The Best American Science and Nature Writing 2012

by Dan Ariely

  The signs leverage what’s called a feedback loop, a profoundly effective tool for changing behavior. The basic premise is simple. Provide people with information about their actions in real time (or something close to it), then give them an opportunity to change those actions, pushing them toward better behaviors. Action, information, reaction. It’s the operating principle behind a home thermostat, which fires the furnace to maintain a specific temperature, or the consumption display in a Toyota Prius, which tends to turn drivers into so-called hypermilers, trying to wring every last mile from the gas tank. But the simplicity of feedback loops is deceptive. They are in fact powerful tools that can help people change bad behavior patterns, even those that seem intractable. Just as important, they can be used to encourage good habits, turning progress itself into a reward. In other words, feedback loops change human behavior. And thanks to an explosion of new technology, the opportunity to put them into action in nearly every part of our lives is quickly becoming a reality.

  A feedback loop involves four distinct stages. First comes the data: a behavior must be measured, captured, and stored. This is the evidence stage. Second, the information must be relayed to the individual, not in the raw-data form in which it was captured but in a context that makes it emotionally resonant. This is the relevance stage. But even compelling information is useless if we don’t know what to make of it, so we need a third stage: consequence. The information must illuminate one or more paths ahead. And finally, the fourth stage: action. There must be a clear moment when the individual can recalibrate a behavior, make a choice, and act. Then that action is measured, and the feedback loop can run once more, every action stimulating new behaviors that inch us closer to our goals.

  This basic framework has been shaped and refined by thinkers and researchers for ages. In the eighteenth century, engineers developed regulators and governors to modulate steam engines and other mechanical systems, an early application of feedback loops that later became codified into control theory, the engineering discipline behind everything from aerospace to robotics. The mathematician Norbert Wiener expanded on this work in the 1940s, devising the field of cybernetics, which analyzed how feedback loops operate in machinery and electronics and explored how those principles might be broadened to human systems.

  The potential of the feedback loop to affect behavior was explored in the 1960s, most notably in the work of Albert Bandura, a Stanford University psychologist and pioneer in the study of behavior change and motivation. Drawing on several education experiments involving children, Bandura observed that giving individuals a clear goal and a means to evaluate their progress toward that goal greatly increased the likelihood that they would achieve it. He later expanded this notion into the concept of self-efficacy, which holds that the more we believe we can meet a goal, the more likely we will be to do so. In the forty years since Bandura’s early work, feedback loops have been thoroughly researched and validated in psychology, epidemiology, military strategy, environmental studies, engineering, and economics. (In typical academic fashion, each discipline tends to reinvent the methodology and rephrase the terminology, but the basic framework remains the same.) Feedback loops are a common tool in athletic training plans, executive coaching strategies, and a multitude of other self-improvement programs (though some are more true to the science than others).

  Despite the volume of research and a proven capacity to affect human behavior, we don’t often use feedback loops in everyday life. Blame this on two factors. Until now, the necessary catalyst—personalized data—has been an expensive commodity. Health spas, athletic training centers, and self-improvement workshops all traffic in fastidiously culled data at premium rates. Outside of those rare realms, the cornerstone information has been just too expensive to come by. As a technologist might put it, personalized data hasn’t really scaled.

  Second, collecting data on the cheap is cumbersome. Although the basic idea of self-tracking has been available to anyone willing to put in the effort, few people stick with the routine of toting around a notebook, writing down every Hostess cupcake they consume or every flight of stairs they climb. It’s just too much bother. The technologist would say that capturing that data involves too much friction. As a result, feedback loops are niche tools for the most part, rewarding for those with the money, willpower, or geeky inclination to obsessively track their own behavior, but impractical for the rest of us.

  That’s quickly changing because of one essential technology: sensors. Adding sensors to the feedback equation helps solve problems of friction and scale. They automate the capture of behavioral data, digitizing it so that it can be readily crunched and transformed as necessary. And they allow passive measurement, eliminating the need for tedious active monitoring.

  In the past two or three years, the plunging price of sensors has begun to foster a feedback-loop revolution. Just as YOUR SPEED signs have been adopted worldwide because the cost of radar technology keeps dropping, other feedback loops are popping up everywhere because sensors keep getting cheaper and better at monitoring behavior and capturing data in all sorts of environments. These new, less expensive devices include accelerometers (which measure motion), GPS sensors (which track location), and inductance sensors (which measure electric current). Accelerometers have dropped to less than a dollar each—down from as much as twenty dollars a decade ago—which means they can now be built into tennis shoes, MP3 players, and even toothbrushes. Radio-frequency ID chips are being added to prescription pill bottles, student ID cards, and casino chips. And inductance sensors that were once deployed only in heavy industry are now cheap and tiny enough to be connected to residential breaker boxes, letting consumers track their home’s entire energy diet.

