AI can’t tell if you’re lying anyone who says otherwise is selling something – TNW

Another day, another problematic AI study.Todays snake oil special comes via Tel Aviv University where a team of researchers have unveiled a so-called lie-detection system.

Lets be really clear right up front: AI cant do anything a person, given an equivalent amount of time to work on the problem, couldnt do themselves. And no human can tell if any given human is lying. Full stop.

The simple fact of the matter is that some of us can tell when some people are lying some of the time. Nobody can tell when anybody is lying all of the time.

The university makes the following claim via press release:

Researchers at Tel Aviv University detected 73% of the lies told by trial participants based on the contraction of their facial muscles achieving a higher rate of detection than any known method.

Thats a really weird statement. The idea that 73% accuracy at detecting lies is indicative of a particular paradigms success is arguable at best.

Base luck gives any system capable of choice a 50/50 chance. And, traditionally, thats about how well humans perform at guessing lies. Interestingly, they perform much better at guessing truths. Some studies claim humans achieve about the same accuracy at determining truth statements as the Tel Aviv teams lie-detection system does at determining truthfulness.

The Tel Aviv University teams paper even mentions that polygraphs arent admissible in courts because theyre unreliable. But they fail to point out that polygraph devices (which have been around since 1921) beat their own system in so-called accuracy polygraphs average about an 80% 90% accuracy-rate in studies.

But lets take a deeper look at the Tel Aviv teams study anyway. The team started with 48 participants, 35 of which were identified as female. Six participants were cut because of technical issues, two got dropped for never lying, and one participated in only 40 out of 80 trials when monetary incentives were not presented.

So, the data for this study was generated from two sources: a proprietary AI system and 39-40 human participants. Of those participants, an overwhelming majority were identified as female, and theres no mention of racial, cultural, or religious diversity.

Furthermore, the median age of participants was 23 and theres no way to determine if the team considered financial backgrounds, mental health, or any other concerns.

All we can tell is that a small group of people averaging 23-years in age, mostly female, paired off to participate in this study.

There was also compensation involved. Not only were they paid for their time, which is standard in the world of academia research, but they were also paid for successfully lying to humans.

Thats a red flag. Not because its unethical to pay for study data (it isnt). But because its adding unnecessary parameters in order to intentionally or ignorantly muddy up the study.

The researchers explain this by claiming it was part of the experiment to determine whether incentivization changed peoples ability to lie.

But, with such a tiny study sample, it seems ludicrous to cram the experiment full of needless parameters. Especially ones that are so half-baked they couldnt possibly be codified without solid background data.

How much impact does a financial incentive have on the efficacy of a truth-telling study? That sounds like something that needs its own large-scale study to determine.

The researchers paired off participants into liars and receivers. The liars put on headphones and listened for either the word tree or line and then were directed to either tell the truth or lie about which theyd heard. Their partners job was to guess if they were being lied to.

The twist here is that the researchers created their own electrode arrays and attached them to the liars faces and then developed an AI to interpret the outputs. The researchers operated under an initial assumption that twitches in our facial muscles are a window to the ground-truth.

This assumption is purely theoretical and, frankly, ridiculous. Stroke victims exist. Bells Palsy exists. Neurodiverse communication exists. Scars and loss of muscle strength exist. At least 1 billion people in the world currently live with some form of physical disability and nearly as many live with a diagnosed mental disorder.

Yet, the researchers expect us to believe theyve invented a one-size-fits-all algorithm for understanding humans. Theyre claiming theyve stumbled across a human trait that inextricably links the mental act of deceit with a singular universal physical expression. And they accomplished this by measuring muscle twitches in the faces of just 40 humans?

Per the aforementioned press release:

The researchers believe that their results can have dramatic implications in many spheres of our lives. In the future, the electrodes may become redundant, with video software trained to identify lies based on the actual movements of facial muscles.

So the big idea here is to generate data with one experimental paradigm (physical electrodes) in order to develop a methodology for a completely different experimental paradigm (computer vision)? And were supposed to believe that this particular mashup of disparate inputs will result in a system that can determine a humans truthfulness to such a degree that its outputs are admissible in court?

Thats a bold leap to make!The team may as well be claiming its solved AGI with black box deep learning. Computer vision already exists. Either the data from the electrodes is necessary or it isnt.

Whats worse, they apparentlyintend to develop this into a snake oil solution for governments and big businesses.

The press release continues with a quote:

[Team member Dino Levy] predicts: In the bank, in police interrogations, at the airport, or in online job interviews, high-resolution cameras trained to identify movements of facial muscles will be able to tell truthful statements from lies. Right now, our teams task is to complete the experimental stage, train our algorithms and do away with the electrodes. Once the technology has been perfected, we expect it to have numerous, highly diverse applications.

Exactly what percentage of those 40 study participants were Black, Latino, disabled, autistic, or queer? How can anyone, in good faith and conscience, make such grandiose scientific claims about AI based on such a tiny sprinkling of data?

If this AI solution were to actually become a product, people could potentially be falsely arrested, detained at airports, denied loans, and passed over for jobs because they dont look, sound, and act exactly like the people who participated in that study.

This AI system was only able to determine whether someone was lying with a 73% level of accuracy in an experiment where the lies were only one word long, meant nothing to the person saying them, and had no real effect on the person hearing them.

Theres no real-world scenario analogous to this experiment. And that 73% accuracy is as meaningless as a Tarot card spread or a Magic 8-Balls output.

Simply put: A 73% accuracy rate over less than 200 iterations of a study involving a maximum of 20 data groups (the participants were paired off) is a conclusion that indicates your experiment is a failure.

The world needs more research like this, dont get me wrong. Its important to test the boundaries of technology. But the claims made by the researchers are entirely outlandish and clearly aimed at an eventual product launch.

Sadly, theres about a 100% chance that this gets developed and ends up in use by US police officers.

Just like predictive-policing, Gaydar, hiring AI, and all the other snake oil AI solutions out there, this is absolutely harmful.

But, by all means, dont take my word for it: read the entire paper and the researchers own conclusions here.

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AI can't tell if you're lying anyone who says otherwise is selling something - TNW