News and events



Thursday 23 August 2018, University of Tampere

12.30 – 13.00 Registration, main building, outside lecture hall A4 (2nd floor)

13.00 – 13.15 Welcome words, Kaarina Nikunen, lecture hall A4, KA

13.15 – 14.30 Key note by Mark Andrejevic:

Becoming Operational: Automated Media, Datafication, and Power

14.30 – 15.00 Coffee

15.00 – 18.00 Workshop (lecture room C5, 1st floor)

Introductions and group work on the burning questions of datafication research

19.00 Dinner, restaurant Tampella (add. Kelloportinkatu 1)

Friday 24 August

9.00 – 10.00 Panel discussion (lecture room C5, 1st floor)

Three approaches to datafication: Göran Bolin (everyday datafication), Rikke Andreassen (inequalities) and Lina Dencik (data justice)

10.15 – 12.00 Workshop continues in lecture room C5

12.00 – 13.00 Lunch

13.00 – 14.00 Workshop continues

14.00 – 15.30 Action plan and next steps

Keynote abstract:

Mark Andrejevic: Becoming Operational: Automated Media, Datafication, and Power

This presentation proposes some key concepts for thinking about the social impact of data-driven decision making. It argues that datafication and automation go hand-in-hand because of cascading logics of automation: automated data collection leads to automated data processing and, eventually, automated decision making and action.  Such forms of automation rely on processes of simulation and pre-emption that dispense with the trappings of representation (and thus with the space for action that it opens up). Trevor Paglen, building on the work of Harun Farocki, describes operational images as those which serve as a form of action (by being part of a technical operation), rather than of representation. The presentation considers what is at stake in the eclipse of representation and how it might serve as a leverage point for contesting the forms of opacity that characterize automated decision-making processes. The presentation develops an account of the relationship between simulation, pre-emption, and environmental forms of governance. It concludes wish some suggestions for contesting the post-subjective logics that link these together.


17-18 June, 2019, Copenhagen/Roskilde University

Monday 17 June

12.00 – 13.00 Registration and coffee

13.00 – 13.00 Welcome/Rikke Andreassen

13.15 – 14.30 Keynote by Seeta Gangadharan London School of Economics:

A politics of refusal: Agency, choice, and technology

14.30 – 15.00  Coffee

15.00 – 16.30   Panel: What Constitutes ‘Good Data’ in the Creative Economy?

Helen Kennedy, Laura Mayne, Jedrzej Niklas, Susan Oman, Robin Steedman, David Beer, Mark Taylor, Helen Thornham

17.00 – 18.00  Future work and challenges

19.00  Dinner

Tuesday 18 June:

8.30 – 9.00  Coffee

9.00 – 10.30  Panel: Automated Decision Making in the European Union     

Matthias Spielkamp, Algorithm Watch: Report Automating Societies

Minna Ruckenstein: Debating and repairing ADM systems

Anne Kaun: Folkhemmet 4.0. Automating the Welfare State

10.45 – 12.00 Workshop presentations

Niamh Ni Bhroin & Steffen Krüger: “Vital Signs: Exploring Inequality through Datafication in Self-Tracking Health Insurance”

Anders Olof Larsson: “Navigating a ‘Post-API age’”

Susana Tosca ‘A participatory ethics of the good media life?’

12.00 – 13.00 Lunch

13.00 – 15.00    Workshop presentations

Julia Velkova: ”The ‘non-people’ of datafication: data centres and human labour”

Salla-Maaria Laaksonen: “Data magic performativity and social power of data in analytics companies”

Pille Pruulmann-Vengerfeldt: “Datafication of museum visit – tracking visitor with smart ticket”

15.00 – 16.00  Next steps




Seeta Peña Gangadharan: A politics of refusal: Agency, choice, and technology
From theoretical computer scientists to industry data scientists, the inevitability of intelligent, optimization-based systems appears to go unquestioned. Algorithmic decision making and artificial intelligence are coming or are already here. Even those studying and practicing fairness, accountability, and transparency in machine learning tend to accept automated computer systems’ hegemony, while trying to mitigate any harmful social impacts of these technologies. In this talk, I challenge this discourse of inevitability by rethinking the idea of exclusion in technologically mediated society. Reflecting on theories of abnormal justice and subaltern ethics, I argue exclusion can serve as productive force of change to counter sociotechnical forms of inequality. From individually motivated to coordinated acts, exclusion from automated, data-driven systems is an affirmation of human agency in the face of technological forms of governance.