  Of course, technology has been tracking what people do for years. Call-center agents have been monitored closely since the 1990s, and the nation’s tractor-trailer fleets have long been equipped with GPS and other location sensors—not just to allow drivers to follow their routes but to enable companies to track their cargo and the drivers. But those are top-down, Big Brother techniques. The true power of feedback loops is not to control people but to give them control. It’s like the difference between a speed trap and a speed feedback sign—one is a game of gotcha, the other is a gentle reminder of the rules of the road. The ideal feedback loop gives us an emotional connection to a rational goal.

  And today their promise couldn’t be greater. The intransigence of human behavior has emerged as the root of most of the world’s biggest challenges. Witness the rise in obesity, the persistence of smoking, the soaring number of people who have one or more chronic diseases. Consider our problems with carbon emissions, where managing personal energy consumption could be the difference between a climate under control and one beyond help. And feedback loops aren’t just about solving problems. They could create opportunities. Feedback loops can improve how companies motivate and empower their employees, allowing workers to monitor their own productivity and set their own schedules. They could lead to lower consumption of precious resources and more productive use of what we do consume. They could allow people to set and achieve better-defined, more ambitious goals and curb destructive behaviors, replacing them with positive actions. Used in organizations or communities, they can help groups work together to take on more daunting challenges. In short, the feedback loop is an age-old strategy revitalized by state-of-the-art technology. As such, it is perhaps the most promising tool for behavioral change to have come along in decades.

  In 2006 Shwetak Patel, then a graduate student in computer science at Georgia Tech, was working on a problem: How could technology help provide remote care for the elderly? The obvious approach would be to install cameras and motion detectors throughout a home, so that observers could see when somebody fell or became sick. Patel found those methods unsophisticated and impractical. “Installing cameras or motion sensors everywhere is unreasonably expensive,” he says. “It might work in theory, but it just won’t happen in prac
tice. So I wondered what would give us the same information and be reasonably priced and easy to deploy. I found those really interesting constraints.”

  The answer, Patel realized, is that every home emits something called voltage noise. Think of it as a steady hum in the electrical wires that varies depending on what systems are drawing power. If there was some way to disaggregate this noise, it might be possible to deliver much the same information as cameras and motion sensors can. Lights going on and off, for instance, would mean that someone had moved from room to room. If a blender was left on, that might signal that someone had fallen—or had forgotten about the blender, perhaps indicating dementia. If we could hear electricity usage, Patel thought, we could know what was happening inside the house.

  A nifty idea, but how to make it happen? The problem wasn’t measuring the voltage noise; that’s easily tracked with a few sensors. The challenge was translating the cacophony of electromagnetic interference into the symphony of signals given off by specific appliances and devices and lights. Finding that pattern amid the noise became the focus of Patel’s PhD work, and in a few years he had both his degree and his answer: a stack of algorithms that could discern a blender from a light switch from a television set and so on. All this data could be captured not by sensors in every electrical outlet throughout the house but through a single device plugged into a single outlet.

  This, Patel soon realized, went way beyond elder care. His approach could inform ordinary consumers, in real time, about where the energy they paid for every month was going. “We kind of stumbled across this stuff,” Patel says. “But we realized that combined with data on the house’s overall draw on power”—which can be measured through a second sensor easily installed at the circuit box—“we were getting really great information about resource consumption in the home. And that could be more than interesting information. It could encourage behavior change.”

  By 2008 Patel had started a new job in the computer science and engineering departments at the University of Washington, and his idea had been turned into the startup Zensi. At the university he focused on devising similar techniques to monitor home consumption of water and gas. The solutions were even more elegant, perhaps, than the one for monitoring electricity. A transducer affixed to an outdoor spigot can detect changes in water pressure that correspond to the resident’s water usage. That data can then be disaggregated to distinguish a leaky toilet from an overindulgent bather. And a microphone sensor on a gas meter listens to changes in the regulator to determine how much gas is consumed.

  Last year the consumer-electronics company Belkin acquired Zensi and made energy conservation a centerpiece of its corporate strategy, with feedback loops as the guiding principle. Belkin has begun modestly with a device called the Conserve Insight. It’s an outlet adapter that gives consumers a close read of the power used by one select appliance: plug it into a wall socket and then plug an appliance or gadget into it, and a small display shows how much energy the device is consuming, in both watts and dollars. It’s a window onto how energy is actually used, but it’s only a proof-of-concept prototype of the more ambitious product, based on Patel’s PhD work, which Belkin will begin beta-testing in Chicago later this year with an eye toward commercial release in 2013. The company calls it Zorro.

  At first glance, the Zorro is just another so-called smart meter, not that different from the boxes that many power companies have been installing in consumers’ homes, with a vague promise that the meters will educate citizens and provide better data to the utility. To the surprise of the utility companies, though, these smart meters have been greeted with hostility in some communities. A small but vocal number of customers object to being monitored, while others worry that the radiation from RFID (radio-frequency identification) transmitters is unhealthy (though this has been measured at infinitesimal levels).

  Politics aside, in pure feedback terms smart meters fail on at least two levels. For one, the information goes to the utility first rather than directly to the consumer. For another, most smart meters aren’t very smart; they typically measure overall household consumption, not how much power is being consumed by which specific device or appliance. In other words, they are a broken feedback loop.

