Hacking Happiness (16 page)

If you haven’t tried to categorize large sets of data, I can tell you from experience that it can be overwhelming to try to make sense of multiple types of information all related to your business or life. But once a framework for understanding has been established, the value of the insights mined from Big Data can be transformative. This is why finding someone to interpret what your data means is of paramount importance.

When the New Oil Is Crude

The phrase “Data is the new oil” is attributed to a woman named Ann Winblad, senior partner at Hummer Winblad Venture Partners. It squarely positions data in an economic sense via a metaphorical comparison to the oil industry. And in the same way that the control of oil can dictate economic advantage, the interpretation of data can steer decisions that can deeply affect the outcome of an individual, company, or organization. Like oil, data also has
to be refined for it to have value to an organization, or it remains “crude” and unusable.

The critical decisions of refinement are being left more and more to data scientists, the Merlin-like programmers who work to determine how best to manage an organization’s information. Up to now, this role has typically been filled by an IT staffer tasked with organizing company infrastructure to benefit corporate information. But the vast wealth of data at modern organizations requires a new set of skills that includes marketing savvy along with digital expertise. As Claire Cain Miller reports in the
New York Times
, Big Data expertise is so new that curricula or programs haven’t been developed for the field. Data science is also such a broad field of study that it’s more of an academic discipline than just a smattering of specific courses.
⁷

The danger of allowing data scientists to be the sole evaluators of how data should be interpreted is that they may not always know the full context of how it’s going to be used. In the Big Data industry, this tension is referred to as domain versus data science expertise. As an example, a marketing-focused employee at an organization may want to understand what the social sentiment about a certain product means regarding a recent sale. However, not being versed in the tools of sentiment analysis, the marketer won’t know the specific type of report to ask for from a data scientist.

I discussed this issue in an article for Mashable, “Big Data’s Value Lies in Self-Regulation,”
⁸
with Jake Porway. Jake is the founder of DataKind, an organization that brings together leading data scientists and high-impact social organizations through a comprehensive, collaborative approach that leads to positive action through data. Here’s an excerpt from the piece with regard to finding a balance between knowing what to ask for from data and how to interpret it:

“My biggest fear is that data science is used as a blunt tool and that people don’t understand the cultural implications
of quantifying our world,” says Jake Porway . . . [who is] as much a data philosopher as scientist. Gifted at navigating the channel between hacking and hypothesizing, he is adamant about helping people understand how to create context as well as code for insights based on big data. [Regarding this balance,] he says, “This due diligence should be embedded in our craft.”
⁹

The amount of information available via Big Data means organizations need to break down silos between IT and marketing, whatever people’s titles. More data is a blessing as long as everyone works together to make the best sense of what it means.

From Big to Little Data—Profit from the Personal

The term “Little Data” has evolved as a label for the digital information directly relating to consumers. This could be output from your quantified self app or data from sensors in your car relating to your driving behavior. But whereas Big Data refers to a multifaceted organization, Little Data is focused squarely on you. Mark Bonchek describes the evolving relationship between Big and Little Data in his article “Little Data Makes Big Data More Powerful,” citing the need for brands to begin empowering customers by helping provide them with this granular information about themselves to make more informed purchasing decisions.
¹⁰
Note that “Little Data” in this context doesn’t mean there’s less information available for analysis; it means the analysis is focused on just your data. The applications for this level of data scrutiny are endless. Patrick Tucker even showed how two researchers could predict a person’s approximate location up to eighty weeks into the future at an accuracy level above 80 percent.
¹¹

If Little Data can predict your behavior almost two years into
the future, it should be obvious by now how important it is to get a handle on your data.

In my Mashable article “Big Data’s Value Lies in Self-Regulation,”
¹²
I interviewed Martin Blinder, founder of Tictrac, a platform that aggregates apps to help create and manage user’s projects to manage their day-to-day lives. The service is gaining a lot of traction with users, largely because it appeals to the notion of Little Data by functioning as a sort of iTunes marketplace for all of the “life project” apps currently in the marketplace. If users already have a number of different devices, they can aggregate them with Tictrac and focus on a specific type of program, like health or fitness. The company has brokered deals with multiple partners to help achieve this goal, and its platform also syncs with over forty application programming interfaces. Functioning as a data dashboard, Tictrac will eventually begin to learn a user’s behavior to personalize information. Blinder believes this type of evolved adaptation will help people design their lives in the future. “By creating a context around lifestyle design, we’re enabling a world where anybody can find data relevant to them. I feel we’re reaching a point in history where we can really empower ourselves based on an understanding of our own data.”
¹³

Like many aspects of technology, its greatest power is the ability to disappear so users can focus on improving their lives.

From Broken to Broker

Your personal data gets around. Sometimes it’s little, focused on your individual actions. Sometimes it’s part of a big picture, a part of an economy that’s still in its infancy. Right now, advertisers and data brokers are Hacking Your H(app)iness, analyzing the behavior on what brings you meaning to mine insights for their commercial gain. Once you realize your data is an asset, however, you’ll claim it as your own and get rid of the middleman.

You’ll become the data broker. You’re the agent for your digital identity, the manager for your connected content. If you get upset at the idea of identity theft, you should be livid at the notion that someone else will make money off your personal data. And if you still don’t believe me, wait until you see how things will look in the near future.

