Hacking Happiness (6 page)

Does this prove I’ve quantified happiness in some way? Not at all, but it’s a start. Keep in mind I only used one data point—my heart rate—to measure my reaction to the video. If I used an app like Emotion Sense, I would also get time-stamped data relating to my mood and the tone of my voice. If I utilized a service like WeMo with home automation technology and utilized their motion sensors, I could send a text to my wife if I slapped the table hard enough while laughing. We’ll get to the point when we may feel machines know our emotions better than we do.

Note that my lowered heart rate finding due to smiling does have scientific precedent. In “De-Stress in Three Seconds,” author Cassie Shortsleeve reports about a study conducted by Sarah Pressman and other researchers from the University of Kansas in which college students were asked to hold chopsticks in their mouths to simulate a smile before facing a stressful situation. Compared to their non-chopstick counterparts, smilers had lower heart rates and reduced stress, leading researchers to believe the physical triggering of facial muscles to smile sends a message to your brain that says, “You’re happy—calm down.”
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So what if I did a longitudinal study around my Cardiio experiment for a year, adding in whatever sensors I could think of? Would there come a point where I could prove to you that a certain amount of data proved I was experiencing a certain emotion? Probably. Keeping in mind, as in the case of taking a survey, that I know I’m recording myself and have a bias toward laughing.

But my point is not to quantify emotion for its own sake. My goal is to demonstrate how intimately connected we are to the data we’re outputting and capturing in ways we’ve never done before. Mobile and home sensor technology is fairly cutting-edge, as is the trend of average consumers being able to capture their data. And remember, data is a currency. People pay for it. Think how Kmart’s PR value would go up if they could prove that a thousand people doing my Cardiio test watching their commercial lowered their heart rates over time and significantly improved their health.

The idea may seem far-fetched until you hear about a company like Neumitra, featured in the
MIT Technology Review
article “Wrist Sensor Tells You How Stressed Out You Are,” written by David Talbot. Neumitra has a device called bandu that’s compatible with smartphones that can measure stress via increased perspiration or elevated skin temperature.
⁸
To research the piece, Talbot wore the device and tried to recite the alphabet backward in front of a group of strangers, resulting in his stress increasing by 50 percent as measured by wrist sweat and temperature.

Companies like Affectiva have also developed technology along these lines to recognize human emotions in the form of facial cues, letting brands test to see whether ads are engaging with consumers.
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Much like my Kmart example, if a thousand people watching a certain video don’t laugh as measured by Affectiva, it’s a good sign the commercial is a clunker. I see this model moving to the social TV arena,
¹⁰
which is the trend of people interacting with live television programs or with other fans during prerecorded shows.

Whether facial recognition technology employed by Affectiva or Microsoft Kinect is reading our expressions during a show or
our phones are measuring our reactions, our emotional output will be captured in one form or another. In terms of measuring stress, I think about watching a show like
24
and wonder at what point the TV would shut off if my heart rate got too high. Or when I’d get a call from my insurance carrier telling me to watch
Modern Family
to calm down before my rates got increased.

The emergence of quantified tracking of behavior signals that the avataristic form of well-being is fading in importance. While people will always follow influencers and repeat what they say, as we grow more comfortable with our actions being tracked, we’ll be able to quantify emotions, or at least agree on the proxies for emotion based on physiology. Our actions will reveal our true characters. And reputation will more closely mirror our true selves versus the avatars we currently broadcast to the world.

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ACCOUNTABILITY-BASED INFLUENCE

In the twentieth century, the invention of traditional credit transformed our consumer system and in many ways controlled who had access to what. In the twenty-first century, new trust networks and the reputation capital they generate will reinvent the way we think about wealth, markets, power, and personal identity in ways we can’t yet even imagine.
¹

RACHEL BOTSMAN

M
Y MOM RECENTLY
decided to move, now that it’s been two years since my dad died. After decades of meticulous financial record-keeping and making payments on time, she learned she had to restart her credit score from scratch as a widow. Reminiscent of the gaping flaw in the GDP of not measuring women as primary caregivers, this practice also highlights the need to overhaul an outdated system.

Credit reporting’s history began more than a century ago, beginning with small retailers banding together to trade financial information about their customers. The early credit associations often focused on collecting negative financial information about people as well as data about sexual orientations and other private behavior. Oftentimes it was this private information that would justify associations’ denying services, reflecting negatively on people’s reputations.

Not exactly a hallowed past regarding our financial forefathers.

Just as harrowing as this fiscal bigotry from credit associations was their lack of transparency. As Malgorzata Wozniacka and Snigdha Sen noted in their article “Credit Scores: What You Should Know About Your Own,” it wasn’t until 2001 that people could gain direct access to their credit scores.
²
This created a precedent for opaque collection practices around consumer information that data brokers have emulated in the online world. We have time in our Connected World, however, to wrest data back from brokers and control our identities and fates.

