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Free Will in an Algorithmic World
Tai, a senior at the University of Pennsylvania, wakes up at the perfect time every morning—well-rested, but not late for classes or appointments. Today that meant rising at 7:18 a.m. He did not set his alarm for that time. Rather, it was chosen for him. His phone’s sleep-tracker app had been following his sleep patterns over the past few months, monitoring his REM cycles and periods of lighter rest. Using this information, it set a smart alarm that wakes him during a light stage of sleep, while also trying to maintain some level of consistency over time. The theory is that this schedule will prime Tai for greater energy and concentration throughout the day.
Tai needs to be sharp. He’s at a turning point in his life, about to step away from the relatively safe world of college—of information-gathering, homework, and exams—into the “real” world of practical problem solving: finding a job, choosing a place to live, and negotiating the wonderful but complicated details of a romantic relationship that’s getting more serious by the day.
Tai rolls over in bed and, with one eye open, grabs his phone and checks his notifications: 14 likes on his latest Insta, seven Facebook notifications, and three comments on his new Facebook profile picture. Not bad for a Monday night. He scrolls down his Facebook feed. An article shared by his friend Harry grabs his attention with its headline, “The Wealth of New Choices With Robot Vacuum Cleaners.” He clicks and, liking what he reads about the Eufy RoboVac cleaner, forwards the article to his girlfriend, Kate.
There’s an email from his mom, too, with a link to a New York Times article, “What I Wish I’d Known Before Moving in Together.” Tai groans. Mention even a possibility to his mother, and she sets it in stone. The picture accompanying the article shows an attractive couple in their thirties sitting on an unblemished white staircase, smiling into each other’s eyes. He types, “Ha ha thanks. That middle-aged couple looks happy, see. How did you find this?” Calling them middle-aged will definitely get on his mom’s nerves. But there’s no time for more needling: It’s already 7:28 a.m.
Tai rolls out of bed and, walking across his dusty carpet, opens his dresser, pulling out a pair of stretch washed chinos from Bonobos (he follows the online clothing retailer on Instagram), blue-and-gray argyle socks (top-rated on Amazon), and a dress shirt and tie. He has a job interview today.
As he sits down for breakfast, Tai thinks of the fortuitous circumstances that led to the interview. He found the job posting through his friend Samantha, who LinkedIn’s algorithms had reminded him to congratulate on her six-month work anniversary. Their conversation had been a little awkward, as Tai and Samantha had matched on Tinder a few years earlier. She was an artsy girl with a bubbling self-confidence; lots to like about her, but neither of them felt any sparks. And although they became friends, it had been hard for Tai to keep up with her since she graduated, especially since Kate wasn’t Samantha’s biggest fan.
Tai’s friendship with Samantha is hardly the only thing that’s been getting on Kate’s nerves lately. Their discussion about possibly moving in together seems to be stressing her out. Over the weekend, Tai had sent Kate a Huffington Post recommended article: “15 Things Couples Should Do Before Moving In Together,” which she read with great interest—especially point number 15, “Have an exit strategy.” Tai suggested that if they did split up, it would make sense for her to be the one to move out—after all, he had found the new apartment for the two of them. But it was only a contingency plan. Her angry texts on the subject were still awaiting his reply.
After dressing, Tai checks his phone again to see if there are more texts. Nothing new from Kate, but there is a reply from his mom about the Times article: “Oh, I was looking for housewarming gifts for you and Kate, and it popped up on Google. Why don’t you send it to her, sweetie? And good luck on your interview this morning!”
Tai can hear Chance the Rapper, chosen for him by Spotify Discover, rapping on the other side of his bedroom wall, which is now glowing with the light of the rising sun from the east window. It’s time to head out for the interview. He looks for an Uber to take him to campus. The price is $11.23, which feels a bit steep; yesterday it had been $9.34 for the same route. He closes the app and relaunches it. The price is now $10.82. It’s not clear to Tai why it changed, but he confirms the booking this time and waits at his door for the Toyota Corolla to pull up.
As he exchanges pleasantries with the driver, Tai opens a notebook to work on his case interviews, the part of business school job applications where students are asked to think through a challenging business scenario and present a solution. The case prep document shared by another student includes the question: What is root cause analysis?
