Petter Falk, new doctor in Political Science at ý and the Service Research Centre (CTF), sheds light on conditions and grounds for datafication in his doctoral thesis “Assemble Care // Align Data”.
– What surprised me the most was that datafication is intuitively accepted, despite a kind of intellectual resistance, says Petter Falk.
The term “big data” is frequently used nowadays, but your research emphasises the importance of the small details. Why is that?
– First of all, it needs to be said that “the small details” aren’t the opposite of what some refer to as Big Data. It is when the small details, such as individual documented interactions with the healthcare system and social services, accumulate that they actually create a critical mass of data. This, in turn, becomes part of what I highlight in my thesis, namely the conditions and grounds underlying what we refer to as datafication, when the transformation of life and society becomes normalised.
What are the most notable discoveries from your study?
– I have primarily looked at how datafication arises and what effect this has on the view of patients and users as subjects. And perhaps the most notable finding in my study is that there is a so-called epistemological dissonance in how data is understood as a resource, and what it can achieve. Nurses and social workers are aware that the data they produce in meetings with patients and users does not always represent the situation or needs of the patient or user in a fair and relevant way. At the same time, Swedish welfare organisations still choose to base both decisions and new data-driven initiatives on this data. In the end, this leads to the representation of patients and users as data-driven subjects being undermined, and in the long run, it should be considered a democratic risk.
Why are these specific results evident?
– These tendencies don’t become completely clear until you zoom out a bit and look at both small and large aspects. It’s easy to focus on emerging technologies like AI and robots, instead of on the fundamental prerequisite for these to work – namely data. But if you have experience with the data-driven systems of the public welfare, for example in the role as a nurse or social worker, you are often well aware of its shortcomings.
Was there anything in your research that surprised you?
– What surprised me the most was that datafication is intuitively accepted, despite a kind of intellectual resistance. Welfare organisations have good insights about the shortcomings in data production, while also clearly expressing ambitions to still use this data to achieve new data-driven insights or develop new types of data-driven systems. Datafication thus becomes a kind of force of nature that sort of “just happens” without being processed through political discussion or democratic analysis.
In what way do you think your research can be of benefit to others?
– I hope and believe that it can be useful as a starting point for reflection on data and data-driven welfare. My experience is that there is a need for both practitioners and decision-makers to conceptualise data as a democratic resource, but it is still unclear how to approach this.
The datafication of, for example, healthcare was intended to greatly improve efficiency – has that happened?
– First of all, it is important to differentiate between digitalisation and datafication, because they are not the same thing. Put simply, digitalisation means that you make an analogue process digital. Datafication means an increased use and normalisation of data.
– It is also important to discuss what efficiency improvement is and how this concept is used to describe the state of an organisation. In my studies, I noticed that sometimes a digital service or solution can be of great use to a certain practice. But in other contexts, it may bring an administrative burden and more bureaucracy. And what is efficient for welfare organisations, such as minimising time with patients or users, may not be at all what the patient or user wants.
– What I can say based on my research on datafication is that the term “efficiency” is often used as a signal word to enable new data-driven systems and new data production, even if it’s not necessarily something directly requested by patient and user groups. In my study, I refer to this as a “datafied gaze”, a kind of perspective where actors are constantly looking for new ways to transform interactions with patients and users into data.
How has your study been received?
– If we look at the empirical context, the reception has been mixed. Operational staff, such as nurses and social workers, often shrug their shoulders and say “we already knew this”, while also being grateful that someone is highlighting the phenomenon as a problem. For strategic staff and decision-makers, it is often a bit difficult to be critical of datafication because it becomes an indirect criticism of digitalisation as a process. Since their entire existence is so marked by a drive to digitalise as much as possible, it also becomes a kind of questioning of the prevailing logic and ethics related to the goals of the organisations. In light of this, my research findings, even if they may seem intuitive, become a type of threat to the current ambition.
– At the same time, I can already see that the issues I have raised in my thesis resonate with several welfare organisations. For example, one of the organisations I studied has chosen to refer to my research in their new digitalisation strategies, and I’m having ongoing discussions with two other organisations about creating a course specifically on datafication in democratically governed organisations.
Has your study opened up for more research?
– I will continue to deepen my research within the framework of various collaborations and will remain at ý. I also have several ongoing dialogues with research networks both in Sweden and internationally.
