Blade Runner 2049 -- and it's been getting thousands of views and a dozens of likes when clipped into shorts. [https://www.youtube.com/watch?v=sK-TsLQkIos]
The text is like: "The neon is pink. Her hair is blue. Her face is light. She smiles because she was made to smile, and somewhere beneath the awareness of that fact is the older, simpler, more animal truth: a face is smiling at you. Someone said your name. Someone said “you look lonely” and meant it as an invitation rather than a wound."
To me that is a kind of LLM writing that's "value above replacement". Like if I lost that Sonnet 4.6 script I wouldn't be able to get it again it was just a particular permutation of the neural network manifold that emerged from our discussion about the movie and the style I wanted etc.
That sounds cool. It's also a style of SciFi writing--clipped sentences that juxtapose images and let you put together meaning. I wonder how long this sequence can go before the LLM messes up because it has limited understanding (if you will) of the underlying meaning of the images.
I basically agree, but it's more specific than that, I think. The basic promise is that the writer believes the thing you are writing. This is a feature of human speech that is so central that Grice made it part of one of the maxims of his pragmatic theory of conversation: "do not say what you believe to be false" or "that for which you lack adequate evidence."
In writing, using generative AI destroys the pragmatic basis for this conversational maxim, because it means that a consequential number of "people" you and I talk to online are not really people at all. They're entirely artificial, and the text generated was never even read by a human, certainly not a statement of a human's actual beliefs about anything. (This isn't even a human-preferring standard, the problem with LLM text is that even the LLM doesn't believe it.) Even in cases where a human does interact with the text in some capacity before it is published, it's likely that a plurality to a majority of the ideas reflected in the text come from a language model that does not actually believe them.
Writing is something that aids in the development of human ideas. It's not just that in the ideal case, a human being will have certain ideas and be able to communicate them to other people. Rather, we often have inchoate, unclear, or even contradictory ideas and opinions, and the process of writing itself leads us to figure out what it is, exactly, that we believe. So even in the "ideal" case of someone like OP who engages with LLMs more critically, and claims responsibility for every bit of text they publish, the process is still detrimental to the production and communication of true beliefs because their ideas were formed in dialogue with an agent that did not actually believe them. It's a process that is dangerous to bypass because you skip most of the thinking involved in writing without even realizing it.
I don't think an author is bound to their readers via contract, implicit or otherwise. I have no obligation to tell people what tools I use, or how I've arrived at a final product. That might be upsetting to hear, but authors don't owe their readers anything, just as readers don't owe authors anything.
There is a precedent for this, many auto biographies are actually ghostwritten, demonstrating that this contract you speak of has never actually existed.
Similarly how would you feel about writing that the author passed over to an editor?
p.s., I'm just echoing the arguments of the orginal article's author, who has a talent for reductio ad absurdum.
edit: added p.s.
AI can definitely be used as a tool in a workflow that's mostly driven by human effort. But as a reader, it's hard to tell whether a particular piece of AI-assisted writing came out of that kind of workflow without investing the effort yourself, and the prior of AI Writing == AI Slop is pretty strong. Attribution seems like a partial solution, since someone putting their name behind it will suffer reputational harm if they're producing nothing but slop.