My presentation at Leeds Beckett University on 4th of July 2016. Need more info contact me!
With this survey we want to get a more in depth view on Quantified Self, behaviour and trends. Click here to fill in the survey!
We want to see if you as a respondent tracked yourself in the past 12 months with devices such as Fitbit, Jawbone Up, Withings Pulse or Aura, Body Media and so forth. Maybe you use mobile apps such as Runkeeper, Moves, Human, Fitness Pal. Maybe you started in the past 12 months and you quit or maybe you are tracking yourself for years already. Looking forward to see your answers! This survey is part of PHD on designing for more engagement, wellbeing and happiness in Personal Informatics! We will donate €1 to the ‘International Alzheimer LIga’ and ‘Doctors withouth borders’ for each respondent. Thanks for your collaboration!
A philosophic debate on ‘Self tracking cultures and the emergence of hybrid humans’ part of Being Human Festival, University of Liverpool December 10th 2015
A group of professors in law, sociologists and communication scientists came together to discuss and debate about self tracking cultures and the emergence of hybrid humans.
The intake of the debate was inspired on Deborah Lupton – The Quantified Self, 2012
As we covered different angles within this debate, I will try to recap them in this article.
Quantified Self or Personal Informatics we understand that people are gathering all sorts of data about themselves for different purposes and aims. Today Quantified Self is not an obscure domain anymore, it comes into different sectors such as the workplace, healthcare to name a few. Self tracking in itself is not a new phenomenon. People have being down this all the time, they track finances, the books they read, the films they go to. And setting goals for ourselves is something very popular during the Christmas and new year period. Today we have technology which facilitates all this and makes it maybe easier to track our lives and interests, but also very detailed. Our data is presented in data visualizations and frequency tables, we create data doubles so to speak, a digital data profile. In doing so we use different devices/wearable’s and apps and there are a lot of questions arising now all this gets more diffused in a population.
Some immediate thoughts, but not limited to this.
First, we leave a trace of data behind for ‘ourselves’ but also for ‘others’
Second, what do we learn from gathering our data?
Third, what is behind the data?
Fourth, who owns the data that we are gathering?
Fifth, what happens with the data?
A digital trace for ourselves but also for ‘others’
While self-tracking ourselves we leave a trace of data behind. We leave data behind on the servers from the companies that deliver the devices or the mobile apps. Some of the self-trackers also share their data on Social Networks such as Facebook or other. At moments we also want to create context, so we use photos Instagram or other photo applications, so we kind of create a digital online diary in the cloud. We can generate a construction of the self, a presentation of the self. Which presentation do we want to give?
This data can be interpreted in different ways and provoke different emotions with the user. What do we want to achieve with this data? Do we want to create a better self? If so, what does that mean? Are we striving for a certain role model, a role model that is maybe a hidden standard in the app or device we use? Will this data, presenting ourselves, make us happier and create a sense of well being? Will it confront us with someone who we don’t want to be?
Control and surveillance
As mentioned before, we leave a trace of data behind for ‘others’. Research shows that some personalities like the control aspect these devices create, depending on what is tracked. Other personalities get stressed out by this control. There is a duality within the self-tracking activity, furthermore there is this surveillance aspect. The data stored on private servers, mainly in the US and not under European legislation, where privacy for example is a different regulation. What happens with the data and who owns the data?
While Personal Informatics is entering different domains these questions get more important. Take the workplace for example where companies measure interactions between employees in a meeting. Who is leading and who Is quiet. The measurement of certain behavior of people could be interesting to learn more about certain behavior in a certain situation within a workplace, but if people get accountable for their behavior through self-tracking in so much detail with facts and figures to where does this lead? Will this become part of the evaluation process of an employee?
Is this not also the dream of every insurance company? If you don’t move the minimum 30 minutes per day, and you don’t burn X calories a day, your insurance will get higher because there is no change in your behavior? Are we going to a ‘Digital Health Capitalism, where health is the next commodity in all its aspects?
Behavior design within Personal Informatics?
All the devices and its software have an aim; they are developed to let the user do something. Most of them have Behavior Design aspect in it. It will trigger you or nudge you to start or to create new habits and routines. In itself this is a good aspect. To a certain extent people need nudges to do something more or better. But as with all new technology we as a user need to learn how to go about these new technologies and learn how to use them that it is a proper way for the involved user. We can change our lifestyles for the better, but also here there is this duality again, we can get obsessed about the data or change ourselves so much it is not sustainable and not matching with our original personality, hidden processes get ingrained in our everyday life. We then need to think is this what we want? Do we want to create the ideal body? Thinking about the hidden standards that might behind the thought of these apps, considering most of them are developed in the US California it might be an ideal body that is not an ideal body in another culture? And doing so what if we fail? Will this impact our self-esteem? Will we get worried because we set the goals to high for ourselves and don’t achieve. These algorithms are not emphatic nor compassionate and can be very blunt in that perspective.
