Mobile media revealing our selves to ourselves

Mobile phones have many, many purposes: entertainment, art, communication, education. One of the more controversial applications of this technology is using it for monitoring. When certain people have the ability to covertly monitor others while not being monitored themselves, there is a power imbalance. It is possible for those doing the monitoring to judge and punish those who they catch doing something bad when, in fact, this is something that they do themselves but no one is able to observe them doing it. I'm not sure this actually happens all that often or will be as likely to happen in the future as most people believe, but for the time being, let's assume this concern about mobile media as monitoring device is a valid one.

But what about self-monitoring? The possibility of using mobile technology for self-monitoring and self-feedback has not yet been fully realized, and I think it may help people overcome two significant obstacles to behavior change.

The first obstacle is being aware of the patterns in your own behavior: the environmental cues that cause you to unconsciously respond in a way that isn't in your long-term interests, the moods and thoughts that precede worse moods and thoughts. It will be tricky to use mobile tech to reveal these patterns without being too obtrusive. I've tried out some experience sampling technology on my phone and its hard to even get it to work right, and when it does work right, it may just be too much of a nuisance to put up with. It feels like one more thing you have to do, like a diet, and almost all diets fail. But its conceivable that you could design a less intrusive way of tracking thoughts, feelings, and behavior throughout the day.

The second is one I've been thinking about a lot: people do not like to be told what is good for them by others. They may be a bit more accepting of such advice if its coming from a trusted expert (say, a medical doctor), but even then, it doesn't feel good to be told what to do. People will start to look for reasons to doubt the expertise of the advice giver. If we give people the tools to make connections for themselves and to use that new knowledge to alter their choice environment, there is no external force telling them what to do. If anything, they are telling their selves, their future selves, what to do.

We all do this already. We resolve to do things in the future that are in our best long-term interests but then fail to do so in the face of temptation or distraction. Mobile media, because it is with us at all times in all contexts, can be a tool with which we cope with temptation and distraction. Ideally, it will not proscribe particular ways of being, but will merely be a tool for individuals to closely observe and then structure their lives.

Modern existence necessitates being part of an increasingly complex (i.e., hard to understand) set of interactions with an increasing number of people. It is difficult to know why you feel the way you feel, or do the things you do. Designing an unobtrusive, secure self-monitoring application and using it in tandem with some choice-limiting technology is a way to exist in such a society. Potentially, mobile tech is a layer of technology between all those aforementioned applications - entertainment, art, communication, education - and the self who is equipped with the older "technologies" of the brain, eyes, ears, and nose.

The Two Webs

There are two dialogs on human behavior (which includes political, economic, and social behavior) taking place on the web. In effect, there are two webs.

One web consists of data on human behavior and commentary about this data. This one connects some folks in academia to folks in policy circles and the private sector around the world. This is Big Data.

The advantages of this mode of inquiry is that it harnesses the power of new media technologies to provide more information to help improve our predictive power when trying to understand something as enormously complex as individual and collective human behavior. Many of the critiques of quantitative study of human behavior were grounded in the fact that studies simply didn't have enough information to predict and explain the variance in behavior. Whereas other sciences (physics, chemistry) had enough information about a system to predict outcomes within that system, social sciences did not. But if we were to assume, for a moment, that a team of researchers had access to every single bit of information about every human thought, feeling, or behavior for thousands of years, then that team's ability to predict human behavior would be comparable, I think, to those in other sciences. With better predictions come better answers to questions: how best to minimize suffering, or the spread of disease, or human's impact on the environment, or whatever.

Of course, this mode of inquiry is not without its flaws (or at least perceived flaws). The collection and analysis of so much data on human behavior is viewed as being exploitative in some way: those collecting the information benefit and those who are the subjects do not. There are privacy issues: privacy is seen as a prerequisite to mental and emotional health as well as a means of maintaining some power over determining the course of your life (the actual value of privacy would be difficult to determine within this purely quantified conversation about human behavior). There is also the fear that someone with enough information about human behavior will be able to manipulate people to suit their ends (but if those collecting and analyzing data discuss findings freely and don't hoard secrets, this critique doesn't make much sense to me). It can easily be abused by people thinking there's a causal relationship when then there is only a correlational one. Statistics, when misused, create the illusion of certainty. Statistics could always be misused, but the more powerful and widespread they become, the more likely misuse might be and the damage that could be done.

