Why are lie detectors legal and why were they ever used for anything? We know they don't work. And we know this one won't work any better, because now they've just put the work of sentiment analysis on "AI" vs. a "trained expert".
Iraq and other countries purchases millions of dollars worth of phony bomb detectors. Something anyone with a bit of science education can debunk.
Look at all the things on Kickstarter that are obvious pipedreams or scams yet people invest.
https://www.vanityfair.com/news/2015/06/fake-bomb-detectors-...
This is a hilarious read.
Our society was built on large amounts of discretion being exercised by law enforcement and the ability to convincingly lie to law enforcement.
Society is going to get flipped on its head if we are able to detect total truth, and enforce all laws with 100% effectiveness. Even worse when these tools will be mostly in the hands of the government, and not the people.
This I get.
> and the ability to convincingly lie to law enforcement.
This less so. Can you elaborate?
If everything were some day 100% honest, the polite niceties of "oh sorry didn't see the speed limit change" or "Forgot I left my pocket knife in carryon, sorry" would go away. Of course these are only two of countless examples.
"Do you have any intention of overthrowing the government?" - "No" - beep, and now you're in a forced labor camp
Even if these tools worked, they wouldn't be able to detect truth, only belief.
Former inmates, drug addicts, surgeons, lawyers, mechanics, welders, astrophysicist, particle physicists, pilots. Need I go on?
Not once have I read anyone here who’s admitted to being a high level politician.
[0] https://slate.com/technology/2013/04/dowsing-for-bombs-maker...
That anonymity disappears much more quickly if said Member of Congress has also posted in the past about where they're from and which political issues they're passionate about...
I'm just wondering if it's too much to hope that they'll base the decision whether to implement it beyond the trial on data and not on marketing.
And there is of course the argument that it should be possible, albeit with a lot of effort and/or a reasonable punishment, to break the law. (If this was impossible, we'd never get out of regimes we don't agree with, and with the advance of technology I'm afraid we're heading somewhere where a small group is actually able to oppress a huge number of people.)
Border agents are trained to look for all sorts of things, none of which make you guilty, but a few of which may make you suitable for more questions or a quick search.
So I'd imagine it'll get used in the same context.
Personally, I don't like the concept of deploying algorithms for which we don't understand how they work, in scenarios of high health or social impact. It's cute to deploy DNNs to classify cat pictures, as when - not if - it spectacularly fails, nothing of value is lost. But if you can't point at the verified model the algorithm follows, or at least trace the algorithm after the fact, understanding and assessing every step it took, then that algorithm has no place in making decisions about people's lives.
And it's a similar promise to a lot of other over-promising AI technologies that don't work, like "fake news detectors".
And how do you know that?
I'm not for it, but it's not a polygraph as described.
Quote: "Looking for cues to deception merely from ephemeral facial micro-expressions is questionable and likely fruitless. Micro gestures may be indicative of internal emotional turmoil that is being suppressed, but that is it. The distinguished Paul Ekman, who in fact coined the term micro - expression has stated in his book Telling Lies that micro expressions are rare and they "don't occur that often" (Ekman 1985, 131, 165). Plus as others have said, there is no single behavior indicative of deception (Matsumoto et. al., 2011, 1-4). I am concerned that machines that focus solely on the face will no doubt miss other information from the body (sweating, jittery hand, etc.) or generate lots of false positives because negative emotions abound especially where such machines are intended such as airports (stress of travel, stress of being subjected to searches, or inconvenient interviews, etc) or in a police setting."
[1] https://www.psychologytoday.com/ca/blog/spycatcher/201203/th...
All in all, just another worrying piece of news from Hungary.
Please take a step back and look at all the replies to you. They all essentially say the same: We don't know of any reliably objective measurement for measuring lying. Humans can sometimes do that intuitively, yes, but to my knowledge there hasn't been a single successful attempt of a generalization of detection. That's why state of the art means using trained humans, like the airport security in Israel.
Without a mechanism to detect lying without using humans, no amount of statistics (which ML boils down to) can help you. ML can't change the fact that you don't know if the data point is a signal or just noise. Without knowing what the signals look like, ML can't calculate the noise away.
