The Naked Future (23 page)

Her central argument is this: our personalities are governed by how different neurotransmitters interact. Dopamine-led people are, in Fisher's words, “curious and energetic.” This category is for eccentrics, people who love to travel, can't stop asking questions, display a certain degree of impetuousness, and are eager to explore the world. It's the category in which she places herself. If you're more cautious and inclined to follow the rules, you're serotonin led.
An analytical and tough-minded arguer? Your temperament dimension is testosterone based. Finally there's the estrogen-based personality characterized by empathy and attentiveness. The estrogen profile is the quintessential nice guy or nice girl.

Fisher is not the first researcher to propose a matrix to pigeonhole people into different personality types. Ernest Tupes and Raymond Christal's five-factor model, which scores the personality on the basis of openness, conscientiousness, extroversion, agreeableness, and neuroticism is perhaps the most widely known. The fundamental flaw with these personality matrices is they aren't based on biology, says Fisher. They start with an assumption rather than a hypothesis that could be falsified with real evidence from fMRI data. “Make the questionnaire based on what you know from biology, and then go back to the biology to study whether, in fact, what you say you're studying, you actually are studying,” she says. As she explains it, “The bottom line is, I am not studying your culture. I'm studying your biology. I'm only studying traits that I know have a biological basis.”

To demonstrate the validity of her theory, Fisher and her colleagues conducted fMRI scans on a wide assortment of people and have also designed a questionnaire (she refers to this as the Fisher Temperament Inventory), which seeks to measure “the degree to which one expresses aspects of these four trait constellations.”

She's also played a key role in a major survey effort at Match .com called Singles in America, which is America's largest survey thus far on dating habits. It's a first-of-its-kind big data study on dating, featuring responses from more than 107 million people who took the survey on Chemistry.com (also part of IAC's portfolio of dating sites) and Match.com. Among the findings from the survey released in the most recent study:

• A friends-with-benefits arrangement is becoming more mainstream every year. Some 44 percent of surveyed adults admitted to having been in a friends-with-benefits relationship in 2012, up from 20 percent in 2011.
  
• Your friend with benefits should be monogamous. More women than men say they would prefer to be in an exclusive relationship before going to bed with a partner (37 percent of single women in 2012, 31 percent in 2011, and 25 percent in 2010).
  
• Perhaps the best finding for Match.com's bottom line: the surveys show that more people are looking for love on the Internet first and other places second. Far more people meet online today than they do in bars. Nearly 30 percent of the singles surveyed had dated someone that they met online and 20 percent had met their most recent partner through a Web site. Only 7 percent said they had dated someone they met at a bar.
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“What big data can do for you is find patterns in behavior and personality that you would never find in a small sample—never find it because there's too much noise,” says Fisher. “The vast majority of personality questionnaires, and all kinds of questionnaires, are based on the college population, for heaven's sake.”

Like Yagan, Fisher is also interested in using data from mobile apps to take profile matching to an entirely new level. But she's looking for something rather more ambitious than a simple hookup app. What she wants is “the kind of app that uses what we know from evolutionary psychology, body language, linguistic studies, that really sums up a deeper understanding of who you're talking to . . . I mean, we spend our lives trying to size up the people around us constantly. And I think we're missing an awful lot of data, unless we start using apps that really do talk about word usage, body language.”

This is what makes Pentland's work with the sociometer so potentially valuable to the future of dating and marriage. Because the sociometer provides a means to
continuously
see how your personality is affecting the person closest to you, it can provide a telemetric monitor for relationship health. After the experiment concluded, Anmol Madan actually created a program called a Jerk-O-Meter, which ran on a Zaurus VOIP phone.
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The program worked just as you might imagine. When the owner's attention or interest in the phone conversation began to flag, the program would send out such helpful notifications as “stop being a jerk.” When Madan revealed the app, it received coverage from CNN, the
New York Times
, and other major media outlets, but it never emerged as a viable commercial product. Like Leonardo da Vinci's helicopter or Friendster, the program paid the price for being ahead of its time. The Zaurus was not a popular device commercially and the iPhone was still in its infancy at the time of development. Moreover, the idea of self-monitoring personal conversations for “degree of jerk”
probably struck consumers as bizarre. People have been having conversations since, well, before there were people. Why should we now use a device to help us do the most natural thing in the world?

Today, Madan has his hands full with a new start-up, Ginger .io, which is applying telemetric signaling and predictive analytics to health. This arguably is a more noble cause than matchmaker tech. And the market for relationship software to help couples digitally analyze how they speak to each other doesn't really exist. But the utility of telemetric communication analysis is being proven. The testing ground just happens to be someplace other than love.

There's a reason people sometimes claim to feel married to their job. Marriage takes work, yes, but our work life has a lot in common with a long-term romantic relationship. Collaboration styles have a huge influence on outcome and performance. But there's a key difference: poor collaboration between two people in a workplace can hurt an entire organization, resulting in lost revenue or worse. This is why its employers are leading the way in developing techniques to actually collect real-time relationship data.

In the big data present, the honest signals that occur between people, the inaudible notes that make up the tone and character of our interaction beyond what is literally said, are mostly lost. In the naked future that ability spreads to more people and more couples. Suddenly, a lot of people can become much smarter about what
effect their words and actions will have on the person they're with. This future is visible today in the way that a few ambitious organizations and companies are measuring collaboration dynamics.