You might call this the rational web. It views behaviors and events as probablistic (or it should, anyway) and it takes into account the degree to which outcomes are affected. If, say, it was determined that people's political party identification determined the amount they were paid when controlling for occupation, abilities, etc., you could find an answer to the question of how much difference it made in terms of pay (maybe Republicans make $4000 more on average when controlling for other relevant variables). In fact, there is an expectation that you answer the "how much" question.

The other web consists of rhetoric: emotional appeals to pre-existing, deeply held beliefs about human behavior. The most commonly used technique here is to select a few emotionally charged stories and try to get the audience to empathize with them. As access to the web has increased, it has become easier to find a subject (that is, the individual at the center of the story) whose situation exemplifies the pre-existing beliefs about human behavior held by the author of the story and the intended audience. Its easier to find the emotionally charged stories, the one or 3 or 100 personal stories that, when you look at parts of them the right way, support your pre-existing belief that, say, capitalism or socialism is harmful or that a certain policy does more harm than good. This technique connects some other folks in academia with the public at large, particularly disenfranchise members of the public worldwide.

Here, I think one possible danger of the wide-spread use of this technique might be that the echo chamber effect (where certain factions become less able to take the perspective of others and become more hostile towards others) gets stronger. Confirmation bias runs amok, and fewer people take into account new information in order to make better decisions. Any holder of an opinion, no matter how wacky, can find others supporting their opinion. This social support, this sense that one is not alone in one's beliefs, is essential to the persistence or propagation of an idea or ideology. Even if one is in the minority, all one has to do is draw an analogy to a group that was in the minority that eventually became the majority (the rebelling colonists in early America or civil rights crusaders in the later 1950's) in order to justify one's beliefs.

You might call this the emotional web. Rather than being probablistic, it is principled. It rarely asks the question "how racist is a statement?" or "how much privacy is being sacrificed?" or "how much freedom is the right amount of freedom"? In this way, it seems irreconcilable with the rational web.

You can't easily categorize certain websites as one or the other. Two of my favorite news sites - the New York Times and Slate - have some stories that appeal to statistics and analyses of statistics and other stories (usually editorials) that appeal to emotion by cherry-picking individual stories. In fact, a journalistic standard seems to be to combine the two: start with an individual's story and then zoom out to the larger trend. Hook the audience with emotion and convince their inner skeptic with data.

Still, I can see, at the very least, certain blogs that are more emotional or more rational, and it would be interesting to see if certain people gravitated toward either emotional/rhetoric arguments or rational/data-driven ones. Last month, I saw a great paper at the International Communication Association's annual conference by Brian Weeks titled "Partisan enclaves or diverse repertoires? A network approach to the political media environment" that suggested that the self-selection ideological bias (dems watch only MSNBC, repubs watch only Fox News) is a misconception and that personal media repertoires are more diverse, at least ideologically, than many believe. They may be diverse (or rather, balanced) in terms of their emotional or rational content as well. But maybe they are not, in which case we really are two different groups of people having two fundamentally different conversations about human behavior. Definitely an avenue worth exploring.

Data Mining as Psychotherapy: How the petabyte age could help us to know our selves and why that's nothing to be scared of

Let's start with a problem. Make it a personal problem. I mean "personal" in two senses: "personal" as in something that you wouldn't want to talk about with anyone besides a very close friend or a therapist, and "personal" as in specific to you and only you. Say you're depressed, or that you're engaging in what you know to be a self-destructive pattern of behavior. How can you solve this problem, or avoid repeating it in the future?

Now, let's pretend you had a magical machine that could track every bit of thought and experience you had from your birth to this moment. The data produced by the machine tells you everything that led up to that negative outcome moment. Well, not everything. Only the things that you were a part of. If a butterfly flapped its wings in China the day after you were born, the machine would not record that. It is possible that things that you were not directly a part of could have a profound effect on you, leading you to become depressed or engage in shitty behavior (see sensitive dependence on initial conditions). Nevertheless, if you have to limit your recording of information somehow due to technical limits, of which there will always be some, and your goal was to find out the cause of a problem that relates to you specifically, then it would be good to start with all experience and thought related directly to you.

