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Researchers develop ‘smarter’ smartphone based on personality

A woman takes a picture with her smartphone. (DANIEL LEAL-OLIVAS/AFP/Getty Images)

By Ese Olumhense

‘Like an excellent human secretary’

A team at Rutgers University has developed a model system for smartphone notifications that prioritizes alerts based on a user’s personality traits, determining when the user might prefer to be interrupted or to be left alone.

“Ideally, a smartphone notification management system should be like an excellent human secretary who knows when you want to be interrupted or left alone,” says Janne Lindqvist, an assistant professor in the Department of Electrical and Computer Engineering at Rutgers. “We know that people struggle with time management all the time, so a smartphone, instead of being a nuisance, could actually help with things.” 

Led by Lindqvist, the New Jersey university’s team developed the program after conducting a peer-reviewed study on the impact of smartphone distractions. The Rutgers study involved more than 5,000 smartphone records, aimed to predict how “interruptible” a user is, or how readily they could shift focus to their phones from whatever task they were undertaking. Recognizing that temperament plays an important role on how interruptible a user could be, researchers also assessed the user’s personality traits.

Based on the sum of this data, the team designed a notification system that, like a “human secretary,” learns the user’s behavior and preferences, prioritizing notifications accordingly.

Cell phones sabotaging your health ?

The Rutgers research and notification system is a hopeful answer to a problem many have — notification overload. Previous studies have shown that constant alerts can be a nuisance, undercutting productivity and adversely influencing emotion.

As smartphones have increasingly adopted sophisticated technology and applications — for everything from social platforms to messaging clients, games, and news outlets — users have been inundated by the accompanying alerts and updates, so much so that some Americans are suffering from smartphone-related stress and anxiety, multiple studies have shown, causing sleep problems and whittling away attention spans.

Worse still: your performance on attention-demanding tasks can suffer even when you are not using your phone. Simply hearing the vibration from an incoming text or call can derail your attention span, researchers found in 2015, at levels comparable to interacting with the device.

Though they may be aware of some of these risks, users still often prioritize their smartphones over their health. In a series of University of Virginia studies, collegiate participants were required to sit alone in a room for between six and 15 minutes, without their phones. When left alone with their thoughts, and no option to occupy themselves beside the choice to administer a painful electric shock, many of the young participants chose being shocked just for the sake of distraction, something researchers found “striking.” When given the chance to do the same activity at home, a third of the participants admitted they “cheated” and checked their smartphone or computer.

 Too much machine learning?

Considering all the research that has emerged around cell phone distraction in the last few years, the Rutgers team’s proposed model could be worth checking out for many millennials and others battling tech addiction. Prolonged time away from memes, messages, and social media could help many with focus, sleep, and productivity.

For those wary of Big Brother, though, systems like the one developed at Rutgers pose interesting privacy and surveillance questions, namely: How much machine learning is too much? Could user data, including mood, location, and behavior patterns be accessed by the government or other surveillance entities, more than it is now?

For privacy-conscious users — especially those who have watched the dystopian technology show Black Mirror, which analyzes the potentially sinister side of our increasingly digital lives — the possibility for user data to be used and abused is not novel.

Though it’s not known whether the Rutgers team will adopt strict privacy guidelines for user data, the tech industry seems to be slowly heeding these concerns, with Facebook and Instagram announcing this week that user data could no longer be used by developers for surveillance tools. Whether or not others will take notice of this and adopt similar policies is unknown, but users could certainly benefit from increased attention to their digital safety.