Sadly, I see their use is more common now.
Peeps are paranoid about commodification; these are the algorithms and heuristics which linguistics has toppled too. And now they're checking through this. This has been checked adversarially, intuitively and counter-intuitively through a Socratic construction, with some autocomplete along with some other thoughts.
Pangram and others don't work. Or the self-abnegation of personal responsibility. Shall I quote? With that
Anyhow, here are two articles on why they are not to be trusted. Oh yeah, did I tell you the classifiers don't work in and of themselves? Well, you are the product. More on the math here.
Since this is continue with Sam Illingsworth's notes, the bias of these.
"Even a perfect detector would be the wrong tool
Now grant the impossible. Imagine a detector that worked flawlessly tomorrow.
I would still argue against it, for a reason that has nothing to do with accuracy.
The moment you put a detector between a teacher and a student, you change what a teacher is. You turn an educator into a police officer. The work of teaching is to be a co-creator of knowledge alongside the student, beside them while they struggle toward understanding. A detector makes suspicion the default setting. Every essay arrives presumed guilty.
That is not the job I signed up for. I did not become an educator to run my students’ words through a lie detector and wait for a number.
The evidence backs the instinct. I read every public UK university AI policy I could find, 96 of them, for a HEPI policy note this year. On a close reading of a sample, the language of education sat over an architecture of detection and surveillance. And two in five universities had no public AI policy at all. The machinery of policing arrived before the conversation about learning had even started.
You cannot police a student into learning. Detection keeps asking teachers to try."
Wow, look at that math.
Including a linguistic lesson on negative construction.
“It's not X. It's why” is a linguistic construction, more specifically, a “contrastive negation followed by a corrective assertion.” It's part of a rich “grammatical context for negated restrictives in English.” Olli O. Silvennoinen wrote an entire doctoral dissertation of 131 pages on contrastive negation.Since this is continue with Sam Illingsworth's notes, the bias of these.
"Even a perfect detector would be the wrong tool
Now grant the impossible. Imagine a detector that worked flawlessly tomorrow.
I would still argue against it, for a reason that has nothing to do with accuracy.
The moment you put a detector between a teacher and a student, you change what a teacher is. You turn an educator into a police officer. The work of teaching is to be a co-creator of knowledge alongside the student, beside them while they struggle toward understanding. A detector makes suspicion the default setting. Every essay arrives presumed guilty.
That is not the job I signed up for. I did not become an educator to run my students’ words through a lie detector and wait for a number.
The evidence backs the instinct. I read every public UK university AI policy I could find, 96 of them, for a HEPI policy note this year. On a close reading of a sample, the language of education sat over an architecture of detection and surveillance. And two in five universities had no public AI policy at all. The machinery of policing arrived before the conversation about learning had even started.
You cannot police a student into learning. Detection keeps asking teachers to try."
(Off Tangent, he does try the cult thing; that's a fandom thing, though. It's my opinion.)
So, what do we do? Trust, trust that it is. (I wonder how much that paradox catches on)