Now that you've got all that information, you could look for patterns in that data, or maybe the machine could look for them for you. You notice a recurring pattern of actions or thoughts that you keep choosing that lead up to that negative outcome you want to avoid. We have an intuitive grasp of the kinds of behavior or thought that lead up to such outcomes (e.g. I'm depressed because I looked at a picture of a dead relative, which reminded me of how much i missed them and of my own mortality. Maybe I shouldn't look that picture so often). But sometimes, we can't see those patterns, either b/c we don't want to acknowledge that somethings that produce pleasure in the short-term might bring us displeasure in the long term, or b/c we just can't remember everything that we thought, felt, or did over the course of our entire lives.

The first problem is an objectivity/subjectivity problem, solved by asking a trusted friend or a therapist for advice. The second problem is a surveillance problem - no other person is there for our every waking moment, and even if they are, they can't see inside our heads (the closest you could come to that would be a parent or a lover). This creates a trade-off: you're the only person with access to your entire history and your thoughts and feelings, but you're not especially objective about them. The third problem is a cognitive load problem: no one person can hold that much information about one person's life in his/her head.

Enter the machine. The machine is capable of holding a much larger amount of information. The machine also makes the data available to you or to trained professionals (though, once you were able to see the patterns that linked the short-term pleasurable actions with long-term displeasurable consequences, you wouldn't need anyone else to tell you to cut it out). The machine could be with you every waking minute. Heck, it could even record what's going on in your head while you're asleep.

I'm not saying that the machine would allow you to see with complete certainty what led to that negative outcome, but it would be on a par with what we think to be causes and effects in the hard sciences. In other words, they would be able to reduce the probability of there being some other explanation for your misery to virtually nil. So, you take the data, you make note of the patterns of thought and behavior that led up to the negative outcomes, and you choose not to think or do the things that led up to those outcomes. Even better, you look at the patterns that lead up to your happiest moments, and you repeat those.

The machine does not exist. yet. But I think we've got a prototype: google. Google tracks our searches, which might tell us a little more about our patterns of behavior than we might know ourselves. A prototype also exists in the form of spyware that tracks our every click on the internet. As more and more of our desires and thoughts and feelings and actions are conveying on computers, the closer we come to having something like "the machine." (if you included mobile tech and its ability to track us throughout the day, you'd have an even better approximation of the machine).

Is the machine to be feared? I'd guess that most people would say yes, but I wouldn't agree. To me, that's like saying that you're afraid of knowing yourself, or afraid of knowledge in general. What we're afraid of is the misuse or misinterpretation of information. But should that keep us from garnering what we know to be more accurate information about our selves? There is such a thing as responsible data interpretation. In order to engage in responsible interpretation, it is essential to start with this assumption: the information we're dealing with is imperfect and incomplete, and yet it may offer us insight into our thoughts and actions that is superior to (or supplements) what we're currently working with. We need to engage in systematic testing of the circumstances in which this information does provide us with insight, and we need to identify misuse and misinterpretation and discourage it.

The other choice is one that I think too many people choose, mostly out of fear and laziness (its easier to dismiss the entire enterprise of data mining than learn how to do it responsibly and teach people how to interpret data properly and how to tell if someone else is interpreting data properly). I think that, on some fundamental level, we fear data, not the corporations or the governments or the scientists who are gathering it and using it, but the data itself. Given the rate at which behavioral data is piling up, this stance is becoming increasingly irresponsible each day. We can either let someone else aggregate all this data and learn why we do things and how to manipulate us, or we can take control of our own destinies and learn how our minds work so as to beat the others to the punch, to alter our behaviors so as to become less predictable. There's no going back to the pre-data age.

And really, the machine is just an extension of established sciences that spring from our desire to know ourselves more fully. Psychology, sociology, and really all of the social sciences are imperfect versions of the machine. They look for patterns leading up to outcomes we judge to be good or bad, but they have huge blind spots. But the blind spots are shrinking. Sociology and psychology have always played the red-headed stepchild to "hard sciences" like physics and chemistry. A great deal of this ill-will comes from the fact that social science can not deliver the levels of certainty that are the norm in hard sciences (hence the tolerance of smaller effect sizes in social science). That, too, may change in the petabyte age.