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Why I don't like AI art -- Corey Doctorow
https://pluralistic.net/2025/03/25/communicative-intent/#diluted
A law professor friend tells me that LLMs have completely transformed the way she relates to grad students and post-docs – for the worse. And no, it's not that they're cheating on their homework or using LLMs to write briefs full of hallucinated cases.
The thing that LLMs have changed in my friend's law school is letters of reference. Historically, students would only ask a prof for a letter of reference if they knew the prof really rated them. Writing a good reference is a ton of work, and that's rather the point: the mere fact that a law prof was willing to write one for you represents a signal about how highly they value you. It's a form of proof of work.
But then came the chatbots and with them, the knowledge that a reference letter could be generated by feeding three bullet points to a chatbot and having it generate five paragraphs of florid nonsense based on those three short sentences. Suddenly, profs were expected to write letters for many, many students – not just the top performers.
Of course, this was also happening at other universities, meaning that when my friend's school opened up for postdocs, they were inundated with letters of reference from profs elsewhere. Naturally, they handled this flood by feeding each letter back into an LLM and asking it to boil it down to three bullet points. No one thinks that these are identical to the three bullet points that were used to generate the letters, but it's close enough, right?
Obviously, this is terrible. At this point, letters of reference might as well consist solely of three bullet-points on letterhead. After all, the entire communicative intent in a chatbot-generated letter is just those three bullets. Everything else is padding, and all it does is dilute the communicative intent of the work. No matter how grammatically correct or even stylistically interesting the AI generated sentences are, they have less communicative freight than the three original bullet points. After all, the AI doesn't know anything about the grad student, so anything it adds to those three bullet points are, by definition, irrelevant to the question of whether they're well suited for a postdoc.
. . .
The thing that LLMs have changed in my friend's law school is letters of reference. Historically, students would only ask a prof for a letter of reference if they knew the prof really rated them. Writing a good reference is a ton of work, and that's rather the point: the mere fact that a law prof was willing to write one for you represents a signal about how highly they value you. It's a form of proof of work.
But then came the chatbots and with them, the knowledge that a reference letter could be generated by feeding three bullet points to a chatbot and having it generate five paragraphs of florid nonsense based on those three short sentences. Suddenly, profs were expected to write letters for many, many students – not just the top performers.
Of course, this was also happening at other universities, meaning that when my friend's school opened up for postdocs, they were inundated with letters of reference from profs elsewhere. Naturally, they handled this flood by feeding each letter back into an LLM and asking it to boil it down to three bullet points. No one thinks that these are identical to the three bullet points that were used to generate the letters, but it's close enough, right?
Obviously, this is terrible. At this point, letters of reference might as well consist solely of three bullet-points on letterhead. After all, the entire communicative intent in a chatbot-generated letter is just those three bullets. Everything else is padding, and all it does is dilute the communicative intent of the work. No matter how grammatically correct or even stylistically interesting the AI generated sentences are, they have less communicative freight than the three original bullet points. After all, the AI doesn't know anything about the grad student, so anything it adds to those three bullet points are, by definition, irrelevant to the question of whether they're well suited for a postdoc.
. . .
Corey Doctorow goes on to talk about other realms where this is happening.
This is a good example of information theory.
- Take just a few facts (bullet points in his example)
- Fluff them up with AI/prose boilerplate
- You haven't added to the knowledge (facts)
- And you may have actually destroyed knowledge (AI ain't perfect and fluff is noise.)