Panel: Automated Decision Making in the European Union

Minna Ruckenstein: Debating and repairing ADM systems

The presentation revisits selected cases of the AlgorithmWatch report, Finland section, co-written with Julia Velkova ( These cases have served as conversation openers, both among experts and citizens, underlining the open-ended nature of the current debate concerning automated decision making (ADM) systems. The piloting of uses of data analytics in the public sector with the aim of predicting future child services needs provokes fears about citizen monitoring. The credit scoring controversy described in the report underlines both citizens’ and ombudsman’s role in resourcefully using existing legal and political tools. Another controversy, focusing on a company with a product that lets potential employers scan emails of job applicants, raises questions about the repackaging of technological offerings to a market that is already potentially intrusive and discriminatory. In the Nordic counties, a particular societal strength lies in a broad consensus that ADM harms need to be avoided and fixed. Yet, in order to understand what those harms might be, we need to closely follow ADM systems and how they are actually used. If the aim is to have “livable relations” with ADM, we need to know these systems intimately, work with them and shape them.

Anne Kaun: Folkhemmet 4.0. Automating the Welfare State

In February 2019, Swedish journalists revealed that up to 70.000 decisions by the employment services might have been false because of a server failure. Employment services are however unable to pin down when the failure exactly occurred and how many decisions have actually been false. Consequently, recipients of benefits might have experienced cuts of their payments, but nobody knows for sure. This example shows that Robot Automation Process – or automated-decision making – has far reaching consequences if there are failures in the digital infrastructure, the input data or mathematical models employed. Regardless the encountered problems, automation of the public sector in Sweden is and continues to be in full-swing. The employment services, for example, plan to fully automate large parts of their activities within the next two years. Automated-decision making in the public sector is often presented as cost efficient and more reliable than decisions made by humans. This presentation, however, suggest that the automation in public services on large scale is part of the ongoing process of restructuring and largely dismantling of welfare state institutions and needs to be considered in a broader discussion of how digital technologies are fundamentally changing our societies.

This presentation contributes a historical perspective on the consequences of automation in the social service sector, in order to engage with emerging tensions and controversies from automation projects such as the one implemented by the employment agency. It engages with the question why Scandinavian countries are prone to introduce and reinforce these forms of automation based on dataism by tracing them back to ideas of the Folkhemmet (the people’s home) of the 1930s. Linking current developments of automated decision-making to ideas of the people’s home, we show how the citizen in Sweden has always already been datafied in order to measure and manage populations and implement ideas of the welfare state. We furthermore discuss the qualitative changes in measuring and managing populations in the current technological and socio-economic context of dismantling of the welfare state.

Panel : What Constitutes ‘Good Data’ in the Creative Economy?

Helen Kennedy, Laura Mayne, Jedrzej Niklas, Susan Oman, Robin Steedman, David Beer, Mark Taylor, Helen Thornham

Asking what constitute good data practices is an essential part of the data studies project. It follows on from critical work that has exposed the harms that accompany widespread datafication. If current ‘data arrangements’ are harmful to non-powerful citizens, as critical data studies scholarship suggests, then alternative arrangements are needed, and thinking about what constitutes good data is one way of examining what these might look like. Building on critical groundwork, on What Constitutes ‘Good Data’ in the Creative Economy? (hereafter Good Data), we consider whether it is possible to conceive of life with data as other than harmful and oppressive. We understand ‘good’ as a complex, normative concept – it could mean fair, ethical or just, but it could also have other meanings. We use this concept because it is open for actors to define in their own terms and in relation to their own data practices and experiences.

