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Why Do I Feel My Phone Vibrate Even When No One's Calling or Texting?

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A few months ago, I decided to give up on text message alerts. Not because I wasn’t interested in replying, but because I couldn’t handle having my phone vibrate at random. I had started experiencing “phantom vibrations,” the false sensation that your phone is vibrating. Unwilling to deal with constant pinging ringtones, and filled with disappointment and embarrassment every time I reached into my pocket to find that my brain had invented the sensation of a vibrating alert, I opted to merely mute everything.

It worked. I no longer feel that phantom phone itch in my leg or where the bottom of my purse brushes against my body. (As it turns out, very few texts are actually urgent.)

I’m not the only person who hallucinates that someone is trying to communicate with me. Psychologist David Laramie dubbed the feeling “ringxiety” in his 2007 dissertation on mobile phone use and behavior, but it wasn’t invented with the cell phone. In 1996, ”phantom-pager syndrome” made an appearance in a Dilbert strip. The phenomenon has since been studied across age ranges, professions, and cultures.

A 2012 study of 290 Indiana undergraduates found that 89 percent had experienced some degree of phantom phone vibration, averaging about once every two weeks. Nor is it limited to phone-obsessed college kids. A study of hospital staffers, who are frequently tethered to pagers and phones at work, found that 68 percent of the 176 workers surveyed experienced phantom vibrations.

It’s not just vibrations, either. Laramie’s 2007 study of 320 adults found evidence for aural hallucinations, too—two-thirds of the participants actually thought they heard their phone ringing.

But why people feel vibrations where there are none is still up for debate. In the 2010 hospital worker study, the Massachusetts-based researchers hypothesized that the phantom signals “may result from a misinterpretation of incoming sensory signals by the cerebral cortex.” They continue:

In order to deal with the overwhelming amount of sensory input, the brain applies filters or schema based on what it expects to find, a process known as hypothesis guided search. In the case of phantom vibrations, because the brain is anticipating a call, it misinterprets sensory input according to this preconceived hypothesis. The actual stimulus is unknown, but candidate sensations might include pressure from clothing, muscle contractions, or other sensory stimuli.

Recently, a University of Michigan phone study posited that ringxiety is linked to insecurity. The 2016 study found that people with attachment anxiety (who are insecure in personal relationships) were more likely to experience frequent phantom vibrations. This seems to make sense: If you’re insecure in your romantic relationship, you’re probably more likely to obsess about whether or not your partner is texting you. Expecting a message or call, or being particularly concerned about something that you might be contacted about, was further associated with phantom alerts.

However, most studies have found that only a tiny fraction of people are seriously bothered by the phantom signals—typically around 2 percent of the populations examined [PDF]. In the Indiana study, “few [participants] found them bothersome,” the researchers noted. The hospital workers studied didn’t, either. Many reported phantom-vibration sufferers didn’t try to do anything about it. Others successfully rid themselves of the sensation: Of the 115 hospital workers who experienced phantom vibrations, 43 attempted to stop it by taking their device off vibrate or carrying it in a different place, with 75 percent and 63 percent success rates, respectively.

The best way to rid yourself of phantom vibrations, it seems, is to be a super secure person with no social anxieties. Or, you could just try moving your phone to a different pocket. 

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11-Year-Old Creates a Better Way to Test for Lead in Water
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In the wake of the water crisis in Flint, Michigan, a Colorado middle schooler has invented a better way to test lead levels in water, as The Cut reports.

Gitanjali Rao, an 11-year-old seventh grader in Lone Tree, Colorado just won the 2017 Discovery Education 3M Young Scientist Challenge, taking home $25,000 for the water-quality testing device she invented, called Tethys.

Rao was inspired to create the device after watching Flint's water crisis unfold over the last few years. In 2014, after the city of Flint cut costs by switching water sources used for its tap water and failed to treat it properly, lead levels in the city's water skyrocketed. By 2015, researchers testing the water found that 40 percent of homes in the city had elevated lead levels in their water, and recommended the state declare Flint's water unsafe for drinking or cooking. In December of that year, the city declared a state of emergency. Researchers have found that the lead-poisoned water resulted in a "horrifyingly large" impact on fetal death rates as well as leading to a Legionnaires' disease outbreak that killed 12 people.

A close-up of the Tethys device

Rao's parents are engineers, and she watched them as they tried to test the lead in their own house, experiencing firsthand how complicated it could be. She spotted news of a cutting-edge technology for detecting hazardous substances on MIT's engineering department website (which she checks regularly just to see "if there's anything new," as ABC News reports) then set to work creating Tethys. The device works with carbon nanotube sensors to detect lead levels faster than other current techniques, sending the results to a smartphone app.

As one of 10 finalists for the Young Scientist Challenge, Rao spent the summer working with a 3M scientist to refine her device, then presented the prototype to a panel of judges from 3M and schools across the country.

The contamination crisis in Flint is still ongoing, and Rao's invention could have a significant impact. In March 2017, Flint officials cautioned that it could be as long as two more years until the city's tap water will be safe enough to drink without filtering. The state of Michigan now plans to replace water pipes leading to 18,000 households by 2020. Until then, residents using water filters could use a device like Tethys to make sure the water they're drinking is safe. Rao plans to put most of the $25,000 prize money back into her project with the hopes of making the device commercially available.

[h/t The Cut]

All images by Andy King, courtesy of the Discovery Education 3M Young Scientist Challenge.

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Google's AI Can Make Its Own AI Now
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Artificial intelligence is advanced enough to do some pretty complicated things: read lips, mimic sounds, analyze photographs of food, and even design beer. Unfortunately, even people who have plenty of coding knowledge might not know how to create the kind of algorithm that can perform these tasks. Google wants to bring the ability to harness artificial intelligence to more people, though, and according to WIRED, it's doing that by teaching machine-learning software to make more machine-learning software.

The project is called AutoML, and it's designed to come up with better machine-learning software than humans can. As algorithms become more important in scientific research, healthcare, and other fields outside the direct scope of robotics and math, the number of people who could benefit from using AI has outstripped the number of people who actually know how to set up a useful machine-learning program. Though computers can do a lot, according to Google, human experts are still needed to do things like preprocess the data, set parameters, and analyze the results. These are tasks that even developers may not have experience in.

The idea behind AutoML is that people who aren't hyper-specialists in the machine-learning field will be able to use AutoML to create their own machine-learning algorithms, without having to do as much legwork. It can also limit the amount of menial labor developers have to do, since the software can do the work of training the resulting neural networks, which often involves a lot of trial and error, as WIRED writes.

Aside from giving robots the ability to turn around and make new robots—somewhere, a novelist is plotting out a dystopian sci-fi story around that idea—it could make machine learning more accessible for people who don't work at Google, too. Companies and academic researchers are already trying to deploy AI to calculate calories based on food photos, find the best way to teach kids, and identify health risks in medical patients. Making it easier to create sophisticated machine-learning programs could lead to even more uses.

[h/t WIRED]

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