Serenity

Project Description

Do you get stressed out easily? Does stress negatively affect your personal and professional life? Serenity aims to help remove this unnecessary and unhealthy stress. Serenity is a wearable device that identifies when users are stress and provides users real-time feedback when choices are made to reduce stress. The People’s Insurance Company (P.I.C.) promotes Serenity to all of their clients who seek regular medical attention to handle stress. P.I.C. hopes that Serenity will decrease their clients' annual medical costs.

Cutting out stress sounds like a good thing right? As it turns out, this might not always be the case. Avoiding certain stressful situations might benefit someone in the short-term, however it can lead to negative implications in the long-term. A user might opt to skip work one day to avoid a stressful presentation. Avoiding the presentation will lower their current stress levels, however it might cause them to get fired if it becomes a habit. Another user might decide to cancel a stressful lunch with their in-laws one day, but the next day decides to discontinue communication with everyone close to them.

The examples listed might seem unrealistic at first, however situations like those might become very possible with the way technology has been heading. Our team chose this topic after acknowledging that people accept guidance from technology more and more everyday. Technology is already beginning to guide our day-to-day decisions. We think scenarios, like those listed above, are very likely to occur in the next few years if proper precautions are not taken when designing for the Internet of things.

Design Recommendations

There are a number of serious risks to consider when designing Internet of Things connected products. Within the Serenity scenario, we exposed three such potential risks. These risks, as well as potential mitigating considerations, are described below.

First, by the Serenity device only measuring a single physiological aspect of your life, namely stress, the holistic perspective is lost. IoT software will be utilizing a digital representation of the real world; and, regardless of the number of sensors we deploy into a user’s environment, this digital representation will always loose some level of detail, even if just the context or emotional value of an interaction. This potential concern is further explored by Dourish and Bell’s Diving a Digital Future: Mess and Mythology in Ubiquitous Computing (Dourish and Bell, 2011). What values and meaning you ascribe to a situation through your choice of data elements to include in this digital representation will have potential serious implications for your user. Designers of IoT devices must stay aware of the whole context of use, rather than just a sensor or data point of interest.

Second, humans have a proven tendency to perform to the most visible metrics they are have access to. The phrase “You are what you measure” illustrates this psychological condition (Ariely, 2010) and is demonstrated clearly by the Serenity scenario. The user is now being measured exclusively on stress levels and so optimizes their life to this metric, ignoring all other traditional social and physical cues (relationships, physical health, career success). While this metric optimization behavior can be useful in IoT devices to prompt engagement and prolonged usage, designers should be conscious of what intentional or unintentional behaviors the IoT device’s feedback may promote.

Third, the Serenity system illustrates the potential hazards of deploying ubiquitous systems based on an architecture or set of data in contexts other than originally intended. It is easy to imagine the ‘stress measurement’ features of Serenity were originally developed for use in lab settings to help doctors quantify patient data. However, when adopted by another company (insurance) this same device architecture and sensor system was used to achieve completely different goals from the original deployment. This fundamental concern was raised and further discussed by Adam Greenfield in his book Everyware (Greenfield, 2006). As designers, it is important to consider the potential downstream consequences of design decisions even though you can never completely predict know how or by whom your design will be used. Following the use of a design or system after deployment may help ensure the users best interests are considered over time.

References

Dourish, Paul and Genevieve Bell, 2011. Divining a Digital Future: Mess and Mythology in Ubiquitous Computing, MIT Press, Cambridge, MA, USA.

Ariely, Dan. 2010. Column: You Are What You Measure. Harvard Business Review, June 2010 Issue. Accessed 2/13/2016 at https://hbr.org/2010/06/column-you-are-what-you-measure.

Greenfield, Adam. 2006. Everyware: The Dawning Age of Ubiquitous Computing. Peachpit Press, Berkeley, CA, USA.