This brief presentation will introduce you to some main points of our research paper
”Work of the Unemployed: An inquiry into individuals’ experience of data usage in
public services and possibilities for their agency”. I am Naja Holten Møller, Assistant
Professor at the University of Copenhagen – and I present this research on behalf
of my co-authors as well, Trine Rask Nielsen, University of Copenhagen and Christopher Le
Dantec, Georgia Institute of Technology.
The study shows how approaches, such as design fiction, are effective at including marginalized
communities through changing the conditions for design. Showcasing the fictional outlook,
and how the ‘design experience’ can be disempowering if not qualified through a deeper
critique, the paper contributes to agendas on design justice.
We set up this fiction to address power dynamics in public services and job placement more
specifically.
We wanted to understand how individuals experience the use of data about them through a fictive
app, speculating what future datafied jobplacement could look like.
The context of this study is Danish job placement and this paper builds on a longer ethnographic
fieldwork across 2 municipal job centers, which has been ongoing through a couple of
years by now, focusing on casework and Citizens’ Strategies for Exercising Authority and Personal
Autonomy in Social Welfare.
The overall question we explore in tnis paper is: What happens once (new) forms of data becomes institutionalized and designed
– potentially invisibly – into the decision-making infrastructures that gatekeep access to public services?
What we see in this picture is the citizen portal for unemployment services the way it looks today.
Today public services increasingly presume a new and more active role for individuals
to play in datafied society: However, while design efforts attempt to include stakeholders,
such attempts are often limited to professional perspectives. However, little is known about
how individuals who are subject to these solutions experience the increasing use of data about them.
The design fiction of this paper that we all jobnettrace is a possible, yet fictional scenario: an app for unemployed
individuals ‘work’ that they have to perform by managing how data about their lives, including new uses of social media data etc.,
are shared in order to make themselves eligible for support, as we will see demonstrated in this next clip.
Imagine a platform: “jobnettrace” — a further development of an already existing
Danish job placement platform called jobnet.dk, but now as an app with self-tracking elements….
On this platform, individuals can apply for particular services and job placement offers
and this way support is earned as the unemployed individual uploads self-tracking data – personal
data, like GPS data, data from social media, or health data.
An algorithm classifies the performance of unemployed individuals based on the data they
upload. This way the algorithm becomes the central mechanism for accountability and control
instead of the caseworker, who acts as an arbitrator between the individual citizen
and the algorithm.
To understand how individuals experience data usage in this setting, we set up 4 online
focus groups and invited 20 individuals enrolled in job placement to reflect on the app and
fictive scenario, and they were then invited to reflect and debate with each other these
4 questions:
What do you think of the fictional app shown in the video and illustrated here?
What information about you do you see as being your personal information and what information about you do you want to share with the job
center, and in what situations? Why? And why not?
When do you think it’s okay for the job center to collect information about you
if you get something in return, and in what situations?
What is important to you in terms of being able to trust the job center ’s use of
information about you, and in what situations?
Here we see some examples of the responses we got. Our first findings shows that Individuals’
experience use of scores as illegitimate and stressful as we hear from one individual stating:
“A score of ones ‘success’ would add yet another stress factor to being unemployed.
It would not be motivating, as it is probably intended, because I would feel pressured to
always keep an eye on my score. I miss an elaboration on what the score is based on?”
Secondly, we find that our participants neither perceived data about the individual as a commodity
nor civic duty, as we hear from another individual in the study:
“Income: Of course they need to know, because it’s fair that I still receive support.
Educational background: Yes, then hopefully they can help me in my job search.
Health data: Yes, if I am entitled to sickness benets.
The rest: Absolutely not. Consider it surveillance.”
Finally, Intention matters for the kinds of data individuals share, we find in the study.
One individual reflects: “Trust in job placement can be increased if you as an unemployed is
met with care and interest, as a human and individual, and not just a number in a row.
It is, in fact, the most important thing that could be done differently [in job placement].
What we learn from the study is also that data sharing is decided within the specific relation and in this way data are folded
into the hierarchical interactions among caseworker and individual within the larger context
job placement and other kinds of public authorities involved in the production of data about the
individual. From this perspective, unemployed unemployed individuals have a legitimate interest
in the design of algorithmic public services
Understanding data as something that may be commodified
critically shapes how we should make individual experiences a resource for designing service provisions.
Data usage, we find, is experienced by unemployed individuals
as more or less reasonable but their assessment of reasonableness runs into gaps.
The non-technical public understands agency as
the power to take control of usage of data, distinct from
power over the conditions and individual impact.
Thus, designers of public services need to be attentive to the limits of how individual agency can be exercised in conditions that allow it.
To sum up, what this scenario means for design of algorithmic public services, is that we
need to be less concerned with the materialities of data, and more concerned with the materialities
of policy, regulation, and the state as it institutionalizes and encodes itself into
digital infrastructures of decision-making in public services.
This study shows how approaches, such as design fiction, are effective at including marginalized communities through changing the conditions for design.
We thank all the individuals that were involved in the study for their engaged participation
in the focus groups. We also extend our appreciation to the caseworkers and job centers that invited
us to ethnographically study their practices, which has been the foundation for this work.
This work has been supported by the Innovation Fund Denmark
Thank you for listening.