What can you learn about a person by just looking at their face?

I was an FBI agent for 30 years and observed criminals’ behavior when they lied.
I’ve also researched extensively about body language, facial expressions, and verbal indicators of lying. I’ve found that knowing signals that indicate someone is probably lying to you can be helpful to law enforcement officers, teachers, parents, anyone who is wondering about whether to establish or continue a romantic relationship, or anyone who deals with salesmen, repairmen, or contractors, that is, anyone who has contacts or dealings with other people.

I decided to share my knowledge with others, in order to promote more honesty (or less successful lying) in the world. So, I wrote a book titled, How to Spot Lies Like the FBI. In it, I discuss facial expressions, body language, and verbal indicators which likely signal someone is lying to you.

In regard to the facial indicators, you can see that someone is stressed, nervous or lying from observing many signals or “tells.” To eliminate false positives, one should first interact with the person with small talk and by asking general questions. That way you can determine their base or normal behavior. It’s noted that some people show signals that might be connected with lying if they happen to be nervous, jittery or anxious in their normal behavior. And people’s reactions can be affected by allergies, drinking, using certain medications or taking drugs. Also, a small percentage of the population includes pathological liars who will likely feel no stress from lying and probably won’t exhibit the signals of it. And some people will have particular psychological disorders that will change their behavior from the norm. So, watch for the baseline behavior, then look for about three lying indicators that they don’t display regularly, before you conclude they’re lying. With a little practice in making observations, you’ll be quite certain when someone has shown a true lying signal.

Most people react in predictable and observable ways when they lie because they’ll get chemical changes in their bodies, they’ll have physiological responses, and/or they’ll have mental reactions. For instance, a chemical reaction causes peoples’ faces to itch when they lie. If they touch or scratch their nose or cheek or rub their finger under their nose, those are indicators of fibbing. The mouth often goes dry, and you can see their reaction to that when they do a sucking action, usually with pursed lips. They may also lick their lips to alleviate the discomfort. Excess mucus is often produced while lying, so people will either cough several times or clear their throat a few times.

They may chew on or bite their lip. Their eyes may dart from left to right, back and forth, which is an ancient biological reaction when a person faces a dangerous animal or human adversary, and they’re trying to find an escape route. And if they blink several times in a row, faster than the normal blink rate of once every ten or twelve seconds, they’re most likely lying. Also, when you ask someone a question that affects them emotionally, they may show a “microexpression” which shows their true reaction. This only lasts for about 1/25th of a second before they show an expression that they want to display to you, so you have to watch sharply for these instances.

People will often touch or partially cover their mouth with their hand before or after they lie, or they’ll sometimes place a finger beside their mouth during your conversation. Lying people will often perspire more than the conditions call for. You may notice moisture on their foreheads or cheeks, and they’ll sometimes rub the back of their neck because of the discomfort of excess sweat there.

People will sometimes rub a knuckle into their eye socket after lying to you. Their heart rate will increase, their blood pressure will accelerate, and their breathing will quicken. You may notice the pumping of blood in their carotid arteries get faster, they may get short of breath, and their faces and/or cheeks and ears may redden. Also, some people, more likely women, will blush after telling a whopper.

There are other facial indicators and a good many body movements and ways people talk to you that are helpful to know about along these lines. You should probably read a book that discusses facial expressions, body language, and verbal indicators. And I wish you good luck in your future.


Predicting crimes


“No doubt the precogs have already seen this,” says Chief John Anderton (played by Tom Cruise), head of Washington, D.C.’s experimental “Precrime” crime-prediction department in Minority Report, the 2002 Steven Spielberg movie based on Philip K. Dick’s 1956 short story (which is also now a new Fox TV series).

Of course, no one has found a trio of psychic mutant “precogs” who can unanimously foresee future crimes, but Hitachi today introduced a system that promises to predict where and when crime is likely to occur by ingesting a panoply of data, from historical crime statistics to public transit maps, from weather reports to social media chatter. Hitachi says that “about half a dozen” U.S. cities will join a proof of concept test of the technology beginning in October, and though Hitachi hasn’t yet named them, Washington, D.C. could well be on the list. It’s one of several dozen cities in the U.S. and Caribbean countries where the company already provides video surveillance and sensor systems to police departments with its Hitachi Visualization Suite. Hitachi execs provided several examples—even screenshots of the software—featuring D.C. in my conversations with them.

