概要： 导读：刚毕业的大学生，突然觉醒，认识到算法对他自己现实世界的介入如此潜移默化。很多选择是真得来源于他自己的意志么？还是各种算法的推荐累加，最终导致他做出的决定。他觉得时候考虑跟女朋友同居这件事在决策上的合理性了。 Fr...
Free Will in an Algorithmic World
In this brave new world, many of our choices aren’t choices at all
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.
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.
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.
Tai现在听到Spotify（流行的音乐App） “发现”功能为他选择的Chance the Rapper，在他的卧室墙的另一边咚咚作响，卧室的墙面，在东面窗户透过的冉冉升起的太阳光芒中发光。是时候出去面试了。他找一个优步带他去校园。价格是11.23美元，感觉有点不合理;昨天同一路线的价格为9.34美元。他关闭应用程序并重新启动它。现在的价格是10.82美元。Tai目前还不清楚为何价格会有变化，但他这次确认了预订，站在门口等着预订到的司机开着丰田卡罗拉过来接他。
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.
这一切似乎都是随机的。但他不禁怀疑Facebook，谷歌，Tinder和亚马逊所采用的算法在其目前的情况下可以发挥作用的程度。他是否可以从一个程序员那里，通过一个虚构的等式，测试出他下一个工作？这项工作真的是他生命和职业生涯中最好的选择，还是过去决定无关紧要的偶然结果——都基于他点击鼠标和在屏幕上滑动的日常行为？Tai喜欢把自己想象成坐在驾驶员的座位。但这次优步打车的经历表明他不是 - 无论是比喻还是字面上。
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.
自2004年以来，我一直在沃顿商学院教授一门名为“应用技术”的课程。事后我应该将其命名为“科技中有什么”，因为这是一个更准确和描述性的名称。多年来这门课程中一直保持不变的一个主题是算法决策。Tai问出的问题——“我们在多大程度上控制了自己的行为？” - 这种问题越来越多地出现在课堂上。
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.
正如一些产品设计师所指出的，这种行为如此普遍的原因，在于流行的产品设计理念 - 例如使用通知和游戏化来增加用户参与度 – 开发和扩大人类的弱点：例如我们需要社会的认可，还有，即使我们认识到做某些事情会带来长期成本，但因为可以得到即时的满足，我们却没有能力抵抗不去做它。虽然我们可能觉得我们正在做出自己的选择，但其实我们常常被推动，甚至被蛊惑着做出了选择。
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.
我们还体验了算法对社交媒体网站的影响，我们可能会相信，朋友是我们所看到的内容的主要驱动因素。实际上，算法起着同样重要的作用。 2012年，Facebook进行了一项研究，调查了他们的新闻提要算法，他们向一些用户展示了更多的“硬新闻”——也就是更多的是“伊拉克战争”，而不是“装在盒子里的猫”。然后他们测量了这同一批用户中有多少人点击了2012年11月我们大多数人在Facebook Feed的顶部看到的“我投票”按钮。
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.
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