Even simpler: For ML you need a dataset with people lying and people saying the thruth. That's what you train the model on. But we have no way of building that dataset, because, to my knowledge, we don't have a way to reliably build up this dataset: We can't reliably detect if someone is lying.
[0] https://en.wikipedia.org/wiki/Burden_of_proof_(law)
[1] https://www.wired.com/story/inside-polygraph-job-screening-b...
And nobody is being accused of anything, there is no burden of proof involved yet. If you mean that we can't subject someone to a lie detector while asking questions, i.e. we cannot subject anyone to anything without a reasonable suspicion, then we couldn't have airport security at all unless someone tweeted "today's plane is gonna be da bomb!"
Which would be a lot better than the current state of things in the USA, but that's not how this works.
I think it's unlikely that they'll be perfect, but they may very well be good enough to filter people for further, more intensive screening.
You'd be surprised. AI is just a catch-all marketing term, see for example IBM's Watson umbrella brand, that's sold like advanced AI but has had tons of fiascos, and is shown to be different sets of often simplistic implementations.
E.g: https://www.massdevice.com/report-ibm-watson-delivered-unsaf...
https://spectrum.ieee.org/the-human-os/robotics/artificial-i...
https://www.theverge.com/2018/7/26/17619382/ibms-watson-canc...
In this case, there's excellent reason to be sceptical about whether the service has a remotely adequate dataset, because even if lie detection were a simple problem, how on earth are you going to get calibration data involving hundreds of data points of real airline passengers lying about having weapons in their luggage or intending to overstay their visa? Never mind calibration data by gender, ethnicity and nationality...
Usually when people say 'AI', IBM included, what they mean is fairly trivial machine learning. Machine learning requires a dataset to learn on.
> In this case, there's excellent reason to be sceptical about whether the service has a remotely adequate dataset, because even if lie detection were a simple problem, how on earth are you going to get calibration data involving hundreds of data points of real airline passengers lying about having weapons in their luggage or intending to overstay their visa?
You could do it by watching film of interactions with border agents when it is still unknown whether or not the person was lying, and then use whether or not they were caught smuggling (or whatever) ex-post as your ground truth.
You're going to need a lot of film. Good luck picking the controls for that that ensure your ML system picks up on subtle differences in humans that are lying and not glaringly obvious differences in appearance, accent and even background noise between the footage of the convicts and the control group...
I assume you would isolate the people in pre-processing, and do feature extraction of things you might think are interested in. Yes, it'd still require a lot of data, but that data may exist somewhere. A lot of these things are filmed.
From CIA, and TSA, to your local police department, everybody would have jumped all over it.
This is some vendor managing to sell some BS to bureaucrats (probably with the required bribes).
If CIA had it, you wouldn't hear about it. I don't see any reason why these countries couldn't pilot it for their border security before TSA, though.
FWIW, polygraphs are still used for security clearance screening. So, they are at least accurate enough for that use. They get a bad rep because they aren't admissible in court, but it's not like they have zero correlation to truth telling. They are still quite accurate.
a) it'll work,
b) it's actually any sort of AI,
and that, for example, even reputable companies like IBM can peddle all kind of shit as AI.
So, IBM was used as an example of a common practice, not as some logical axiom that "because they did it, nothing AI will ever work". Example != logical necessity.
It does, however cast doubt, especially for such a thorny problem as "lie detection", that nobody has, thus far, solved.
Even if all this "AI" does is match the quality of a polygraph, it is probably extremely useful in screening people rapidly at the border.
You obviously don't work for IBM :)
A skilled IBM Watson sales consultant as capable of selling simple linear regressions as Big Data AI!
While I don't disagree that "AI" as a term is being abused, the distinction you're making seems very much a philosophical one.
Where did they get that dataset from? Did they ask a bunch of people a bunch of questions and then hired private investigators to verify the answers (and then hire extra investigators to cross-verify answers given by the previous bunch)? Because beyond something like this, there's no known way to create such a dataset.