This kid rocks my world.
Archive for February, 2015
(This is the first article I’ve had published, originally printed in the IQT Quarterly, December 2013 edition. It finally struck me that I should put my writings on my blog, so here’s the one, with more later.)
The Human Bits: The people under all that data
You’re an 8 today! The meaning and the uselessness of life-tracking
“The unexamined life is not worth living.” – Socrates
Buster Benson found that the course of his in-person interactions would change based on the information people saw about him online. A casual interjection a coworker would greet him with at the office would look something like this: “You’re an 8 today. You must be feeling pretty good! Let’s talk.” Acquaintances would avoid writing him during periods of heavy email inflow.
Since 1999, Buster has tracked not only the number of emails he received per day but also his scored his levels of morale, health, sleep, alcohol, and caffeine on a scale from 1-10. These numbers were publicly available on his blog. [busterbenson.com] Today, his blog shows his email traffic, how much time he spent walking and eating, how often he was angry or sad, and pictures of him shared around the web. The page greets visitors with the option to “Search all 32,402 entries.”
Buster is a successful Seattle entrepreneur, notably the creator of HealthMonth, a profitable online game in which players try to improve their lives (eat better, get out of debt) by changing one small thing per day for a month. He identifies himself as a husband, a father, and someone who, after 14 years of collecting personal data, is still struggling to find meaning in all of it.
What’s that you say? (And so do I.) This master of self-tracking has spent over a decade analyzing his life and he still doesn’t understand it? We-ell, yes and no. Let’s first try to see it from his point of view. As a pioneer in digital self-tracking, Buster has made some important discoveries about tracking and meaning that can make our own self-tracking a lot easier.
In his recent Quantified Self (more on this below) talk – “Why I Track” – Buster explained how he expected to find correlations in his data that would guide him in dividing and organizing his life. He especially expected to see a positive correlation between having great days and high scores in the short list of meaningful variables he’d curated, which included spending time with family, running, and sleeping 8 hours. To set up the data, Buster tracked individual variables like sleep and mood, then scored each day on a scale from 1-3. (The scale tells him whether he thought he had an above or below average day.)
Intuition told him that spending more time with his wife would have a positive correlation with above average days. Or exercising more. Or watching a movie. In fact, none of it did. There was no correlation.
Quick primer on correlation: a p value of 1 connotes significant, positive correlation, a p value of 0 means no correlation. A p value of greater than 0.5 implies positive correlation.
Buster hoped for a p value of greater than 0.5. His actual correlation? Negative 0.13. Ouch.
What does this mean for the rest of us mere mortals with a bad habit (or 10) to shake? While Buster’s results were surprising, his desire to track has not lessened. He has actually created a challenge for others to find positive correlations in their data and share it. [bit.ly/self-trackingchallenge] Ultimately, the data do not predict outcomes or guide us into living the perfect lifestyle. But they do offer us a window of introspection through which we can pull out the bits that are meaningful to us. Through tracking every lifestyle variable he could think of, Buster realized that many, if not most, of them were useless, but he also discovered the few that were really important to him. He found that data are important to track, and can be unpredictably useful at different times, but don’t give an accurate view of happiness or meaning over time. We have to develop our own methods for that part.
It is key to understand the human nature that lies beneath the creation of big, personal data as we move towards a more quantified world. Human factors are at the root of why simply prescribing medications doesn’t work — people forget to take them, or whether they’ve taken them. And why those at risk for heart disease won’t walk more or stop smoking. Device makers and health providers are grappling with these issues. And when policy-making and fear-mongering fail to improve our lives, it makes sense to go to center of the issues – to the people themselves. One group leading the pack is the Quantified Self.