In 2012, Cindy Caldwell, Christopher Larmey, and statistician Brett Matzke of the Pacific Northwest National Laboratory (PNNL) set out to try to predict where workplace accidents were going to occur around the lab and which teams of employees (or work groups) would be involved. An accident at PNNL is a bit more serious than a stubbed toe or a sprained wrist. The lab, which does work for the U.S. departments of Defense and Energy, is involved in cutting-edge research on nuclear fission, natural gas development, and weapons research. Employees handle volatile, radioactive, poisonous, and highly classified material on a daily basis. A bad day at the lab is a bad day indeed.

Matzke plotted all the accidents that had occurred in the lab during the previous year. He and his coresearchers had to consider all sorts of mishaps, from the ones involving explosive material to more mundane types involving vehicles, falling from ladders, or just misfiling paperwork. They wanted to see if there existed some common feature among them that predicted their occurrence.

They discovered that employees who indicated (via survey) that their relationship with their supervisor was strained, who felt they weren't well listened to, that their concerns weren't shared, and, as a result, weren't
engaged
in their workplace were much more likely to have an accident.

When Caldwell and her fellow researchers added together the scores for (A) whether the group worked with hazardous materials (note: they found that a work group will have 1.9 accidents a year just because they're exposed to hazards); (B) worker engagement; and (C) past operational experience (defined as previous incidents, sick days taken, staff performance, hire and attrition rate for a group), they were able to almost perfectly predict the
number
of
incidents that each work group would experience that year.
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Considering that the work groups contained an average of just sixteen people, it's a short leap from figuring out the weak link work groups to the particular weak link workers in the groups.

That number becomes far more useful if you can also predict
when
that accident will take place. When I asked Caldwell if there might be some way to do that, she acknowledged that constant telemetric monitoring of employee engagement would provide more actionable data than a once-a-year survey.

A couple of years ago a California company, e22 Alloy, began marketing a software-as-a-service (SaaS) application (called Alloy). The company was one of very few start-ups that could analyze the “continuous, objective data of the online activities of the workforce.” The distinction between continuous data collection and spying
is a subtle but important one. Monitoring employee behavior without that employee's knowledge and using collected information to punish employees can indeed be called spying. Forcing employees to submit to having all their computer activity watched is not spying if you tell them you're doing it but that sort of petty office-tyrant behavior isn't going to be good for morale and probably won't be much of a productivity boost, either.

Company founder Josh Gold was very sensitive about the spying applications of his product. In his presentation at Strata 2012, he recommended that employers not use the program without the explicit permission of their staff, and that employees should be able to suspend tracking whenever they choose.

Used properly, this sort of app could provide supervisors with “advance warning” that a big project is headed off the tracks. For instance, if you're a manager and one of your work teams starts communicating a lot more, but tangible work product decreases, that's a warning sign, as is “changing activity patterns,” which could take the form of a lot more e-mails suddenly shooting back and forth at the end of the day and/or a lot of profile updating on LinkedIn.
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Back to love. In the same way that tone, timing, and particular
changes in interoffice chatter can help predict project failure, communication changes between spouses can be indicative of buried problems. Marriage and work really do share a lot in common.

Here's a case in point. My wife and I both work from home and are copartners in a little joint hobby we call “not letting the house become an apocalyptic hellscape.” Succeeding in this endeavor requires a certain amount of vacuuming, laundry folding, moving of trash and recycle bins to the curb, returning them to the side of the house, and dishwashing. It demands effort, management, and communication. In fact, it's very much like a regular job, and each of us has one (or more) of those as well.

More important, neither of us can agree on the definition of “hellscape.” I fall more on the literal side. In fact, if I'm deep in a project, I may not notice that an interdimensional portal has opened over the cat-litter box until Yog-Sothoth the Outer God wraps his cold tentacle around my neck. My wife, meanwhile, knows by sight how many days it's been since someone ran the vacuum.

In our interactions, we'll fall into the role types outlined by Pentland's research. “Do you think we should run the vacuum?” she will ask, taking the explorer role, which my wife uses to talk to me about vacations to faraway places, contemporary issues, and our mutual acquaintances. I do not want to explore the issue of running the vacuum. I will respond that I am too busy and prattle off all the items on my to-do list I feel are more relevant. In doing so, I will speak calmly and evenly, taking the leadership position. My to-do list is something I can speak on with authority. I will win this exchange, but in doing so, I will lose. My wife will run the vacuum but not feel good about it. She has her own to-do list that is as long as mine, but she can make time to play “not letting the house become an apocalyptic hellscape” twice as hard. I detect her feelings and reflect them, rationalizing my own feelings of resentment.

People in long-term relationships approach exchanges with residual notions and emotions from the last exchange. Over time this can erode a person's ability to objectively perceive what's fair or logical in terms of the division of household labor, expenses, goals, and so
on. Communication telemetry could fix this problem. Now imagine the workforce telemetry solution described above in place at home.

If I'm deeply involved in a project, running up on a deadline, then my communication patterns, my Internet usage, my verbal exchanges with my wife will indicate this just as it does when a workplace manager is floundering on a project. In those instances where I truly am too busy, I won't have to tell my wife I don't see the need to vacuum; she will actually be able to verify it herself. I, likewise, could use data from her communication patterns to reach a better understanding of her current stress level, which would speak to engagement with the house.
I don't ever have to see the house in the same way that she does to remember to run the vacuum.
All I have to see is her current stress level and then, without questioning, bring out the Dyson.

This isn't a perfect solution to the problems that arise in long-term cohabitation, but it does strike at one of the biggest unspoken problems in modern marriage. After a certain period, we expect the person we are with to be able to anticipate our moods. This expectation is not born of any rational or objective understanding of the way we communicate but of simple exhaustion. We become tired of explaining ourselves. The only solution is to develop the capacity to say more without exerting more effort, and telemetry can help with that.