The 'Quantified Self' is a thrilling prospect for some: Massive datasets about oneself can be a new route to self-discovery. But for most of us, the idea of continuous self-tracking is a novelty that results in shallow insights. Just ask anyone who has bought a Fitbit or Jawbone Up which now lies dusty at the bottom of a junk drawer.

For the Quantified Self movement to become truly useful, our gadgets will have to move beyond the novelty of gratuitous behavioral data, which we might call a 'first degree of meaning.' They’ll have to address a second degree of meaning, where self-tracking helps motivate people toward self-improvement, and a third degree of meaning, where people can use data to make better choices in the moments when a decision is actually being made. We’re moving closer to those goals, but we’re still not thinking rigorously about the challenges involved. So let's start.

#### Matthew Jordan ##### About JMatthew Jordan, Artefact's research director, has worked with companies like Baxter Healthcare, St. Jude Medical, and Mayo Clinic to apply the design process to the health industry. Two recent Artefact projects he led are [Juice Box energy system](https://www.wired.com/2013/11/four-world-changing-products-dreamed-up-by-todays-best-product-designers/) and [Dialog](https://www.wired.com/2014/03/3-insights-wearable-design-smart-concept-epileptics/), a concept for people with epilepsy. He can be reached at health@artefactgroup.com.

It so happens that the rise of the quantified self coincides with the rise of Big Data, which has become a buzzword rapidly adopted in targeted marketing campaigns and recommendation engines that push products. But in between Big Data and Small Data, between the Quantified Self and the crowd lies a third way: what we at Artefact like to call the Quantified Us.

Imagine a future where self-tracking harnesses a whole population’s data to identify patterns and make meaningful recommendations. Imagine a future where we can see into the data of people just like us, to help us live better, and where we willingly give up a bit of privacy in exchange for vast benefits.

The Quantified Us —————–

The Quantified Us should be based on a select group of people who share similar goals, health conditions, or even similarity of emerging data patterns. They could be your friends, but they're more likely strangers who happen to have a lot in common with you. We are already starting to see the beginnings of a Quantified Us movement starting to emerge, though we feel its full potential is untapped:

-PatientsLikeMe allows people to share personal health records so they can compare ‘treatments, symptoms, and experiences.’ The site also supports personal connections with the community, as well as the ability to track your own health data and to make your records available to medical researchers. These data, however, are positioned as a tool for the medical community to review and gain clinical insights.

-Crohnology is a social network centered on people who suffer from Crohn’s disease and colitis. The community revolves around the sharing and aggregation of information. But the scope and depth of data that the patient can access is limited, and, as a result, so are the insights.

-StockTwits uses a followers model, connecting investors who are interested in the same financial opportunities. Though the insights can be very timely and represent the sentiment of an informed group, the ‘group’ is just defined by who decides to follow who. There is no collaboration, because because no one is sharing their personal data.

Dialog, another concept from Artefact. This one is for people with epilepsy: It would warn of oncoming seizures and track environmental triggers, while also serving patient data to doctors. Image: Artefact

The Application —————

While these early, partial examples of the Quantified Us are headed in the right direction, they still make users manually share their data and pan for insights. The Quantified Us should instead tackle the challenge of helping these groups form, facilitating data collection, extracting insights tailored to individual action. To get to this future, we must be clear about what the Quantified Us is and how it achieves success. A successful Quantified Us strategy is:

\–Selective, But Configurable: People must be able to control the boundaries of how their data is shared, and the sample sets to which they’re compared. For example, if a woman experiences migraines brought on by caffeine, she—not anyone else—should be able to exclude people with unrelated triggers. For that to work, designers have to create user experiences that make clear the boundaries between groups and the individual user.

\–Driven by Democracy: The Quantified Us hinges upon people making a choice to trade their personal data for access to broader swathes of information. That’s a grass-roots type movement, and design’s role should be to foster a sense of community and transparency.

\–Focused on Individual Understanding and Decisions: The Quantified Us means nothing unless individuals can extract insights, make better decisions, and change their behaviors. Therefore, a well-designed platform should make decision making the core of its user experience.

What patients would see and could share with doctors with the Dialog concept. Image: Artefact

The Promise ———–

Imagine a person with epilepsy trying to understand an uptick in seizures. What if he could compare his triggers to those of people just like him? Such a user experience could address everything from Crohn’s disease to migraines. These need not be separate products: Indeed, they could be similar user experiences, tailored to individual use cases.

Now imagine a person with insulin-dependent diabetes whose blood sugars are running high at night, but who isn’t able or doesn’t feel motivated to understand why. What if she could see the profiles and data of other people like her, and see where she falls relative to the “norm”? What if she was able to start a dialog with other people like her, or to get emotional support when she needs it?

It’s easy to imagine a variety of scenarios in which self-tracking combined with collective data sharing can result in deeper understanding and heightened motivation. Ultimately the Quantified Us can help people take better care of themselves, more often—and feel more connected to each other in the process.