The Quantified Self: self knowledge through numbers
When people ask, “what is the Quantifed Self,” its cofounder, Gary Wolf, likes to ask, “What do you think it is?” This line of questioning usually reveals the original asker’s motivations and, sometimes, a story about their own self-tracking. Not pre-defining the Quantified Self for people is an important concept, as (not to sound cheeky) the Quantified Self is whatever you want it to be. It’s quantified – it’s about you. It’s the Quantified (key word:) Self. To understand how that notion came about, let’s go back to the beginning.
The Quantified Self was born in 2008 when Wired editors, Kevin Kelly and Gary Wolf, independently noticed the adoption of new technologies for self-discovery. Gary himself had recently used the software SuperMemo, which utilizes an uncommonly practiced technique called “spaced repetition” to learn Spanish in an absurdly short amount of time. Kevin is famed for chronicling the technology age from its inception, including in his 2011 book, What Technology Wants, called “a sharp-eyed study of our abiding need for cars, computers and gadgets” by The New York Times.
The self-tracker is nothing new: farmers noting field conditions and resulting crops or the housewife who monitors her weight against food intake are examples of experiments many of us run in order to lose, gain, or optimize. The trend Kevin and Gary recognized was this experimental behavior taking place in the digital world. They believed that new crops of devices woud become a central to self-tracking. Initially, Kevin and Gary thought the real editorial gems were devices, and planned to blog about the self-tracking tools.
Feeling that they might be missing something, they decided to host a discovery meeting at Kevin’s house in Pacifica, where they invited self-trackers to talk. There was no agenda – it was a “let’s see what happens” affair. And when one guest trickled in late, he was teasingly told to go first, with no other instructions. Unphased, the man pulled out his laptop and opened a spreadsheet that detailed how he had spent every 15 minute chunk in the past year. The story goes that, immediately, the cofounders knew that this – the human side of tracking – was where the real story was.
Since that night, Quantified Self has been a venue for self-trackers to tell their stories, turning the stars into the people and not the tools. Guiding questions for self-trackers are What did you do? How did you do it? and What did you learn?
Quantified Self meetings, literally known as Show&Tells, happen in over 60 cities around the globe and attract about 12,000 people in sum. Enthusiasts include people from every spectrum of society: entrepreneurs, patients, Olympic athletes, health nuts, venture capitalists, and people who simply say they “want to be more awesome.”
We know that data collection and analysis is no longer an occupation solely of academics, corporate types, governments, and the like, but is fair game for anyone who has access to data. Personal computers, smartphones, and now a bevy of bluetooth enabled devices are changing the players in the big data game, allowing individuals to collect hundreds of data points per second and glimpse their results in real-time.
Data are being collecting in a wide range of devices, from fitness tools like Body Media’s BodyFit, to financial monitors like Intuit’s mint.com. Companies large and small (Omron and Fitbit, for example) have jumped in, creating devices targeted to the individual.
A snapshot of devices
Brain: Emotiv – an EEG headset initially designed for gamers
Stress: emWave – a heart rate variability monitor that trains your breathing
Sleep: Zeo – an EEG headband worn at night that monitors sleep and wake times and sleep stage
Steps: Fitbit One and Zip, Misfit Wearables Shine, Zamzee (for children)
Athletics: Zephyr BioHarness, BodyMedia, Basis health watch
Users of self-tracking devices are as diverse as the devices themselves. What they have in common is that they adopt technology with the aim of gaining personal insights. Typically, the self-tracker cares about just one thing – himself.
Unfortunately, making sense of nascent tools – let alone the influx of piles of data – is not simple. For the person who wants to see through the data, experiments are necessary, and few among us are properly trained in experimental design. Lack of analytical skills can get in the way of finding meaning, making what began as a hopeful endeavor turn into a difficult, and often lonely, experience.
The Quantified Self has been a popular draw because it has the dual use of being a marketplace for human frustration and learning. Asking any Quantified Self attendee why he or she comes to Show&Tells draws the answer “I come for the people.” The presentations, side conversations, and unavoidable human connections often inspire, motivate, give us that “aha!” moment, or plant seeds that we take back to our everyday lives.