Abstract for debate 10th of December 2015
Can Self-Tracking be a bigger promise in healthcare?
As Self-tracking devices get more and more in the mainstream, we see different usage, motivation and engagement. The literature that arises form different domains, looks at different perspectives towards the domain of self-tracking. In this debate we would like to talk about the design perspective of wearable devices or ‘things’ and look at it from a sociological perspective.
In recent literature we learn that these self-tracking tools and devices have a limited usage. People tend to use these devices for a very short time. In (Fogg, 2010) terms we could map these users as span behavior types, with different purposes or aims. Users are excited and curious for the data, set certain goals if possible within the environment that they use, but after two weeks, a month some literature talks about a 6 month (Shih, 2015) maximum before users drop out.
Question arise if Personal Informatics can have more meaning in a healthcare environment. And how can we then create more engagement within this environment. From a design perspective this is rather challenging. In order to come to an engagement design approach, we also need to look at the wellbeing and happiness that could bring these devices. What does it mean for a patient to see all the objective facts of their life, (Ancker JS1, 2015) came to four major themes in interviewing patients and care givers: ‘ (1) tracking this data feels like work for many patients, (2) personal medical data for individuals with chronic conditions are not simply objective facts, but instead provoke strong positive and negative emotions, value judgments, and diverse interpretations, (3) patients track for different purposes, ranging from sense-making to self-management to reporting to the doctor, and (4) patients often notice that physicians trust technologically measured data such as lab reports over patients’ self-tracked data’.
In a broader perspective we need to ask how society will go about in this matter from an ethic and privacy perspective. If we want to create more engagement with these devices, the user needs to trust this environment. Trust not only in accurateness of the data, but also in who owns the data and what happens with the data.
(Lupton D. , 2014) speaks of 5 modes of self-tracking private, communal, pushed, imposed and exploited. These modes can intersect or overlap with each other. In our research we limit ourselves to private self-tracking, pushed self-tracking and to a certain extend communal self-tracking.
(Lupton D. , 2014), defines these modes as follows:
Private self-tracking, as espoused in the Quantified Self’s goal of ‘self knowledge through numbers’, is undertaken for purely personal reasons and the data are kept private or shared only with limited and selected others.
Pushed self-tracking departs from the private self-tracking mode in that the initial incentive for engaging in self-tracking comes from another actor or agency. Self-monitoring may be taken up voluntarily, but in response to external encouragement or advocating rather than as a wholly self-generated and private initiative.
Communal Self-tracking, while self-tracking, in its very name and focus on the ‘self’ may appear to be an individualistic practice, many self-trackers view themselves as part of a community of trackers (Boesel, 2013a; Lupton, 2013a; Nafus & Sherman, 2014; Rooksby, et al., 2014). They use social media, platforms designed for comparing and sharing personal data and sites such as the Quantified Self website to engage with and learn from other self-trackers.
Considering these 3 modes we would like to look deeper into the possibilities of creating more engagement through the more ‘leisure’ wearable devices that are used in conjunction with the ‘medical’ self-tracking devices chronic patients already use. This will give a more holistic view on the behaviour and lifestyle of the patient, create more context to the data and therefor could be analysed to enable a happiness and wellbeing state for the patient.
By learning about attitudes and behaviour of patients we can empathize more and come to a more engaged relationship between patient and care provider. Help the patient in his or her lifestyle improvement or life comfort.
Ancker JS1, W. H. (2015, Aug 19). You Get Reminded You’re a Sick Person”: Personal Data Tracking and Patients With Multiple Chronic Conditions. J Med Internet Res.
Boesel, W. E. (2013). Retrieved from Cyberology: http://thesocietypages.org/cyborgology/2013/05/22/what-is-the-quantified-self-now/#more-15719
Fogg, B. &. (2010). Behavior Wizard: A Method for Matching Target Behaviors with Solutions. Stanford University.
Lupton, D. (2014). Self-tracking Modes: Reflexive Self-Monitoring and Data Practices. Imminent Citizenships: Personhood and Identity Politics in the Informatic Age’ workshop.
Lupton, D. (2013a). Understanding the human machine. IEEE Technology & Society Magazine, 32(4), 25-30 .
Nafus, D. &. (2014). This one does not go up to 11: the Quantified Self movement as an alternative big data practice. International Journal of Communication, 8, 1785-1794.
Rooksby, J. R. (2014). Personal tracking as lived informatics. Proceedings of the 32nd annual ACM conference on Human factors in computing systems, Toronto.
Shih, P. H. (2015). Use and Adoption Challenges of Wearable Activity Trackers. iConference 2015 Proceedings.