  9  

AUGMENTED REALITY

There is no other future of computing other than [Augmented Reality] which can display information from the real world and control objects with your fingers . . . it’s the keyboard and mouse of the future.
¹

MERON GRIBETZ, FOUNDER AND CEO, META

I
WROTE A SHORT
story in 2012 that describes how I see augmented reality working in our very near future, a (Google) Glass half-empty/half-full scenario to whet your appetite regarding the possibilities of how geeky tech will influence our lives.

SELF-SCREENING

I lurched from the train car, elbow to elbow with a thousand other commuters stepping off New Jersey Transit. I jerked my head to the right and heard a chime indicating my CPRS was online. A bright red arrow hovered in the air before me, analyzing the platform leading to the stairs going up to the main platform of Penn Station.

“Go right.” Sean Connery’s brogue sounded in my brain as a red line appeared on top of the horde of pressing flesh,
all vying for the same staircase. As I turned my head, the line flashed green when my best virtual path appeared be-fore me.

IBM’s CPRS (Consumer Pattern Recognition Simulator) lets you set the voice that navigates your actions through a virtual commuter game. (Connery’s voice had been chosen for me because I was a fanboy.) The app worked for any major New York transportation hub and was the latest in IBM’s Smarter Cities offerings. It utilized image-recognition-based augmented reality to analyze results of multiple predictive formulas to create algorithms based on commuter behavior. The game played out on my iPhone 8 contact lenses.

“What arrr yoo prepared to dooo?” Nice. Connery’s quote from
The Untouchables
.

I headed toward the stairs. In my urgency, I bumped a woman next to me, and she grunted. In the upper-right-hand corner of my vision, I saw my points decrease on a small New Jersey Transit con.

“Fuck!” I muttered, apologizing and letting her pass. In my ear I heard the sound of a baby crying and my points dropped even further. The AR in my contact lenses analyzed her past fifty tweets and discovered she was pregnant. Son of a bitch.

Everyone’s actions in the game were tied to real-world penalties and rewards. Early social-based action apps like Recyclebank and DailyFeats were still in use to encourage people to earn free stuff or gain social cred. But apps like GymPact where, by choice, you were penalized by your peers for not going to the gym had become wildly popular. Geek-chic went from craving Klout to demonstrating your accountability, and the craze had caught on with local government and utilities companies. I regularly did my laundry
at three in the morning to get a high ABI (accountability-based influence) score from OPower, the leading social network based on the Smart Grid.

In my case, my next month’s commuter pass would cost about fifty cents more because of bumping a pregnant lady. So now I had to make up my points via speed. I started walking fast. A heart-shaped icon appeared in the upper left-hand corner of my vision as the pulse monitor watch grew snug on my wrist. If the heart went from red to purple, my doctor would get a text indicating I was at risk for cardiac arrest. The monitor went all the way to magenta four times one month and my insurance premiums increased.

Once at Penn Station I headed for the stairs, noting the commuter-gamers outside Starbie’s. (Certain sims let you order your coffee mid-play so you could pick it up right away and mobile-pay via NFC.) Distracted by the aroma of fresh-brewed coffee, I stumbled on something large at my feet. I looked and saw a large sack of grain. A money icon appeared in my vision over the bag, so I pulled my eyes to the left, indicating I would take the points for the grain. Frustrated at having to wait for the points to tally, I kicked the sack, hard. Then I ran upstairs.

As I neared the middle of the station, a red stop sign icon filled my vision. I paused, not sure what was happening. Virtual Air Rights codes had deemed it unlawful for advertisements or any game component to trick someone when using augmented reality–based app functionality.

I heard a new voice in my ear. “Chuck, look up.”

This freaked me out, as none of my voice recognition software was programmed to speak unless I spoke first. And most of my sims used eye tracking or Microsoft Kinect to recognize my gestures before I heard external voices in a game.

I looked up as I heard the board clicking, the shifting words forming the following phrase:

All the world’s a screen, and we are merely layers.

I stood for a long minute, gazing at the board and not really comprehending what was happening. I vaguely registered that my contact lenses were in reality mode, meaning the board actually said the words I saw above me.

“You a Shakespeare fan?” the voice came again.

“Sure?” I said, turning to see where the voice was coming from.

“Up here, Chuck.” I looked back at the board, and one side of the screen was shaped like a smiley-face icon. The lips moved when it spoke. “Thought I’d go with a smiley face versus a scary
Tron
-looking thing. Besides, part two sucked.”

“Agreed.”

“They call me the Bard. A few years back MoMA did a real-time data exhibit thing and they ran Shakespeare quotes on my screen. Somebody got cute and took the ‘o’ out of ‘Board’ and it trended on Twitter, so here we are.”

I looked at the other side of the screen, opposite his “face.” “So what’s with the quote? Am I a ‘mere layer’?”

I assumed the metaphor had to do with the Smart Grid, where the notion of Big Data meant that with networked artificial intelligence, we’d arrived at an Internet of Things mentality. In a sense, everything with a chip in it was alive, or in this case, a layer. Being a geek, I’d felt the whole idea of the singularity was inevitable starting around 2011 or so. I was also sure Bard was hooked to the Internet and dozens of cameras in the station that pumped images he could access anytime from the cloud.

“Sort of,” Bard responded. “Don’t get pissed, but I accessed your e-mail and social channels just now.”

I wasn’t that pissed. “Privacy” had a whole new definition these days. Since a GPS knew where you were at all
times and everyone’s virtual games were hooked real-time to the Web, government types simply accessed video or Outernet feeds from citizens any time they wanted. Everyone’s lives were recorded at all times. According to CNN, no event occurred without at least two cameras recording what happened for potential public usage. News and law enforcement had become whole different animals in the past few years.