I truly believe AI content has some kind of 'survivor bias' in the sense when it is detected. When it is sloppy and terrible it's really noticeable, when it's well done or used partially with a human you won't even notice or realize it's AI.
This black/white view on content is for lazy people who do the laziest prompts and send slop without checking, editing, copywriting, improving anything.
One of the biggest disappointments I found on the human race with the release of useful LLMs is the propensity to have the lowest denominator behaviour possible, be as lazy as possible and let themselves be cognitively replaced by AI, if you put in the SAME effort we used to put in before writing content, using ai tools as leverage I have no doubt it would be an improvement, we are just comparing apples to oranges when you consider the effort dispensed to write.
It depends on what the writing actually is, of course, but in general -- I have zero interest in hearing what genAI has to say about anything. I'm very interested in what people have to say about things. The "quality" of the writing doesn't enter into it.
1) Life is short, so attention is a scarce resource. And we discover whether a text was worth reading only after reading it. We must therefore choose what to read based only on available signals.
Until a few years ago, the existence of a text was in itself a signal. The fact that someone had paid days or weeks of his life to express an idea was proof that at least one person had judged that idea worth hours of a finite life. The cost of writing forced authors to select, from everything they might have said, the things that seemed to them most worth saying.
Today, publishers of LLM generated content do not need to select which ideas deserve the reader's time. They can publish everything (it costs them only a few seconds). Facing a block of text, the reader cannot be sure that anyone has judged it worth anyone's time; he cannot even be sure that someone has read it!
2) We look in language for more than interesting sequences of words: we read to connect with other minds. Language developed because man is a social animal who needed to communicate. One of language’s functions is to make one's mental states accessible to others. Notice that when you read an argumentative text, you often feel something for its author: recognition, gratitude, the relief of not being alone in thinking what you think, or irritation, the itch to lay out the counterargument to the author, etc. Reading is (partly) a social act. (Of course, this doesn’t apply to all forms of texts, we probably don’t care if the weather report is AI generated).
And the trouble is that an AI text (even carefully prompted) never reflects exactly what its “author” meant to say. Between the intention and the result stands an LLM that fills in the implicit in its own way, chooses one framing of an argument over another, adds or removes a nuance, adds a stylistic effect that shifts the emphasis (and AIs love stylistic effects). Because LLMs are probabilistic in nature, you even know that had the “author” prompted his AI 10 seconds later, the text he would have asked you to read would have been different. So, by construction, the result is not his own version.
Of course, the output may be more brilliant than what the author would have written. But still, it is not what he had in mind. Noise has been inserted between the author's mental state and the reader. There are often a thousand adjacent arguments leading to the same conclusion, and only one of them is the author’s. More generally, word order, sentence structure, lexical nuance, stylistic emphasis are part of the reasoning: change those and you change the argument. This is why it would sometimes be better to read someone’s prompts rather than their model’s output. It would provide more precise information on what they actually think.
3) When someone writes, he is by construction obliged to choose, at every point of every sentence, the word which he finds optimal for you to read. Of course, he does not always succeed in choosing the best words, but at least he has tried. On the other hand, when someone gives you an AI generated text, you know that he saw a bunch of words, and thought « good enough, I’ll make him read that ». An implicit contract binds an author to his reader; that contract is broken when the author spends less effort producing the text than the reader will spend reading it. Reading a good human text is spending a moment with someone who took care to receive you well. Nobody feels well received by an AI copy-paste.
4) An author owes the reader what the reader could not have obtained alone, not something he could get in a few seconds from Claude. If a reader knows that he could regenerate an equivalent version of the text (perhaps more tailored to his taste and personality), the motivation to read legitimately evaporates. LLM texts can be interesting and informative, but we have chatbots for this.
What does superior quality mean in this case?
I truly believe AI content has some kind of 'survivor bias' in the sense when it is detected. When it is sloppy and terrible it's really noticeable, when it's well done or used partially with a human you won't even notice or realize it's AI.
This black/white view on content is for lazy people who do the laziest prompts and send slop without checking, editing, copywriting, improving anything.
One of the biggest disappointments I found on the human race with the release of useful LLMs is the propensity to have the lowest denominator behaviour possible, be as lazy as possible and let themselves be cognitively replaced by AI, if you put in the SAME effort we used to put in before writing content, using ai tools as leverage I have no doubt it would be an improvement, we are just comparing apples to oranges when you consider the effort dispensed to write.
It depends on what the writing actually is, of course, but in general -- I have zero interest in hearing what genAI has to say about anything. I'm very interested in what people have to say about things. The "quality" of the writing doesn't enter into it.
Here's why:
1) Life is short, so attention is a scarce resource. And we discover whether a text was worth reading only after reading it. We must therefore choose what to read based only on available signals.
Until a few years ago, the existence of a text was in itself a signal. The fact that someone had paid days or weeks of his life to express an idea was proof that at least one person had judged that idea worth hours of a finite life. The cost of writing forced authors to select, from everything they might have said, the things that seemed to them most worth saying.
Today, publishers of LLM generated content do not need to select which ideas deserve the reader's time. They can publish everything (it costs them only a few seconds). Facing a block of text, the reader cannot be sure that anyone has judged it worth anyone's time; he cannot even be sure that someone has read it!
2) We look in language for more than interesting sequences of words: we read to connect with other minds. Language developed because man is a social animal who needed to communicate. One of language’s functions is to make one's mental states accessible to others. Notice that when you read an argumentative text, you often feel something for its author: recognition, gratitude, the relief of not being alone in thinking what you think, or irritation, the itch to lay out the counterargument to the author, etc. Reading is (partly) a social act. (Of course, this doesn’t apply to all forms of texts, we probably don’t care if the weather report is AI generated).
And the trouble is that an AI text (even carefully prompted) never reflects exactly what its “author” meant to say. Between the intention and the result stands an LLM that fills in the implicit in its own way, chooses one framing of an argument over another, adds or removes a nuance, adds a stylistic effect that shifts the emphasis (and AIs love stylistic effects). Because LLMs are probabilistic in nature, you even know that had the “author” prompted his AI 10 seconds later, the text he would have asked you to read would have been different. So, by construction, the result is not his own version.
Of course, the output may be more brilliant than what the author would have written. But still, it is not what he had in mind. Noise has been inserted between the author's mental state and the reader. There are often a thousand adjacent arguments leading to the same conclusion, and only one of them is the author’s. More generally, word order, sentence structure, lexical nuance, stylistic emphasis are part of the reasoning: change those and you change the argument. This is why it would sometimes be better to read someone’s prompts rather than their model’s output. It would provide more precise information on what they actually think.
3) When someone writes, he is by construction obliged to choose, at every point of every sentence, the word which he finds optimal for you to read. Of course, he does not always succeed in choosing the best words, but at least he has tried. On the other hand, when someone gives you an AI generated text, you know that he saw a bunch of words, and thought « good enough, I’ll make him read that ». An implicit contract binds an author to his reader; that contract is broken when the author spends less effort producing the text than the reader will spend reading it. Reading a good human text is spending a moment with someone who took care to receive you well. Nobody feels well received by an AI copy-paste.
4) An author owes the reader what the reader could not have obtained alone, not something he could get in a few seconds from Claude. If a reader knows that he could regenerate an equivalent version of the text (perhaps more tailored to his taste and personality), the motivation to read legitimately evaporates. LLM texts can be interesting and informative, but we have chatbots for this.