Good Data involves four Postdoctoral Fellows exploring the question in the project’s title with four creative economy partner organisations, reflecting critically on their data analytics and other data practices, how they communicate what they do with data with end users and audiences, and related issues of fairness, ethics and justice. In our presentation, after a brief introduction, the four post-doctoral fellows will talk about their individual projects, which involve working with:

  • a trade body for the video game industry, representing hundreds of game developers and producers (Jedrzej Niklas);
  • a charity which maintains a large film archive and allocates funding to film production, distribution, audience development, and research (Laura Mayne);
  • a public service broadcaster (Robin Steedman);
  • a large arts funder (Susan Oman).

We will conclude by reflecting on tentative answers to the project question.

Niamh Ni Bhroin & Steffen Krüger: Vital Signs: Exploring Inequality through Datafication in Self-Tracking Health Insurance

Health insurers are increasingly harnessing processes of datafication to innovate and create new insurance products for their customers. These include the development of loss-framed incentives, such as Discovery’s Vitality Program, where customers can obtain an Apple Watch ‘almost for free’, as long as they follow and record data relating to their individual ‘health journeys’ over a two-year period.

In this paper we outline the potential consequences of these new insurance products, with a particular focus on the enhancement of existing health and social inequalities. These inequalities arise because of the personalization of health insurance based on aggregate and individual data analysis. This moves away from pervious collective insurance schemes, where members would have a shared responsibility and related premium, regardless of their individual level of health or fitness. The schemes are also reliant on the integration of digital infrastructures, through which customers can be nudged and guided to behave and consume in ways that will support their achievement of optimum health. These schemes, as they relate to health and life insurance, are being strongly resisted in certain European contexts, in particular in Germany.

Through a discourse analysis of published materials, including websites, industry-publications, journalism and applied and critical research, we explore how these deals are presented and understood. We find that insurers are increasingly encouraged to ‘get on board’ and harness the potential of datafication, while consumers are warned about potential risks to data privacy and security. At the same time, insurers are encouraged to ‘target the most lucrative customers’, i.e. those with the lowest health risks, while end-users are encouraged ‘to consume wellness’. This contributes to increasing social inequality.

Anders Olof Larsson: Navigating a ‘Post-API age’

As the application programming interfaces (APIs) of many social platforms are closing or monetizing the forms of data collection that were previously available to researchers, scholars interested in the subfield of media and communication research loosely defined as ‘computational communication research’ as well as beyond must seek new ways to gather data. Renowned scholars like Deen Freelon and Axel Bruns have suggested that as these events unfold in the post Cambridge Analytica stage, we are entering into a “Post-API age” – as Freelon puts it, “heavy investment in teaching and learning platform-specific methods can be rendered useless overnight” (Freelon 2018, 1) when the companies operating these platforms decide to remove the access that many researchers have depended on. Of course, this is nothing new – efforts similar to those now taken by Facebook were indeed undertaken by Twitter in 2011 (O’Brien 2011). In a legal sense, these companies certainly have the rights to do with their content as they wish. However, given that services like Facebook and Twitter now carry almost infrastructural, societal functionalities – whether they like it or acknowledge it or not – the argument could be made that they need to work together with interested and relevant parties such as researchers to make sure that scholarly insights into commonly discussed issues like so-called fake news or the practice of trying to influence elections can remain accurate. For the meeting in Copenhagen, I’d like to discuss some of the possible ways forward for researchers interested in harvesting data from social platforms – including, but not necessarily limited to the introduction of Crowdtangle for academics and The Social Science Research Council Social Data Initiative.

Susana Tosca: A participatory ethics of the good media life?

Participatory design methods (Bodker, 1996; Sanders & Stappers, 2008) have long been recognized to be a viable way to incorporate the voices and life situations of technology users. They have been implemented in the design of actual prototypes and technologies, but they can also be applied to invite users of social and digital media to reflect about the ways in which their current media use affects their attempt to live a good life.

Research has pointed out the problematic aspects of intense mediatization (Couldry & Hepp, 2017) and the ways that our selves are marketed and exploited (Fenton, 2012; Van Dijck, 2013). But how do regular people deal with these challenges? Which strategies do they devise to use media in a positive way in the face of structural oppression? How do they juggle morality, ethics and the practical concerns of everyday life?