I wrote a piece for Mashable in 2011 called “Why Social Accountability Will Be the New Currency of the Web.”
³
I was fascinated with online networks that had measurements reflecting trust generated by action where ratings were based on what people had done versus just how they were perceived as people.

One of the first places I looked was in the business world. Measuring performance is not a new idea, but typically it’s only managers who rate employees based largely on their productivity. New models have emerged, however, that aggregate peer-to-peer comparisons to form a picture of someone’s overall accountability, or reputation. One of these is Work.com, formerly known as Rypple and now a part of Salesforce.com. For my piece, I interviewed Nick Stein, who, at the time, was director of content and media for Rypple and is now senior director, marketing and communications, at Salesforce.com. A “social performance” platform, Work.com aggregates positive feedback (in the form of recognition) provided by colleagues. This recognition appears on an individual’s social profile, providing a snapshot of that person’s capabilities—as determined by their peers—thereby contributing to their reputation at work.

I asked Stein if he saw a day when someone’s Work.com score could become portable, meaning it would follow an employee from one job to the next. While he felt the number of variables depen
dent on the context of one organization might not translate to a second one, he did feel measures like Work.com would have an influence on reputation.

As we move toward a more social and transparent workplace environment, influence is becoming less dependent on your place in the org chart and more on the real, measurable impact you have on your colleagues. The idea is that all ongoing feedback, both positive and constructive, helps build an employee’s real reputation at work . . . This enables individuals to develop influence based on their real impact rather than a perception of where they sit in the company hierarchy.
⁴

I want to focus on Stein’s idea of “real impact” now that the Connected World includes technology from sensors allowing quantified measurement. In the same way that brands will measure our emotional responses while watching TV, employers could track employees’ moods or physical data as a reflection of corporate culture or performance. Right now it may be creepy to think of intimate data being visible to employers or peers, and employment policies need to protect information about sensitive medical conditions or other data people don’t want to share in a work environment.

But let’s examine the rise and implementation of social media in the workplace as a precedent for how sensor data could be adopted in the future. When social media first arrived, privacy was of huge concern but didn’t keep the medium from becoming a mainstay of modern communication.

I began pitching the idea of blogs or podcasts for the business world in 2005, followed by Twitter, Facebook, and the like as soon as they became available. I sat in dozens of meetings where IT specialists warned about people using their own phones and de
vices at work, and managers expressed concern with employees wasting time on social media. I attended and spoke at hundreds of meetings and conferences discussing these issues and the merits of utilizing social media at work.

I think it’s safe to say social media in various iterations has now been universally adopted for the workplace. Social media policies are in place, employees know the distinction between their public and work personas, and brands understand the vital importance of engaging with consumers where they get their media. I don’t even use the term “social media” anymore—it’s simply “media,” and it’s all social. The process of this adoption of social media in the enterprise has taken roughly a decade.

This precedent of technology focused on our identities in the form of social media will expedite the adoption of sensor data in the workplace.

In 2006, Hitachi approached the MIT Media Laboratory Human Dynamics Group to investigate the opportunities for “social sensors” in the enterprise. The resulting research in
Sensible Organization
provides a fascinating sense of how wearable and proximity sensors could affect the workplace. Part of the research focuses on how social sensors allow employees to visualize aspects of behavior revealed through these technologies. For instance, sensors could reveal which employees are more socially connected in an office, giving managers a way to quantify how best to disseminate communications to their organizations. Employees could also see how their activities could better dovetail with colleagues to increase their effectiveness at work.
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A more recent study of social sensors in the workplace from MIT, “Sensible Organizations: Technology and Methodology for Automatically Measuring Organizational Behavior,” provides other pragmatic examples of technology utilized to improve dynamics among employees. Of particular interest is the “meeting mediator,”
⁶
which uses sociometric badges (lanyards worn by employees
measuring vocal tone and proximity) to help people understand how they’re participating in a conversation. Displayed on a tablet or computer, employees are represented by shapes that equate to their physical location in a room. Depending on how often they speak and for how long, color patterns shift in the meeting mediator display, reflecting patterns in the conversation.

Fig. 1.
Meeting mediator
is an example of a mobile phone–
sociometric
badge application. Each square in the corner represents a participant. The position of the center circle denotes speech participation balance, and the color of the circle denotes the group interactivity level. Fig. 1(a) shows a well-balanced and highly interactive group meeting, whereas Fig. 1(b) shows that participant
Y
is heavily dominating the conversation with a low level of turn taking between the participants.