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One of the most painful arguments I keep having with fellow techies is the question of whether you can distinguish between human-written and AI-generated text.
Their skepticism is rooted in reason: at their core, LLMs are state-of-the-art statistical models of how humans talk. If so, the output from the model should be almost by definition indistinguishable from human language under any statistical test.
I donβt think this is always argued in good faith; at least some of the debates are started by folks who wish to maintain deniability for their own underhanded use of the tech. But if you sincerely hold this belief, I present you the following collage:

The image shows about 150 Amazon book covers that appear if you search the site for β100000 whysβ (link). Some of these books are category bestsellers in children literature. You can view a zoomable, full-resolution version here.
Thereβs nothing inhuman about any of these titles or covers. At the same time, I probably donβt need to convince you that youβre staring at the purest form of AI slop that is now the scourge of many non-fiction book categories on Amazon. More specifically, what weβre seeing here is the artifact of LLMs being quasi-deterministic: if a hundred βauthorsβ give the an LLM a similar prompt β say, βgenerate a reference book for childrenβ β the model will produce functionally identical output perhaps 80% of the time.
The similarities in the collage go far beyond the choice of titles: for example, all the covers in the top row feature a roaring dinosaur in the top left corner of the design. There are many other clusters in the data, too. Look for a recurring red-and-white cartoon rocket, a golden retriever, a lion, and so forth.
This is precisely what makes LLM writing distinctive: itβs not that the modelsβ individual mannerisms are different from ours. Itβs that they resort to the same, complex set of mannerisms in response to almost any normal prompt. This is a fuzzy signal, so you shouldnβt fire your intern when they say βitβs not this β itβs thatβ. But in more casual settings, itβs OK to trust your gut. In fact, these instincts are becoming increasingly important because traditional models of online interactions fall apart if it takes much less effort to produce content than to engage with it.
PS. If youβre using an LLM to automate blogging: yes, the tech is amazing, but chances are, your publication could be renamed to β100,000 Whysβ.
π¬ **Whatβs your take?**
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#οΈβ£ **#whys**
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