Just as the community adopted the term “hallucination” to describe additive errors, we must now codify its far more insidious counterpart: semantic ablation.
Semantic ablation is the algorithmic erosion of high-entropy information. Technically, it is not a “bug” but a structural byproduct of greedy decoding and RLHF (reinforcement learning from human feedback).
During “refinement,” the model gravitates toward the center of the Gaussian distribution, discarding “tail” data – the rare, precise, and complex tokens – to maximize statistical probability. Developers have exacerbated this through aggressive “safety” and “helpfulness” tuning, which deliberately penalizes unconventional linguistic friction. It is a silent, unauthorized amputation of intent, where the pursuit of low-perplexity output results in the total destruction of unique signal.
When an author uses AI for “polishing” a draft, they are not seeing improvement; they are witnessing semantic ablation. The AI identifies high-entropy clusters – the precise points where unique insights and “blood” reside – and systematically replaces them with the most probable, generic token sequences. What began as a jagged, precise Romanesque structure of stone is eroded into a polished, Baroque plastic shell: it looks “clean” to the casual eye, but its structural integrity – its “ciccia” – has been ablated to favor a hollow, frictionless aesthetic.
As a former linguistics major, I find this to be horseshit.
Really, we optimize for the least possible amount of communication necessary. With a spouse, you don’t ask full questions. Early on, you might have to shoot a look, but later on? This is now ingrained. They’re offering the solution before you express the problem.
To be clear, by “communication” I’m talking about the information conveyed by a certain utterance, while you’re likely referring to the utterance itself.
Once you take that into account, your example is optimising for #2 at the expense of #1 — yes, you can get away conveying info in more succinct ways, but at the expense of requiring a shared context; that shared context is also info the receiver knows beforehand. It works fine in this case because spouses accumulate that shared context across the years (so it’s a good trade-off), but if you replace the spouse with some random person it becomes a “how the fuck am I supposed to know what you mean?” matter.
Sure. That’s a specific use case and not likely a useful one.
When we start getting into utterances, though, we’re firmly in linguistics. Unless you’ve been passing bad checks.
Yeah, got to borrow some word from discourse analysis :-P
It fits well what I wanted to say, and it makes the comment itself another example of the phenomenon: that usage of “utterance” as jargon makes the text shorter and more precise but makes it harder to approach = optimises for #2 and #3 at the expense of #1. (I had room to do it in this case because you mentioned your Linguistics major.)
Although the word is from DA I believe this to be related to Pragmatics; my four points are basically a different “mapping” of the Gricean maxims (#1 falls into the maxim of manner, #2 of manner and relation, #3 of quality, #4 of quantity) to highlight trade-offs.
I never got a degree! I got roped into the college paper, and from there, well, I didn’t really care about my studies. Why worry about semantics and semiotics when you can tell 18,000 people what to think?
(yeah, I meandered into news after cutting my teeth in opinion)