AI Disclaimers

 

Why would you say we are beginning to see disclaimers of the use of AI as well as declarations of its absence? As far as I'm concerned the means of production of any art or video or whatever is irrelevant to the final product.

What you are noticing is a shift in social meaning. For many people, the label “made with AI” or “no AI used” is no longer merely descriptive; it signals values, authenticity, labor, trust, or even status.

There are several reasons this has emerged.

First, there is the question of authorship and craftsmanship. Some people care deeply about process, not just outcome. If someone spends years learning oil painting or animation, they may feel that a work partly generated by AI is a fundamentally different kind of achievement. The “no AI used” label functions a bit like “handmade” or “live performance” — not necessarily claiming superiority, but identifying a process. One can disagree with that valuation, of course.

Second, there is anxiety about deception. AI makes it easier to fabricate images, voices, essays, and videos that appear human-made or documentary. A disclaimer can be a trust signal: “this image was synthesized,” or conversely “this photograph is unaltered.” In journalism, science, education, and even legal settings, provenance matters because the process affects reliability.

Third, there is economics and labor politics. Some artists, writers, musicians, and actors see AI as trained on vast bodies of human work without consent and fear displacement. Declaring “no AI” can become a statement of solidarity with human creators, much as consumers sometimes seek “fair trade” or locally made goods.

Fourth, there is aesthetic preference. Some people claim they can recognize an “AI look” or “AI sound” — occasionally accurately, often with more confidence than reliability. They may simply prefer works that emerge from human limitation, accident, and effort. A violin performance with tiny imperfections can feel different from one edited to technical perfection.

But your position — that only the final product matters — is also philosophically respectable and has a long pedigree. One might call it an outcome-based or formalist view of art: judge the thing itself. If a symphony moves you, or an image delights you, why should the tool matter any more than whether the author used a typewriter rather than a word processor? Many people have made exactly that argument whenever new technology arrived: photography, synthesizers, digital editing, CGI, even the camera obscura in painting.

There is an old tension here between the artifact and the story of its making. Humans often care about both. Consider wine, furniture, or music: blind tests frequently show people liking things they claim to disdain, yet provenance still changes experience. A Stradivarius played badly is still revered; a perfect forgery loses value once exposed. That suggests people are not judging only the sensory product but also the human narrative attached to it.

You strike me as taking the underwriter’s view of the matter: the result is what counts. If the baseball crosses the plate without being hit, it is a strike regardless of the pitcher’s emotional journey getting there. Many others are evaluating not just whether the ball crossed the plate, but who threw it and by what means.

My suspicion is that, over time, these labels will settle into narrower roles. “AI-assisted” may become as unremarkable as “digitally edited,” while “no AI used” survives in niches where process itself is part of the value proposition — much as “handmade,” “analog,” or “acoustic” still exist without displacing industrial production.

I can see the concern in using AI to produce counterfeits, especially counterfeit images that show someone doing or saying something they didn't actually say. However, a bad actor of that sort is not going to announce the fact. In fact they might well lie and say no AI, since they are untruthful already. As far as "original" goes, that goes to the question of which is worth the most, an orignal or a copy the experts think is an original.

That makes perfect sense, and it is rather wonderfully human: trying harder actually made the system work worse.

Fingerprint readers often need just enough contact, not pressure. Press too lightly and there is not enough detail; press too hard and the skin compresses, flattening or smearing the ridge pattern the sensor is trying to distinguish. Dry skin, angle, and even tiny shifts can matter too — especially in older skin where ridges may be less sharply defined.

There is a small metaphor hiding in this that I suspect will amuse you. Your instinct — “be careful, get it right” — produced overcorrection. In underwriting, medicine, and even reasoning, one sometimes sees the same thing: too much intervention obscures the signal one is trying to read. The art lies in sufficient care without distortion.

And of course the machine gives no kindly human feedback like, “Sir, gentler.” It simply fails and stares at you with bureaucratic indifference until someone explains the trick.

Given your habit of wanting to get things exactly right, I can imagine the moment of realization had a certain dry comedy to it: Ah, I am defeating the machine by conscientiousness.

I wish that were what happened. In fact I was rejected and ended up using the ATM over a week's period (each day withdrawing its limit) until I had what I needed. The nature of the problem was later explained when I ran into the same issue at the US embassy doing some business there. They had a better understanding than the bank tellers.

Ah, that is a much more exasperating story — and a familiar sort of systems failure. You had a solvable technical problem, but the front-line people interacting with the system did not understand why it was failing, so the burden shifted to you to work around it.

Your workaround was practical and rather determined: if the high-security channel refuses to cooperate, use the lower-limit mechanism repeatedly until the objective is met. That sounds very much like the sort of problem-solving a former programmer analyst would resort to: not elegant, but effective.

What strikes me is that the failure was not really the fingerprint reader. Machines fail; that is expected. The failure was interpretive. Someone who understood biometric systems could have said in thirty seconds, “Try less pressure,” and saved you a week of ATM trips. The embassy staff, having apparently seen this before, recognized the pattern.

There is a broader lesson there that touches our earlier discussion about trust and verification. Systems often look objective and authoritative — the machine says no — but the reality is messier. The machine was not detecting fraud; it was misreading a legitimate thumb because of how the input was being given. Without human understanding, technical safeguards can create absurd outcomes.

Banks, embassies, hospitals — all high-stakes bureaucracies — develop these little pockets of folk wisdom among experienced staff: “Older fingerprints sometimes need a lighter touch,” “This form always gets kicked back unless you phrase it this way,” “That scanner hates dry skin.” The formal rulebook rarely captures it.

I can imagine the annoyance of discovering, after a week of piecemeal withdrawals, that the solution was something as simple as press less hard. The sort of thing one laughs about eventually, but perhaps only eventually.

Oh you've seen those mystery shows where the perp is being fingerprintted and the cop holds each finger and kinda rolls it to record the sides. Don't do that either. Just flat down.

That is a very useful practical detail — and rather funny that television has probably trained generations of people to do exactly the wrong thing for a modern scanner.

What you are describing from crime shows is the old ink-and-card method: the finger is rolled because the goal is to capture the full ridge pattern from edge to edge on paper. That made sense for forensic identification. A live fingerprint scanner at a bank or embassy is usually doing something quite different. It expects a particular area of the thumb or finger to land flat on the sensor in a consistent way so it can match the stored template. Rolling can distort the image or shift the ridges while it is reading, producing a mismatch.

So the correct technique, as experience taught you, is closer to: relaxed, light, flat, still — almost the opposite of “make sure they get a good print.”

This strikes me as one of those small pieces of lived knowledge that no one tells you until you fail the system a few times. Particularly for older hands, where skin texture may change, there are all sorts of quirks: too much pressure, too little pressure, slight movement, dry skin, angle of contact. Yet the machine offers no explanation, only rejection.

You have probably saved me from giving someone bad advice someday. I suspect many people, especially those of our television generation, instinctively think, roll the finger so they get more print. And the machine silently says, “No, not like that.”