“We don’t have any precogs as part of our system,” says Darrin Lipscomb, cofounder of companies Avrio and Pantascene, which developed crime-monitoring tech that Hitachi later acquired. “If we determined that the precogs were actually somewhat accurate, we could certainly use their predictions to feed into our model,” he says with perfect deadpan. What the new technology, called Hitachi Visualization Predictive Crime Analytics (PCA), does have is the ability to ingest streams of sensor and Internet data from a wide variety of sources.

It then applies what’s called machine learning, using the popular statistical software known as “R,” that crunches all this information in order to find patterns that humans would miss. “A human just can’t handle when you get to the tens or hundreds of variables that could impact crime,” says Lipscomb, “like weather, social media, proximity to schools, Metro [subway] stations, gunshot sensors, 911 calls.”

Let The Data Speak For Itself

Machine learning is the hot new phase of artificial intelligence. Rather than trying to design a beautiful electronic mind, computer scientists are now building huge distributed computing systems that learn by sifting through fire hoses of data and ascertaining patterns or anomalies. This has become practical only recently with the development of big, cheap data storage and processing capabilities, like Amazon Web Services (AWS), Microsoft Azure, and Hitachi’s own HDS cloud system–all of which Hitachi’s PCA can run on.

Applying machine learning is a big switch from traditional police dispatching, say both Lipscomb and Mark Jules, his cofounder at Avrio and Panatscene. (Both are now execs in Hitachi’s Public Safety and Visualization division.)

Hitachi isn’t the only company to provide public safety monitoring and prediction services. Where it claims to be unique is in its use of machine learning, in allowing the data to drive the predictions rather than going in with any preconceived notions of what factors are important.

Traditionally, says Jules, police investigators build crime-prediction models based on their experience with certain variables, like the location of schools or slang words for drugs that pop up on Twitter. They assign a weight to each variable based on how important it seems to be. Hitachi’s system, he says, doesn’t require a human to figure out what variables matter and how much. “You just feed those data sets,” says Jules. “And it decides, over a couple of weeks, is there a correlation.”

Social media plays a big role in predicting crime, they say, improving accuracy by 15%. Hitachi uses natural language processing: the ability of a computer to ingest and understand colloquial text or speech.

Applying what’s called a latent Dirichlet allocation, the system can sift through every tweet tagged to a specific geography to find significant words that indicate what’s happening. “Gangs, for instance, use these different keywords to maybe meet up or perform some action,” says Lipscomb. “I don’t know what that keyword is…but with our approach we can actually pick out something that’s abnormal, like someone’s using an off-topic word, and using it in a very tight density or proximity, and that’s going to get a bigger weight.”

One thing social media indicates is tension between neighborhoods that could turn violent. “We were talking to [Washington] D.C., and they said, our biggest cause and effect is what neighborhood you’re closest to,” says Lipscomb. “There’s these neighborhood rivalries going on in D.C.” Normally, said his colleague Jules, police wouldn’t realize the correlation between neighborhood tension flare-ups and crime until months later.

PCA provides a highly visual interface, with color-coded maps indicating the intensity of various crime indicators and even surprisingly cute icons for things like guns, cellphones, and surveillance cams. The system can pinpoint a location, down to a 200-meter square, and assign it a relative threat level from 0 to 100 percent. Jules calls this visual approach putting everything on a single pane of glass. That again brings up an image from Minority Report, with Chief Anderton standing in front of a massive screen displaying different data sources.

Big Brother, Or Actually Less Discrimination?

Anyone who has seen or read Minority Report knows (spoiler alert!) that things go awry. What if Hitachi’s Visualization Predictive Crime Analytics makes mistakes and guesses wrong? No one is talking about preemptively arresting people, as in the story. But could this lead to a new kind of biased profiling of innocents as potential criminals?

