Today we interact more and more with computers throughout the day and sometimes don’t even realize it. Most obviously, we use smart phones and tablets. Yet, computers also “hide” in washing machines, dryers, kitchen utensils and more and more also in wearable accessories (e.g. watches) and finally also clothes. With these new technologies come new possibilities, we need to decide how we want to use them.
Wearable devices in form of the smart phone have already become an integrated part of our life and changed it substantially. Just think back on your last vacation or trip. Could you imagine it without your smart phone? Printing out maps, planning transportation, hotels, restaurants ahead of time. No “find my friends” or messaging applications telling you were your company is when they are running late. However, this is just the beginning.
When I’m talking about wearables, I don’t just mean smart watches or bands, but a more personal form of computing. Computing you can wear like clothes accompanying you like a second skin wherever you go and most important supporting you seamlessly in every day tasks.
A word of caution, I’m speculating in these series of articles. Researchers often don’t have a good sense on where technology might go. To give you an example (also for early wearable computing systems), check out Figure 1. That’s me in 2005 with what we thought would be the future of wearables. It turned out that the future would be way less obtrusive and way more powerful. I’m talking about the smartphone.
The more personal computing becomes; the more insights it can get from the users. For me the research directions of wearable, pervasive and ubiquitous computing share the same vision with slightly different flavors. The more computing we will have in our environments the less we have time interacting with them, therefore the computing devices need to become pro-active. Interfaces should vanish. The computing understands what I want and helps me to achieve it. To realize this idea researchers work with a wide variety of sensors detecting everyday activities from interactive stationary systems like the Kinect to wearable devices like the Myo (detecting muscle movement). Sometimes neither the user nor manufacturers are aware of the all the information contained in sensor data collected by these smart devices.
If you are wearing a fitness tracker throughout day/night, companies like FiBit or Jawbone know a lot about your lifestyle (when you get up, go to sleep) and even more private information about sleeping activities.
So far, private companies “own” the users data (step count, heart rate etc.).
Industry stances are quite broad on that matter: From Fitbit for example who lets you use their devices only if you upload your data to their online service to Apple on the other side claims “We don’t want your data”, store all of them in a vault on your phone (called Health Kit) and let you select whom you want to share your data with. Yet, still users need to trust these companies with potential very intimate data. Also, users are often not aware what information they are sharing.
Of course, the closer computing becomes the more difficult it is to design it well. We seen this now with a couple of devices, most prominently maybe with the mixed reception of Google Glass. Although I dismissed Glass due to battery runtime and the lack of everyday useful applications, my opinion changed a bit about head-worn devices when I gave Glass to my grandparents for a week. They could come up with a couple of interesting application scenarios. Moving away from the social acceptance issue, I believe society needs to have an open, informed discussion about important 2 related topics as soon as possible:
Privacy/Ethics and Democratization of Data.
First, who owns the data you or other people are recording? Second, what type of data can be processed or shared with companies/your employer? The Germany German constitutional court, for example, ruled the right to informational self-determination, meaning the citizens should have the right to determine the disclosure and use of their personal data. Yet, it’s till today it’s mostly not practiced and might be difficult to attain.
The other question, how can we use this data for the good of society (not optimizing for particular interest groups or companies).
The discussion around big data reminds me on old discussions about source code (e.g. producing software). In the beginning, more code was good leading even to developers being paid by the lines of code they produce. Yet, more code is often bad. It’s difficult to figure out what happens in the piece of software and makes it hard to find bugs. A lot of companies seem to believe more data is good. However, especially with wearable devices it touches a lot of privacy and ethic issues that consumers are not aware off (even though they agreed to the terms of the company by clicking “yes” in a “Terms and Conditions” Agreement). Big Data in itself can be more a liability than an asset. Actionable insights are an asset. Yet how to get there by just collecting a lot of physiological data (and by doing so violating the privacy and ethic sensibilities of your users) is not clear.
In this series of 3 articles I will explore the impact of wearables on society more. The next article will focus on eye wear. In my opinion, a very promising technological development. In the last article, we will discuss how to get from just collecting data to actual change, from quantified self to practice design.
Kai Kunze works as Associate Professor at Keio Media Design. He held a position as research assistant professor at Osaka Prefecture University 2012-14.
He was a visiting researcher at the MIT Media Lab, 2011.He earned his Ph.D., summa cum laude, in the Wearable Computing field from the University of Passau in Germany, 2011.
His work experience includes research visits and internships at the Palo Alto Research Center (PARC, Palo Alto, US), Sunlabs Europe (Grenoble, France), and the German Stock Exchange (Frankfurt, Germany).