PhD Courses in Denmark

Algorithms have come to play a critical role in shaping our lives. Tech giants, government agencies, NGOs and many other actors are turning interactions into data, targeting and shaping preferences and behaviors across a range of social settings. Life chances and opportunities increasingly rely on systems that allocate welfare, jobs, loans, credit, housing, insurance,justice, and education based on a range of computationally generated metrics, scores, and rankings.These types of datafied and algorithmic techniques have been criticized for their opacity and secrecy, and tendencies to stereotype, stigmatize and deepen forms of inequality. A central matter of concern has further been the dehumanization of social relations, turning humans into quantified and rationalized data subjects stripped of the richness of their social lives.

In this PhD course, we engage with these timely concerns by shifting our perspective from the systems to the people who (have to) work and live with them. Using analytic sensibilities from Science & Technology Studies (STS), anthropology of technology, and Critical Data and Algorithm Studies, we ask: what happens if we study algorithmic systems through the experiences and practices of all kinds of people: experts, citizens, developers, consumers and users. Examining algorithmic systems from the perspective of tech professionals, for example, allows us to engage with their own conceptions about issues such as society inequality and future users. Conversely, the perspective of those who use or are exposed to such systems, including credit scoring, welfare predictions, health diagnostics, performance measures, recommender systems, and self-tracking devices, brings us to the realm of privacy and autonomy and a sense of empowerment or disempowerment.To cope with such systems, people rely on algorithmic folklore, and workarounds and resistances, which not only tell of such practices, but of agential possibilities in the digital environment. 

The course will introduce literature that details new forms of organizing, mediation, contestation, and resistance that algorithmic systems have generated. This in turn, creates avenues for thinking about policy, design, and interventions. In the STS spirit of thinking otherwise, we will discuss concepts, including fear and anticipation, breakages and repair, friction and weeds, that aid in rethinking power, practices and people in relation to algorithmic systems and futures. 

Once we begin to examine, through ethnography and other interpretive methods, the different practices that form in relation to datafied and algorithmic systems, the range of questions and concerns begins to expand. Insights from ‘the field’ become important entry points that help us re-imagine established critiques and their analytic purchase. A key aim of the course is therefore to provide an overview of analytic possibilities across a range of fields, and to facilitate a reflexive space for thinking about the normativities, practicalities, and possibilities entailed in different approaches to datafication and algorithmic systems.

Aim:

The course will provide the participants with:
a) an introduction to key scholarly debates about how to understand and analytically engage with questions of datafication, and algorithmic power and how people live with these aspects in their professional and private lives;

b) an opportunity to engage first-hand with empirical materials and how they might help us to rethink themes of critique, practice, and subject-formation, as they are deployed across STS, anthropology and Critical Data and Algorithm Studies;

c) an opportunity to examine how these ways of thinking may (or may not!) be applied to the participants’ own research projects.

Upon completion of the course, participants will have:
• achieved a strong reflexivity regarding the choice of methods, theories, and concepts, and how these foreground or erase specific questions, problems, and normativities in the study of how people live with computational technologies;

• acquired awareness of different ethnographic and conceptual entry points for reconsidering the powers of algorithms and data. This awareness will be exemplified by themes of public administration, professional expertise and participants’ own projects.

• increased participants’ critical ability to account for the potential role of STS and anthropology of technology, in general, and how it is applied in the participant’s research, specifically.

Literature:

Course readings will be specified closer to course date.

Target group:

Only PhD students can participate in the course. Other junior scholars may participate if space allows.

Form:

In terms of format, the course combines a mix of analytical approaches that will help us learn collaboratively and creatively. Based on an initial set of readings and reflections, we will engage in lectures and discussions; data and paper feedback sessions, in which we make sense of fieldnotes, interviews, and artefacts provided by participants; an algorithmic walk through the city of Copenhagen; writing activities and workshops that help us develop and reflect on our own voices in research process.

Language:

English

Lecturers:

Helene Friis Ratner, helr@edu.au.dk
Maja Hojer Bruun, mhbruun@edu.au.dk
Minna Ruckenstein, minna.ruckenstein@helsinki.fi

Venue:

Campus Emdrup, TBA

Application deadline:

Please sign in via the link no later than 7 December 2023