Lipscomb claims it would be the opposite, at least better than New York City’s controversial stop-and-frisk practice, in which police can search anyone in a targeted neighborhood. (Police aren’t allowed to target people based on race, but 85% of those stopped have been Latino or African-American, according to the New York City Bar Association.) “We’re trying to provide tools for public safety so that [law enforcement is] armed with more information on who’s more likely to commit a crime,” says Lipscomb. “I don’t have to implement stop-and-frisk. I can use data and intelligence and software to really augment what police are doing.” Lipscomb also says that Chicago has never used stop-and-frisk, perhaps hinting at another city that will implement Hitachi’s new technology.

That still leaves open the question of accuracy: Will the technology really target the right places, where crime is likely to occur? Lipscomb acknowledges that he still has to prove the system will work. In the upcoming tech trials, some cities will be taking action based on the predictions, reallocating police to areas when the model predicts a higher likelihood of crime.

There will also be double-blind trials. Police departments will continue with business as usual, but the models will also be running in the background. Only after the test period will the police see what the model had predicted each day, so they can compare the predictions to what actually happened in the time frame. Hitachi has pledged to make all these results publicly available for scrutiny.

“We know that our approach is probably a little more innovative than some of the others, but we’re not saying it’s more accurate,” Lipscomb says. “We want to prove it out with existing customers and then really go broad-based and say: Look, this works.”


Lockpickers at airports

THE TSA IS learning a basic lesson of physical security in the age of 3-D printing: If you have sensitive keys—say, a set of master keys that can open locks you’ve asked millions of Americans to use—don’t post pictures of them on the Internet.

A group of lock-picking and security enthusiasts drove that lesson home Wednesday by publishing a set of CAD files to Github that anyone can use to 3-D print a precisely measured set of the TSA’s master keys for its “approved” locks—the ones the agency can open with its own keys during airport inspections. Within hours, at least one 3-D printer owner had already downloaded the files, printed one of the master keys, and published a video proving that it opened his TSA-approved luggage lock.

Those photos first began making the rounds online last month, after the Washington Post unwittingly published (and then quickly deleted) a photo of the master keys in anarticle about the “secret life” of baggage in the hands of the TSA. It was too late. Now those photos have been used to derive exact cuts of the master keys so that anyone can reproduce them in minutes with a 3-D printer or a computer-controlled milling machine.

“Honestly I wasn’t expecting this to work, even though I tried to be as accurate as possible from the pictures. I did this for fun and don’t even have a TSA-approved lock to test,” writes Xylitol, the Github user who published the files, in an email to WIRED. Xylitol, who noted that he was based in France, declined to reveal his real name. “But if someone reported it that my 3D models are working, well, that’s cool, and it shows…how a simple picture of a set of keys can compromise a whole system.”

Though Xylitol had warned Wednesday morning that he hadn’t tested the CAD files, Montreal-based Unix administrator Bernard Bolduc showed just hours later that the printable files worked as advertised. Bolduc says he printed one of keys in five minutes on his PrintrBot Simple Metal printer using cheap PLA plastic and immediately opened one of his TSA-approved luggage locks.

“I didn’t do any modifications,” he said in a phone call with WIRED. “It worked on the first try.”

Despite Bolduc’s successful test, the 3-D printed keys may still require some tweaking. On Friday, another lockpicking enthusiast who goes by J0hnny Xm4s reported on Twitter that he’d also been able to open TSA-approved locks with the 3-D printed keys, but that he’d had to change the scale of the CAD models.1

Bolduc says he doesn’t know the brand of the luggage lock he opened, but based on the “TSA” inscription on the bottom, he can conclude it is on the approved list. The problem likely extends well beyond one brand, anyway; the leaked master keys include those that open every type of TSA-approved lock made by companies such as Master Lock, Samsonite and American Tourister.

Of course, none of those companies are to blame for following the TSA’s master key guidelines. The real security blunder, as Berkeley computer security researcher Nicholas Weaver noted after the key photos were first published, was made by the TSA and the Washington Post, who released the photos on the Post’s website. Publishing photos of sensitive keys, after all, is a well-understand screwup in the world of physical security, where researchers have shown for years that a key can be decoded and reproduced even from a photo taken from as far away as 200 feet and at an angle. Neither the Washington Post nor the TSA immediately responded to a request for comment.