Tai jots down some notes, applies that technique to analyze his day today, and produces a diagram:
It all seems kind of random at one level. But he can’t help but wonder about the degree to which the algorithms employed by Facebook, Google, Tinder, and Amazon have a role to play in his present circumstances. Will he have some cooked-up equation from a programmer to thank for his next job? And is this job really the best next step for his life and career or just the accidental result of inconsequential past decisions—clicks of a mouse and swipes on a screen? Tai likes to think of himself as being in the driver’s seat. But this Uber ride suggests he’s not — both figuratively and literally.
Or maybe he’s just overthinking things, the aftereffect of an in-class discussion we had on personalization algorithms just a few days earlier. He sends me an email: “Have something interesting to show you. Do you have 10 minutes after class?”
Tai sighs and shuts his notebook. Maybe all he and Kate need is to get away for a bit to reconsider this moving-in idea. He pulls out his phone and opens Expedia’s app. It might have some good hotel recommendations.
Since 2004 I’ve been teaching a class at Wharton called “Enabling Technologies.” In hindsight I should have named it “What’s Going On in Tech,” because that’s a more accurate and descriptive name. One topic that has remained a constant in the course through the years is algorithmic decision-making. The sort of question that Tai asked—to what extent are we in control of our own actions?—is coming up in the class more and more often.
Consider these facts: 80 percent of viewing hours streamed on Netflix originate from automated recommendations. By some estimates, nearly 35 percent of sales at Amazon originate from automated recommendations. And the vast majority of matches on dating apps such as Tinder and OkCupid are initiated by algorithms. Given these numbers, many of us clearly do not have quite the freedom of choice we believe we do.
One reason is that products are often designed in ways that make us act impulsively and against our better judgment. For example, suppose you have a big meeting at work tomorrow. Ideally, you want to spend some time preparing for it in the evening and then get a good night’s rest. But before you can do either, a notification pops up on your phone indicating that a friend tagged you on Facebook. “This will take a minute,” you tell yourself as you click on it. But after logging in, you discover a long feed of posts by friends. A few clicks later, you find yourself watching a YouTube video that one of them shared. As soon as the video ends, YouTube suggests other related and interesting videos. Before you know it, it’s 1:00 a.m., and it’s clear that you will need an all-nighter to get ready for the following morning’s meeting. This has happened to most of us.
The reason this behavior is so common, as some product designers have noted, is that popular design approaches—such as the use of notifications and gamification to increase user engagement—exploit and amplify human vulnerabilities, such as our need for social approval or our inability to resist immediate gratification even when we recognize that it comes with long-term costs. While we might feel as if we are making our own choices, we’re often nudged or even tricked into making them.
Another reason we aren’t truly in control of our choices is that when we search for a hotel on Expedia, browse online dating profiles, or shop for a book, we’re seeing only a small fraction of all the potentially relevant information available. Although we experience a clear sense of free will by making the final decision regarding what we see, read, or buy, the fact is that 99 percent of all possible alternatives were excluded.
You probably don’t mind saving all the time you might have wasted in sifting through inferior options to arrive at a final choice. But algorithms do not simply help us find products or information quickly, which we might have found eventually without their assistance. In truth, they exert a significant influence on precisely what and how much we consume.
The conventional narrative is that algorithms will make faster and better decisions for all of us, leaving us with more time for family and leisure. But the reality isn’t so simple.
We also experience the impact of algorithms on social media websites, where we are likely to believe that our friends are the chief drivers of the content we see. In reality, algorithms play an equally important role. In 2012, Facebook conducted a study in which they tweaked their news feed algorithm to show some users more “hard news”—think more “war in Iraq” and less “cats fitting in boxes.” They then measured how many of these users clicked the “I voted” button that most of us saw at the top of our Facebook feed in November 2012. They compared the self-reported voter turnout of this group against a control group whose news feed algorithm had not been modified. The researchers found that users who had their news feed algorithm tweaked increased their voting turnout by three percentage points, from 64 percent for the control group to 67 percent for the treatment group. A follow-up survey found that these users were also significantly more likely to report that they paid attention to government. Three percentage points might not sound like much, but the outcomes of elections, including the U.S. presidential election in 2016, are frequently determined by smaller amounts.
Look around you and ask what drives your product, media, and people choices. Unless you are a tech Luddite, algorithms are silently rearranging your life. The conventional narrative is that algorithms will make faster and better decisions for all of us, leaving us with more time for family and leisure. But the reality isn’t so simple. In this brave new world, many of our choices are in fact predestined, and all the seemingly small effects that algorithms have on our decisions add up to a transformative impact on our lives. Because who we are, ultimately, is the sum total of the various decisions we make over a lifetime.