In this paper, I will present the results of a series of “utopian” participatory design workshops inspired by the work of Ruth Levitas (2013), where users of technology are required to think of ways in which digital mediation could support them in their aspiration to the good life (Carlisle, 2013), as well as ways in which the good life can be protected from unwelcome intrusions. The workshops goal is to involve the subjects themselves in defining the kinds of meaningful agency that are possible in a highly mediatised world. My presentation will deal with the methodological challenges of applying participatory design methods to the realm of ethical reflection.

Julia Velkova: The ‘non-people’ of datafication: data centres and human labour

Over the past decade, the data capturing practices of sensing media, platforms and algorithms have propelled the intense construction of large-scale, environmentally and energy-intense communication processing infrastructures such as data centres across the world. Strategic corporate visual communication, and media scholars alike have created an understanding of data centres as automated, depopulated, non-human spaces that are full of endless racks of servers. With this paper  I argue for the importance to understand data centres not only as data spaces, but also as workplaces, asking questions about the nature and experiences of labour in them. Drawing upon qualitative interviews, participant observation and a vast photo-material shared with me by the employees working at the second largest data centre in Finland, one operated by the Russian IT giant, Yandex, I illuminate the experiences of work of those who Susan Leigh Star (1999) calls the ‘nonpeople’, people such as security guards, and maintenance workers who ensure the proper functioning of information infrastructures. With feminist art critique Lucy Lippard (1974/2010), and anthropologist Mary Douglas’s (1991) ideas of home, I show how the labour of maintaining a crucial part of Russian internet consumption and data practices is contingent on the creative labour of everyday inhabiting and humanising the industrial space of the data centre. This labour rests upon mobilising traditionally feminine domestic craft and hobby art work such as gardening, cooking, and waste reuse as mode of critique and ultimately, a transformational rehabilitation of a space designed to cater for the machines rather than that for that of the people caring for machines.

Salla-Maaria Laaksonen: Data magic performativity and social power of data in analytics companies

Data, in its many forms, as well as various algorithms used to handle the data, have become central features of our everyday (e.g., Kitchin, 2014; Iliadis & Russo, 2016; Schäfer & Es, 2017). Further, the availability of massive datasets and the need to develop computational methods to analyze them is a prominent technological change affecting organizations. This paper argues that data does not only represent and abstract social action, but also plays a performative role in social situations within organizations and in the process of organizing. By bridging critical data studies with the sociomateriality literature in organization studies, this study looks at the ways how material/technological factors interact with the human/social factors in organizational settings in the context of data analytics. The paper builds on ethnographic field notes and thematic interviews collected during participatory observation periods in five organizations working in the field of social media analytics. The setting allowed for observing and tracing how social media data assemblages (Kitchin & Lauriault, 2018) are formed as they travel through the organization. In this process, the data transforms from raw material to an organizing agent inside the companies, but also acts as a substitute for various social meanings. In addition, it works to institutionalize data analytics practices across organizations and reproduces data assemblage formations that support the existing power positions of platform companies.

Pille Pruulmann-Vengerfeldt: Datafication of museum visit – tracking with smart ticket

Estonian National Museum opened new permanent exhibition in October 2016 and the e-ink based digital labels allow visitors holding language switching cards to change the language of the displays. Today, the cards provide access to ten different languages and can be used across more than 300 e-ink displays across the 6000m2 of exhibition space. In the log data, the individual use is not identifiable as no user-data is collected at the issue of the card. Card is not personalised and is issued at the door to people who don’t read Estonian, the default language of the e-ink displays. Log data is collected in a joint database across all cards and all displays.

Today, museum is in the process of developing smart-tickets, chip-based printed ticket that allows more detailed user-tracking and rewards the visitor with access to a specific digital layer based on your behaviour during the exhibition. The smart-ticket offers theoretically unlimited possibilities of linking additional data from museum databases, extending the provided information with curatorial discussion layer and allowing cultural citizenship through participatory engagement.

Today, museum does not analyse data collected with language cards, rather, the discussions are around the potential use or usefulness of such data. The seminar presentation aims to discuss the challenge of inequalities that extensive use of such data could create as well as the challenges of a more personalised smart-ticket, which is planned to be implemented in the first version by the end of 2019.