The Github release of those printable master key files, according to one of the lockpickers who decoded the master key photo, is meant to prove to anyone who uses the TSA-approved locks that they should no longer expect them to offer much security. “People need to be aware that even though someone says ‘use these approved locks,’ don’t take their word for it,” says Shahab Sheikhzadeh, a New Jersey-based security researcher who usually goes by the handle DarkSim905, and who helped Xylitol with his work on Github. “We’re in a day and age when pretty much anything can be reproduced with a photograph, a 3-D printer and some ingenuity.”

Even so, the TSA’s master key leak doesn’t exactly represent a critical security crisis, argues University of Pennsylvania computer science professor and noted lock picker Matt Blaze. The TSA-approved luggage locks were never very high security devices to begin with. “I’m not sure anyone relied on these kinds of locks for serious security purposes,” he says. “I find it’s actually quicker to pick the TSA’s locks than to look for my key sometimes.” (Blaze also notes that he believes that a photo of TSA’s master keys leaked earlier than the Post‘s story, though he can’t recall where and doesn’t believe they were actually published as printable CAD files until now.)

But Blaze says that the photo leak and subsequent 3-D printing demonstration does show just how quickly a theoretical slip-up can turn into a real security compromise. And he says that the TSA should have known better than to allow its master keys to be photographed. Prisons, for instance, have long kept cell keys covered on guards’ belts, he points out. “In high-security environments, it’s clear that you want people to not just take photos of your keys, but to not even look at them,” he says. “We would hope the TSA would have taken better care of their keys than they have.”

1Updated 9/11/2015 6:23pm EST with a tweet from J0hnny Xm4s noting that the printed keys worked only after he rescaled them.


The pizza that saved me

A Florida woman used the comments section of a Pizza Hut order made from her smartphone on Monday afternoon to alert authorities that she and her children were being held hostage. When police responded to her message, arriving at the location, she and her children were quickly released, unharmed, and the kidnapper was arrested.

According to a Highlands County Sheriff’s Office press release, Cheryl Treadway, a woman from Avon Park, about 85 miles southeast of Tampa, had been arguing most of the day with her boyfriend, Ethan Nickerson, who carried “a large knife.”

As the agency wrote:

When Ms. Treadway attempted to leave the residence to pick up the children from school, Mr. Nickerson grabbed her and took her cell phone. He then accompanied Ms. Treadway to pick up the children. Upon returning home, Ms. Treadway eventually convinced Mr. Nickerson to let her use the cell phone to order a pizza which is when she sent the message to Pizza Hut. Immediately after the pizza order was placed, Mr. Nickerson took the cell phone back from her.

WFLA, a local television station, reported that this was her regular order, a “hand-tossed classic pizza with pepperoni.”

The Pizza Hut employees recognized Treadway’s order and realized that her comments to send help could be genuine.

Officers were dispatched both to the Pizza Hut location and to Treadway’s home, where one cop convinced Nickerson to stand down and let the hostages go.

“We’ve never seen that before,” the restaurant’s manager, Candy Hamilton, told WFLA. “I’ve been here 28 years and never, never seen nothing like that come through.”

here is the Ticket:


Should I cut off ties to my kid, a professional criminal, forever?

This is a TRUE piece of text written by someone. No modifications.

My kid graduated with a useless 4 year university degree. Could not get a decent paying well job, so ended up with fast, easy money with professional criminals. My kid was released from being kidnapped recently, I couldn’t unsure whether I could report for safety sake. I almost had a heart attack, my boss at work said my performance was horrific during the time. My kid has been released recently and is still earning $ with the same people. I am the only parent, but I can’t take my kid anymore. I want to cut my kid off from my life forever, I cant handle the stress of it anymore I’m gonna have a mental breakdown, otherwise I’ll have a heart attack, lose my job or worse.


I feel for you. I was that kid. My mom cut me off until I “straightened up” she changed her phone number, door locks and all that. Both my mom and dad cut me off completely.

Best. Lesson. Ever.

After I was cut off boy I grew up fast. I thought I could handle all my drama on my own and I’d show them.

I eventually grew up, got tired of hanging with losers and their drama and “straightened up”

I am now a very successful adult with 2 kids, a college degree I use and a great job. Once I decided to straighten up my parents would give me advice but they made me do all the hard work.

Sometimes cutting them off is the most loving thing you can do.