  Belkin’s device avoids these pitfalls by giving the data directly to consumers and delivering it promptly and continuously. “Real-time feedback is key to conservation,” says Kevin Ashton, Zensi’s former CEO, who took over Belkin’s Conserve division after the acquisition. “There’s a visceral impact when you see for yourself how much your toaster is costing you.”

  The Zorro is just the first of several Belkin products that Ashton believes will put feedback loops into effect throughout the home. Ashton worked on RFID chips at MIT in the late 1990s and lays claim to coining the phrase “Internet of Things,” meaning a world of interconnected, sensor-laden devices and objects. He predicts that home sensors will one day inform choices in all aspects of our lives. “We’re consuming so many things without thinking about them—energy, plastic, paper, calories. I can envision a ubiquitous sensor network, a platform for real-time feedback that will enhance the comfort, security, and control of our lives.”

  As a starting point for a consumer-products company, that’s not half bad.

  If there is one problem in medicine that confounds doctors, insurers, and pharmaceutical companies alike, it’s noncompliance, the unfriendly term for patients’ not following doctors’ orders. Most vexing are patients who don’t take their medications as prescribed—which, it turns out, is pretty much most of us. Studies have shown that about half of patients who are prescribed medication take their pills as directed. For drugs like statins, which must be used for years, the rate is even worse, dropping to around 30 percent after a year. (Since the effects of these drugs can be invisible, the thinking goes, patients don’t detect any benefit from them.) Research has found that noncompliance adds $100 billion annually to US health care costs and leads to 125,000 unnecessary deaths from cardiovascular diseases alone every year. And it can be blamed almost entirely on human foibles—people failing to do what they know they should.

  David Rose is a perfect example of this. He has a family history of heart disease. Now forty-four, he began taking medication for high blood pressure a few years ago, making him not so different from the nearly one-third of Americans with hypertension. Where Rose is exceptional is in his capacity to do something about noncompliance. He has a knack for inventing beautiful, engaging, alluring objects that get people to do things like take their pills.

  A decade ago, Rose, whose stylish glasses and soft-spoken manner bring to mind a college music teacher, started a company called Ambient Devices. His most famous product is the Orb, a translucent sphere that turns different colors to reflect different information inputs. If your stocks go down, it might glow red; if it snows, it might glow white, and so on, depending on what information you tell the Orb you are interested in. It’s a whimsical product and is still available for purchase online. But as far as Rose is concerned, the Orb was merely a prelude to his next company, Vitality, and its marquee product: the GlowCap.

  The device is simple. When a patient is prescribed a medication, a physician or pharmacy provides a GlowCap to go on top of the pill bottle, replacing the standard childproof cap. The GlowCap, which comes with a plug-in unit that Rose calls a night-light, connects to a database that knows the patient’s particular dosage directions—say, two pills twice a day, at eight A.M. and eight P.M. When eight A.M. rolls around, the GlowCap and the night-light start to pulse with a gentle orange light. A few minutes later, if the pill bottle isn’t opened, the light pulses a little more urgently. A few minutes more and the device begins to play a melody—not an annoying buzz or alarm. Finally, if more time elapses (the intervals are adjustable), the patient receives a text message or a recorded phone call reminding him to pop the GlowCap. The overall effect is a persistent feedback loop urging patients to take their meds.

  These nudges
have proven to be remarkably effective. In 2010 Partners HealthCare and Harvard Medical School conducted a study that gave GlowCaps to 140 patients on hypertension medications; a control group received nonactivated GlowCap bottles. After three months, adherence in the control group had declined to less than 50 percent, the same dismal rate observed in countless other studies. But patients using GlowCaps did remarkably better: more than 80 percent of them took their pills, a rate that lasted for the duration of the six-month study.

  The power of the device can perhaps be explained by the fact that the GlowCap incorporates several schools of behavioral change. Vitality has experimented with charging consumers for the product, drawing on the behavioral-economics theory that people are more willing to use something they’ve paid for. But in other circumstances the company has given users a financial reward for taking their medication, using a carrot-and-stick methodology. Different models work for different people, Rose says. “We use reminders and social incentives and financial incentives—whatever we can,” he says. “We want to provide enough feedback so that it’s complementary to people’s lives, but not so much that you can’t handle the onslaught.”

  Here Rose grapples with an essential challenge of feedback loops. Make them too passive and you’ll lose your audience as the data blurs into the background of everyday life. Make them too intrusive and the data turns into noise, which is easily ignored. Borrowing a concept from cognitive psychology called pre-attentive processing, Rose aims for a sweet spot between these extremes, where the information is delivered unobtrusively but noticeably. The best sort of delivery device “isn’t cognitively loading at all,” he says. “It uses colors, patterns, angles, speed—visual cues that don’t distract us but remind us.” This creates what Rose calls “enchantment.” Enchanted objects, he says, don’t register as gadgets or even as technology at all, but rather as friendly tools that beguile us into action. In short, they’re magical.