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AI discovers that not every fingerprint is unique
(techxplore.com)
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this post was submitted on 11 Jan 2024
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Congratulations to AI researchers for figuring something we knew pretty much since the first proposal of fingerprinting as a bio ID tech. We know that fingerprints aren't unique. That's why they're being rejected everywhere. They don't know what they're talking about and refuse to work out how their research fits into established forensics knowledge. They have no prior knowledge about forensics and insist on overturning decades of forensic knowledge with "I don't know, something with the curvatures of the lines inside the fingerprints, I guess. We don't actually know what the AI model is doing."
The title of the article is so misleading it's pretty much wrong.
If you read the article, what the researchers did was train an AI model that appears to be able to associate different fingerprints of the SAME person.
Example:Assume your finger prints are not on record. You do a crime and you accidentally leave a fingerprint of your left index finger at the scene.
THEN you do another crime and leave your RIGHT MIDDLE finger print at the scene.
The premise is that the AI model appears to be able to correlate DIFFERENT prints from the SAME person.
So, I'm the context of the research, they aren't saying that there is reason to believe that there exist fingerprint markers that might be present on a per-person basis, rather than strictly a per-finger basis.
Terrible headline, terribly written article, and IMO not nearly enough evidence that the correlation actually exists and even less evidence that it's appropriate to be able to be used as evidence.
That being said, based on the comments in the comments section I think most people didn't really grok what this research was, which is understandable based on the terrible headline
The research is bogus then as well. Projections like those have been in wide use at police stations around the globe at least since my cousin bragged about having this when he started his police training. That was.2008.
I mean, the research is the research and the data is the data.
If there are specific critiques to the methodology of the research that calls the validity of the observed data into question, that's fair. "It's 'well known' that..." Isn't a scientific argument. It's actually the exact opposite, it's literally religion.
Also, the conclusions being drawn from the data by the researchers or 3rd parties might be a problem.
To be fair, ML of today is unrecognizable to what it was in 2008. And, I'd be willing to bet the model your cousin was exposed to wasn't a machine learning model, and instead some handcrafted marker analysis with dubious justification but a great sales team.
The great thing about ML science is that it's super accessible. This was an undergrad project. The next step, to establish the validity, really just requires a larger data set. If it's bogus, that'll come out. If it's valid, that'll come out too. The cost of reproducibility is so low that even hobbiests can verify the results.
My cousin wasn't using any ML model. Their software probably did a geometric projection and that's it. Then they'd search for the proposed owner of the fingerprint and get the real ones to compare against. That's something that ML models cannot take from police as long as long as hallucinating is possible.
Right, so this methodology is a completely different approach. I don't think it's fair to call snake oil on this specifically with the justification that other models (using an entirely different approach) were.
Again, not saying it's real or not, I'm just saying that it's appropriate to try new approaches to examine things we already THINK we know, and to be prepared to carefully and fairly evaluate new data that calls into question things we thought we knew. That's just science.
I agree with you. But still, none of what they are talking about is new in the slightest. We know from research on the genetic markers, that determine skin cell differentiation, that people's fingerprints from different fingers have commonalities. Since they were formed by the same chemical signals with roughly the same timing. There's a lot of science on that pathway with RNA sequencing and Turing pattern research. But these authors obviously ignore all of that.
They explain poorly what they are doing because they don't understand what they are doing or how it relates to forensic science. None of the researchers has any experience with forensics. They are just a bunch of dudes playing with computers, AI and a dataset. Rightfully their research was rejected by all major forensic journals.
I have no idea how poorly the authors of the study communicated their work because I haven't read the study.
Jumping to the conclusion that it's junk because some news blogger wrote an awkward and confusing article about it isn't fair at all. The press CONSISTENTLY writes absolute trash on the basis of scientific papers. That's like, science reporting 101.
And, based on what you're saying, this still sounds completely different. RNA sequencing may be a mechanism to "why", but you would knock my fucking socks off if you could use RNA to predict the physical geometry of a fingerprint. If you could say we have a fingerprint, and we have some RNA, do they belong to the same person? That would be unbelievably massive.
If you read the press release, you'll see that they were rejected by all forensic journals and several general science journals. If you knew anything about science you would know that it costs money, out of the pocket of researchers, to be peer reviewed and published. So they are wasting money submitting their work that most journals deemed not worthy of publishing. If they were rejected by one and accepted by another, maybe we could talk about some merit, but being rejected by all is a tall order that simply says they either don't know what they're talking about or utterly suck at communicating. As rarely all journals share the same scope and point of view.
Now, normally I would read the article and tell you, how I did read the paper. Unfortunately I can't, because it isn't actually available, since Science Advances, who allegedly published it, or is going to publish it, has nothing of this article in their database. Trust me, I searched for it.
I would bet money that they are pampered silicon valley hedge fund babies who want to make it on academy with AI and are just going to blow money until they are recognized, no matter by whom as long as it gives them some veneer of prestige to form a startup and hoard money with some tech piece. My belief is supported on the fact that the research is being heralded by Hod Lipson who is part of Facility Makerspace, which is an entrepreneurship, robotics and tech oriented organization. They have no background, interest or passion for forensics, their whole shtick is finding ways to make money with tech. I've seen the types parading college halls like they own the place, acting as if they're the next Mark Zuckerberg, when they haven't even a fraction of the knowledge that he had when he dropped out.
I would certainly expect that you are more easily impressed than the people who actually know something about forensics.