9.-10.3. 2020 Södertörn University, Stockholm, Sweden (cancelled due Covid-19)

Monday 9 March  Van Der Nootska Palatset

11.30-12.30     Lunch

12.30-12.45     Welcome

12.45-14.15     Keynote 1: Stefania Milan, Amsterdam University

Activism and research in the wake of intrusive technology

14.15-14.45     Coffee break

14.45-16.15     Methods workshop with Airi Lampinen & Pablo Velasco, chair Anne Kaun

16.15-16.30     Short break

16.30-17.30    Workshop presentations

Tuukka Lehtiniemi: Imagining the data economy

Kaarina Nikunen & Jenni Hokka: Data workshops and data intimacy

19.00  Dinner

Tuesday, 10 March, Van Der Nootska Palatset

9.00-9.30         Coffee

9.30-11.00       Keynote 2: Dorothy Kidd, University of San Francisco

Data justice, counter-planning and contention: a research approach

11.00-12.30     Workshop presentations

Jannie Møller Hartley, Norbert Wildermuth, David Mathieu, Sander Schwartz: Lurking, making yourself invisible and shrugging it off – Small Acts of Engagement in Datafied Everyday Lives

Anders O Larsson: Academic research and access to social media data in a ‘Post-API age’

12.30-13.30   Lunch

13.30-14.30   Future plans (collaborations, publications, conferences, funding applications, PhD   courses, etc.)

14.30-15.00     Coffee and Wrap-up session and goodbye.



Keynote 1

Stefania Milan: Activism and research in the wake of intrusive technology

Intrusive technology such as personalization algorithms or ‘smart’ surveillance cameras is at the core of data capitalism. Its introduction has radically altered the role of information and technology in the constitution of society, accelerating the crisis of liberal democracy. Its global diffusion is contributing to change power relations from the local to the transnational, introducing novel forms of colonial exploitation. This talk departs from exploring two forms of intrusive technology which constitute two of the building blocks of data capitalism today, namely AdTech, or the technological ecosystem supporting targeted advertising, and facial recognition technology, as one of the most widespread yet most intrusive applications of Artificial Intelligence. It then goes on asking what space we can carve out for (data) activism, and whether we can devise research methods and strategies that are able to promote and support the political agency of the grassroots.

Keynote 2

Dorothy Kidd: Data justice, counter-planning and contention: a research approach

This session presents a study of the use of data, and specifically counter-mapping, in two historical cycles of Indigenous resistance to oil pipelines in western Canada. It briefly summarizes the integral use of data in the European colonial project of mapping the land and sites of potential resource extraction, together with the mass surveillance and violent dispossession of Indigenous peoples; it thus confirms the long historical use of data to exert political, economic and cultural power and control and enclose, disappear and/or silence competing knowledges. However, the study is not about digital inequities per se, but instead argues for centering enquiry about data justice within the specific contexts, histories and practices social movement actor contention. The study examines three different Indigenous first nations and how they have used counter-mapping with the Canadian state and extractive industries as one part of their repertoires of political organizing in two historical cycles, the 1970s and the current period.

My findings suggest that in each case they designed and developed collective data collection that not only countered the knowledge-making systems and discourses of the state, but also benefited their collective knowledge and use of their territories, and in the process developed new collective imaginaries, identities and new forms of governance. The presentation ends by discussing how to develop research approaches about data justice that begin with the contentious, and constitutive practices of social justice movements in specific contexts and locales.

Workshop presentations

Jannie Møller Hartley, Norbert Wildermuth, David Mathieu, Sander Schwartz : Lurking, making yourself invisible and shrugging it off – Small Acts of Engagement in Datafied Everyday Lives

Datafication has been conceived as a large-scale process extending the mediatization of society (Couldry, Nick; Hepp, 2017), an ideology (van Dijck, 2014) that attempts to rethink the way we “live, work and think” (Mayer-Schönberger & Cukier, 2013), a process of colonization of the lifeworld (Couldry & Mejias, 2018). While productive contributions to our understanding of datafication these accounts provide what could be called a top-down approach to datafication, highlighting the ways data logics enter and shape the realm of research (Emery et Al. 2014; boyd & Crawford, 2012), business (Mayer-Schönberger & Cukier, 2013) or media production (Arsenault, 2017). In this paper we argue for a bottom-up approach focusing on what Pink et al. has conceptualized as the mundane data routines and habits of coping with data anxieties and thus ordinary users’ coping strategies (Pink, Lanzeni, & Horst, 2018).

