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Em dashes are commonly used in most countries that speak English. I get the feeling that people from the USA don’t use them often and now have tarnished the use of them.
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Do you remember when the AIs were all writing with bullet points all the time? I miss that! I'd prefer that to the current more-information-density-than-any-human-would-ever-muster approach where sentences are packed so deep you can't get any meaning by skimming.
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The three great epochs of AI:

Way too many bullets -> way too many emojis -> way too many em dashes

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I have a pet theory that there's some overlap of writing patterns that A) indicate quality, clear communication and B) those that the LLMs have been converging on. As a result, we're ruining the reputation of some great writing patterns because we've associated it with AI slop.
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My pet theory is that this was happening, because labs naturally worked to source highest quality data sources they could get. Even if they initially slurped everything indiscriminately, the obvious next step is to sort them by "quality", and bias towards the high end while trimming from low end.

So obviously, government documents, top publications from liberal arts scholars and STEM > Wikipedia > Reddit (and within, r/AskHistorians > r/all, etc.). The first group is the one most likely to (over)use correct / fancy typography.

I have a related pet theory: the telltale sign of AI writing is being too good for the context it's found in, in terms of vocabulary and style as well as structure.

What is jarring about this is precisely the quality - we associate certain styles with important (or self-important) venues, so it's uncanny to suddenly see random shitposts, copywriting spam, or regular chat replies look like work of NYT bestselling authors or legal scholars - it feels wrong in places we expect basic language, grug-brain reasoning, and lots of typos.

Also, what makes the above much more noticeable, is that AI systems don't have cross-session stylistic memory. From the POV of an LLM, that perfectly fitting, masterfully crafted starter is the first and only time it used it. From the user's POV, it's the tenth time they're seeing it in the span of an hour.

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AI writing style comes from post-training, which is entirely under the control of the labs. It's not copying it from any public sources.
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I didn't say it's copying anything. It's learning styles - all of them - in pre-training. Post-training is just about giving it the right defaults.

Doesn't change my point anyway - even if post-training, labs naturally want the LLM to come off as smart (well, except for Grok). Post-training is where they "untrained" em-dashes and such, due to complaints of users.

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I'd heard an interesting theory that in training on customer chats there's a lot of interactions like this:

Agent: _wall of text_

User: yeah sounds great, do it

Which has the predictable outcome of biasing towards wall of text responses.

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Continue to write with em dashes. Be the change you wish to see in the world.
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I did at the beginning, but there is only so much you can take, and no one cares if you have read books and seen it before. There were a bunch of programmers whom I thought would understand em dashes, but they did not and said no one uses such dashes only normal hyphens.

Em dashes ended up as one of the first victims of llm age

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Em dashes were already "doomed" at least half a century ago, because they didn't make it into ASCII character set - which arguably is just because they were seen as redundant on ancient typewriters; that's also why they aren't there on normal keyboards, which was a double whammy: inconvenient for programmers to support, inconvenient for users to type.

In other words, since the very start of computer era, the use of em dashes was always a signal.

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At least with a typewriter, if - was sized right you could -- for an emdash.
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They were in models in the first place because they are used ubiquitously published formal writing. As, of course, are semicolons. There is nothing wrong with using punctuation for nuance and structure.
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I feel like the LLMs used them "wrong". They use them for hard breaks for disconnected thoughts rather than one thought that disconnects.
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I think they just used them too much. I suspect that as they naturally form a thematic break point in writing, their probability was unnaturally high at the end of phrases and this led to overuse.

I don't ever recall seeing an LLM using them incorrectly, as opposed to simply at high frequency but correctly (although I'm sure some low param or early models must have done so at some point).

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The dashes reveal AI generated text. For me a trigger to further ignore the text.
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Because you ignored them before someone told you about them.
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