I’m back at the Media Lab today and got to attend a talk by cultural anthropologist Natasha Dow Schüll, of MIT’s Science, Technology, and Society program, who’s speaking at Pattie Maes’s Tools for Well-Being series.
Digital technologies can have negative impacts on our well-being. Natasha grew interested in the topic over the course of writing Addiction by Design, on the game elements throughout machine gambling in Las Vegas. Speed, repetition, continuity, and designer chairs lure players into a zen flow and open wallet. The casino industry seeks to produce this bubble state, and closely tracks players’ behavior to further refine its profit engines. Loyalty cards are a key mechanism for these studies, recording the games we prefer, the denominations we default to. As “Dividuals“, we are treated as a collection of habits and preferences that can be marketed upon, often in real-time.
These concerns have come to the forefront of public debate around public and private data, but Natasha has shifted her vantage point to the perspective of self-tracking. The key difference here is that individuals are choosing to be tracked, and choose to intervene. Designers have put forth a wide range of gadgets and software to measure steps and caloric intake, productivity, mood fluctuations, and shifts in relationships (Natasha references a marital fight tracker tool).
Natasha has moved from addiction by design to self by design. The Quantified Self Meetup community has provided her a rich starting point. Members self-evaluate semantic content of their emails, caloric intake. Technology promises a route to the good life.
Alumni of Wired magazine founded the quantified self movement to apply commercial grade analytics and feedback loops to individual habits. The promotional discourse tends towards the utopian, empowering users. Journalists, meanwhile, portray the movement as extremist and simultaneously self- and tech-centric. There is pushback that quantifying life comes at the cost of our humanity, and that there is no ideal algorithm for goodness.
Natasha feels these critiques have merit, but may miss the fact that these self-tracking habits are becoming more and more germane to the mainstream experience. She believes ethnographic study of today’s quantified selfers provides insight into the direction we’re all drifting ever closer towards. We’re all implicated in this trend, even if it’s just by virtue of owning a smartphone.
A recent conference workshop asked, “What kind of self is the quantified self?”
- Is the data a mirror? Data rarely captures the whole image.
- Is data a self portrait? If so, it’s pixelated.
- Others suggested metaphors of microscopes, and first- or third-party autobiographical narratives.
The Commerce of Well-Being
The floorspace dedicated to self-tracking technologies at CES has more than doubled. Natasha is meta; she’s tracking self-tracking’s emergence from the true geeks to Best Buy, smartphone app stores, and healthcare systems.The Consumers Electronic Show included wearables, well-being, and fitness devices. The Affordable Care Act’s emphasis on preventative care has been leveraged by marketers pushing quantifying devices. Lifestyle has important implications for individual health, and entrepreneurs are wisely pushing the link between lifestyle changes and health outcomes.
Pew has asked Americans the degree to which they track health indicators. 60% of us track weight, diet, or exercise routines, and 33% track blood pressure, sleep patterns, and headaches. Self-monitoring has been proven to improve chrnoic conditions like high blood pressure, weight, and diabetes. It’s important to note that this self-tracking does not necessarily need to involve gadgets.
At CES, the digital health zone and the fitness zones were adjacent to one another. All manner of gadgets and devices and wristbands and sensors promised to log it all and even intervene, triggering soothing iTunes tracks when you’re stressed out.
The pitch is that these data dashboards could take the guesswork out of optimal daily living. The essential ingredients are to monitor, analyze, and change behavior. Our devices are getting better and better at monitoring, with new capabilities emerging all the time, but we’ve made far less progress analyzing data and actually changing behavior. Critiques of the quantified self movement tend to focus on the fact that very few of us act on the data.
In one session Natasha attended, “Trackaholism: a disorder worth having”, a doctor pointed out that millions of us check smartphones hundreds of times per day. He hopes that we can become as addicted to our health and wellness indicators as we are to the push notifications from social apps.
A much touted statistic at the event predicts that by 2015, more than 500 million people will use mobile health applications.
Precursors to Contemporary Self-Tracking
Natasha reconnects us to the larger human story, linking self-tracking to the Stoic practice of ethics, and the care of the self. This way of life asked that we pay attention, take inventory at the end of the day, and even share the results with another citizen.
Sanctorious (1561-1663) weighed himself, his urine, and his feces in a weighing chair every day for 30 years. If he eats too much, the chair drops him to the floor, where he can no longer reach the food. He was ahead of his time in building an analog device that, unlike many of today’s, produces a data-driven intervention to change behavior.
Benjamin Franklin’s “13 Virtues” is another famous example of attempting to achieve the ideal moral life, this time through a daily grading rubric. He was very focused on the quality of the paper and pencils and other affordances of his recording devices. He found that he was full of faults, but that the practice of self-grading improved them significantly.
Diary writing is another age-old self-reflection tool.
We’ve been offered relatively affordable hardware and software that ship with embedded sensors to visualize and provide feedback on massive volumes of data. It’s linked, too, so even when n = 1, we can draw big data findings from aggregate results. Today’s quantified selves are real-time, and passive.
The “Algorithmic Living” group at Intel’s Science and Technology Center for Social Computing tracks tracking methods, voluntary or otherwise.
The Algorithmic Self
The bits are recorded, filtered through an pre-configured algorithm modeling ideal modes of behavior, patterns are identified and displayed (think graphs), and finally, recalibrated: what kind of nudge, prompt, or incentive adjusts behavior?
Smoking cessation apps alone offer a bevy of mechanisms: they can socially shame you, they can highlight the additional minutes you’ve added to your life, or they can tell you how much closer that cigarette just brought you to death.
Cass Sunstein’s Nudge lays out the importance of paying attention to how we design choice infrastructure. Liberal paternalism allows free will but nudges us towards ideal behaviors.
The Algorithmic Self: Outsourcing Meaning-Making
Self-trackers outsource some portion of their self’s meaning-making to technology, trusting the technology to detect patterns the human would not see. The human is just one part of the loop, and no longer self-sufficient. No person could ever make sense of all of the data the way the software can. These are experiments in algorithmic living.
Natasha’s next book, Keeping Track, seeks to connect the dots between the specific technologies of self-tracking with broader cultural contexts. What modes of self-experimentation and self-care does digital self tracking engender? What do these technologies reveal about changing ideals?
A divide has emerged at the Quantified Self Meetups between quantified Self purists and the startup “vultures” who have come into the space to profit.
I ask if there’s any consensus around which mechanisms work at the behavior-change stage. Like any product, there is user segmentation of which users responds to which features. Some have broken the space into four behavioral groups: social butterflies care about shame, sharing of stats, cheering, while the truly quantified love graphs and don’t necessarily care about sharing. Some of us responds to nannies who nudge and check-in. Others honor the purpose of a Fitbit because we wear it, and don’t need to look at any stats to begin changing our behavior.
Another member of the audience asks about the spectrum between surveillance of self and self tracking. Platforms like PatientsLikeMe can discover aggregate findings from individuals’ data. This happens frequently in healthcare tech, where companies market to consumers, but also sell their insights to other companies.
There’s an emerging concept of being a data donor, like an organ donor, where you agree to include your data in the collective’s to help lead to new findings.
There are very few studies of long-term behavior change from these devices, partially because of their recency, but some medical device companies have found their devices help long-term.