Thus, with empirical grounding in focus groups carried out in 2018 in Roskilde, Denmark, with a total of 34 participants this paper shows how citizens are mobilizing a variety of routines to cope and makes sense of the risks they themselves identify from experiences with datafied platforms in their everyday lives. Each group had from 4-9 male and female participants divided into groups according to age (18-35/35-60) and education level (high/low) in order to increase homogeny and productivity in group discussions (Bloor, 2001).  The data is analysed through the theoretical framework of Small Acts of Engagements, SAOE, (Picone et al., 2019), which aims to capture how people both pay attention to how we act (or choose not to act) upon attention (whether as objects or symbolic messages) and involve ourselves cognitively and affectively with media content. In this way the paper shifts the analytical lens from seeing the users as merely powerless, either unable to grasp the complexities of datafication or feeling anxious about not being able to act, providing an analysis of the agency of the audiences as ‘coping’, however small these acts might be. The paper identifies four types of small acts of engaging indatafied everyday life, namely coping by absence, coping by trust, coping by minimizing risk and coping by apathy.

Tuukka Lehtiniemi: Imagining the data economy

In this presentation I discuss the results of my PhD research on data activism in the context of the personal data economy. The digital environment is increasingly organised to transform aspects of people’s lives into data, in order to make use of those data in the production of economic value. Data activism has emerged as one response to the resulting asymmetries in data usage and distribution. Adopting the concept of collective imagination, my thesis investigates imaginaries about an alternative data economy developed in data activism. Based on data studies literature, I first construct a view onto the dominant data economy imaginary. It consists of collectively shared notions about how the data economy currently functions and ought to function. Based on four original publications, alternative imaginaries are compared with the dominant imaginary. The aim is to examine the alternative imaginaries and their underpinnings, as well as to scrutinise the desirability of the data futures they promote.

The empirical research has focused on MyData, a data governance initiative striving for a more central role for people in the data economy. The thesis identifies two alternative imaginaries developed in the context of the initiative, the market imaginary and the citizen imaginary. Both rely on a notion of data agency, or providing people with new capabilities to act in relation to personal data. The market imaginary relies on market forces for data governance, based on viewing data agency as market choice. Individuals are imagined to act in data markets to improve their lives, making data serve their personal ends. The citizen imaginary foregrounds collective data governance and the common good. Here, data agency is imagined as citizens’ collective capability to participate in the processes that determine how, and for what purposes, their data are used.  In the thesis I discuss how the market imaginary is better positioned of the two to expand beyond data activism; it resonates with technology developers’ imaginaries, leverages existing regulatory instruments and is aligned with commercial notions of the value of data. The reliance on market agency, however, is a precarious starting point for a desirable data future. The practical implication is to encourage data activists to experiment on collective data governance and on new ways to make data valuable, alongside the market-oriented ones. The implication for data activism research is that identifying imaginaries underpinning activist initiatives can aid with shaping pathways towards a desirable digital environment.

Kaarina Nikunen & Jenni Hokka: Lessons learned from data workshops

This paper presents a research conducted in cooperation with the Finnish public service media company YLE that explored people’s ideas and understandings of data gathering practices and their impact on their everyday lives. The aim of the data workshops was twofold: to raise awareness of data gathering practices and datafied media environment as well as to explore people’s feelings, ideas and visions on data practices and the future of data. In this paper we introduce our workshop method and the main results:  the understandings, desires, uncertainties, addictions and even shame expressed in relation to data gathering practices. Drawing on work by Kennedy et al. (2015) we argue for the importance of seeing agency in everyday data practices, as a way to imagine alternatives to current situation. We also discuss the visions and possibilities of creating data management policy on everyday level, for example in terms of how to use data for collective good. While discussions on data in these workshops pointed out the importance of public, transparent data infrastructures they also revealed the contradictions and challenges of organizing data workshops, particularly in engaging with people in vulnerable positions. We critically reflect on the lessons learned from these workshops and the ways they have shaped our current work with digital intimacy and data paths.