I like to say that we’re all a little weird, but we don’t mind it so much when we know we’re not the only ones. We’re programmed to seek families, tribes, communities. This aspect of human nature underlies the success of group weight loss programs like Weight Watchers and Jenny Craig beyond traditional diets, Alcoholics Anonymous, and so forth.
Big Data: What’s in it for me?
While one person examines their life in order to be happier, larger entities (Aetna, the FBI, Google) need to standardize and generalize massive amounts of data across populations in order to make it useful for them. The problem is in motivating the individual to share personal data on behalf of the benefit of a population.
For those who would benefit from big data, it is essential to dive deep before developing a working incentive system for potential data donors. To understand a real person’s motivation to track, and especially to share, we must ask the self-tracker a few simple, but fundamental, questions:
- Why do you track?
- What, if anything, did you learn?
- What now?
Tracking provides a way to understand behaviors and cause and effect over time. Something the human mind is quite poor at doing. Yet, different people have different reasons to pick up a device.
To generalize, self-trackers typically come from one of three camps:
- The perennially curious
- Those with a disease to monitor or improve
- Those who want to be bigger, faster, stronger
The motivations behind each group are different but, largely, self-explanatory.
The Curious are always on the lookout for the next fun – not necessarily important – thing. They’re prone to trying new tools and leaving them on the shelf for the next, new gadget.
Those struggling with a disease are sometimes self-motivated as well as compelled by friends, family, and physicians. There is an obvious pain point that might be remedied simply by becoming more aware of risky behaviors with tracking.
The “more awesome” camp have long been self-tracking, having used gadgets such as heart rate monitors, GPS speed trackers (e.g., Garmin watches), or various nutrition regimens to lose/gain water or muscle. This group insists on quality and accuracy.
As we enter the era of the Quantified Self, it is important to keep good old-fashioned humanity in mind. However, as businesses seek to play in the market, and regulators continue to regulate, the lines between self and device can be blurred.
When humans and devices collide
Philosophical question: If a company implants a pacemaker in your chest, does the pacemaker belong to you?
In Child Development studies, a classic test of understanding (the false-belief task) involves putting a child in a room, who then watches as one man comes into the room and places an object (such as a pair of scissors) in a hiding place. A second man enters the room and puts the scissors in his pocket. When the first person returns, the child is asked by a researcher, “Where will the first person look for the scissors?”
A child’s answer varies depending on age. In early years, nearly all children answer that the first man will look for the scissors in the second man’s pocket. By ages 4-7, children typically understand that the second man doesn’t know the scissors have moved. This fundamental understanding allows us to make rational decisions.
In the pacemaker question, ownership over the device and its data cannot be answered using human reasoning. If the pacemaker is in my body, does that make it mine? Or, does it belong to whomever made it? Did I make the dataset on my heart’s activity?
Hugo Campos is a San Francisco based designer whose self-tracking is at the heart of this debate. Hugo is known in the Quantified Self community as an aesthetic, noted for his beautiful photo food diary, for which he is more cautious about the visual appeal of the food than its nutritional content.
Hugo also has a cardiac defibrillator implanted in his body. Without it shocking his heart a few times a week, Hugo could go into cardiac arrest.
It is clearly in the man’s best interest to have a pacemaker, but Hugo is the kind of guy who doesn’t stop at good enough. He wanted to design his life, including diet, to minimize his cardiac events. So, he exercised more. He changed his diet. He even went vegan for a month. [http://quantifiedself.com/2012/04/hugo-campos-on-going-vegan-in-december/] And all he needed to do in order to see whether his life changes had effected his heart was to see the data from his defibrillator. The only problem was that he wasn’t allowed to see it. [http://online.wsj.com/article/SB10001424052970203937004578078820874744076.html]
Moving forward, ponder this unsolved mystery of the digital age: if you produce data with the aid of technology, who owns it?
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