I am thrilled that our edited volume on The Ambivalences of Data Power is finally out. It explores three new perspectives in Critical Data Studies across 18 contributions.
(1) Global Infrastructures and Local Invisibilities
(2) State and DataJustice
(3) Everyday Practices and Collective Action
Data power is a highly ambivalent phenomenon and it is precisely these ambivalences that open up important perspectives for the burgeoning field of critical data studies: First, the ambivalences between global infrastructures and local invisibilities. These challenge the grand narrative of the ephemeral nature of a global data infrastructure and instead make visible the local working and living conditions, and resources and arrangements required to operate and run them. Second is the ambivalences between the state and data justice. These consider data justice in relation to state surveillance and data capitalism and reflect the ambivalences between an “entrepreneurial state” and a “welfare state”. Third is the ambivalences of everyday practices and collective action, in which civil society groups, communities, and movements try to position the interests of people against the “big players” in the tech industry. With this introduction, we want to make the argument that seeing data power and its irreducible ambivalences in a pointed way will provide an orientation to the chapters of this book. To this end, we first give a brief outline of the development of critical data studies. In part, we also want to situate the data power conferences, the most recent of which this volume is based on. This will then serve as a basis for taking a closer look at three facets of the ambivalence of data power.
On the 1st of December I received a very special and unique honour: together with my colleague Irina Zakharova we received the Berninghausen Prize for Outstanding Teaching 2021 from the University of Bremen in the category “Participatory Teaching”. The prize has been awarded annually since 1991. This year, a total of 125 academics were nominated. A committee made up of teaching staff, university staff, and students perused the submissions and put forward the winners. In addition to us, the economist Dr. Jan Harima and the psychology professor Dr. Nina Heinrichs were each awarded a student prize.
The justification for our prize states:
“Dr. Juliane Jarke and Irina Zakharova from the Faculty of Mathematics / Computer Science won over the jury with their concept for joint teaching and learning. In the “Participative Teaching” category, they were honored for the module “Participative Methods of Software Design.” The class was carried out digitally with team-teaching in the summer semester 2021. Students had full writing and access rights to the utilized platform. Additionally, each small group had their own board for preparation, organization, and communication. Previous class participants’ experiences were incorporated. The jury was impressed that dealing with specialist literature played a role in the final grade, as this is often something that does not receive enough consideration in computer sciences. The lecturers also met up directly with groups outside of video conferences in order to talk through their work. The students spoke their praise for the fact that the class was designed well in terms of content and didactics.”
Are you interested in co-creation? I talked to the student podcast UniBits of the University of Bremen about my reseach and the potential of co-creation for a more inclusive and participatory digital society.
Find out more here (in German): https://blogs.uni-bremen.de/digitales/podcast-unibits/ or directly at Spotify
Data dashboards do not only visualise facts, they also produce compelling narratives.
In our paper, Felicitas Macgilchrist and I trace the stories told by dashboards of AI-powered learning analytics and discuss the implications for educational futures and edtech
With narrative we do not only mean fiction. Narrative refers to a mode of presentation in which a sequence of actions or events unfold over time, involving one or more characters, often involving change.
We analysed one of the leadinglearning management systems which offers adaptive learning tools and predictive analytics for premium clients. The system integrates far more real-time data than early warning systems in education have ever done. We identified 3 stories:
In the first, teachers are managers who oversee, design interventions, check the effects of their interventions, improve efficiency and effectiveness. The multiple further roles of teachers are rendered invisible and thus irrelevant to this particular understanding of education.
The second story is about risk. In the materials, we see red colours flagging a student in trouble. We see him beginning to struggle, as his “success index” decreases over the weeks. The dashboard shows him as the most at risk and in need for intervention.
The third is about sociality: it is risky, the dashboard tells users, for a student to be insufficiently socially integrated and connected. Those students are portrayed as ‘successful’ characters in the dashboard story who maximise their in-tech interactions with others.
As educational and other fields are increasingly embracing predictive tools, it is crucial to examine these systems and their narratives, to highlight how they are harmful, and to consider if and how they are being used beyond the current limited and limiting recommendations.
Very much looking forward to presenting at the Data Science Forum (University of Bremen) next Thursday (17th June, 12pm CEST). I will engage with some of the work on Data Science that has emerged in STS and critical data studies and report from our own projects. Here is an interview that gives a short preview.
I am super excited that the paper I have co-authored with Hendrik Heuer and Andreas Breiter on the problematic framing of Machine Learning in tutorials has been published in Big Data & Society. Machine learning has become a key component of contemporary information systems. Unlike prior information systems explicitly programmed in formal languages, ML systems infer rules from data. In the paper we show what this difference means for the critical analysis of socio-technical systems based on machine learning. To provide a foundation for future critical analysis of machine learning-based systems, we engage with how the term is framed and constructed in self-education resources. For this, we analyze machine learning tutorials, an important information source for self-learners and a key tool for the formation of the practices of the machine learning community. Our analysis identifies canonical examples of machine learning as well as important misconceptions and problematic framings. Our results show that machine learning is presented as being universally applicable and that the application of machine learning without special expertise is actively encouraged. Explanations of machine learning algorithms are missing or strongly limited. Meanwhile, the importance of data is vastly understated. This has implications for the manifestation of (new) social inequalities through machine learning-based systems.
The interdisciplinary Socio-Gerontechnology Network attends to questions of the use and design of gerontechnologies from a critical social science and design perspective. The network has now published its first edited volume: Socio-gerontechnology – Interdisciplinary Critical Studies of Ageing and Technology, which brings together perspectives from ageing studies and science and technology studies. I am have contributed a contribution with Andreas Bischof (Technical University of Chemnitz) which is entitled: Configuring the older adult – How age and ageing are re-configured in gerontechnology design. The chapter will be available open access in due course.
Chapter abstract: Later life has become one of the most prominent topics for the design and development of digital technologies, resulting in the creation of a large body of prototypes and products (gerontechnologies). However, the majority of these efforts suffer from a lack of empirical grounding of their imaginaries of ageing and later life while also failing to involve older adults in design processes in meaningful ways. This chapter reviews how age and ageing can be configured across different instances of the development and deployment of digital technologies. We understand such design processes as configuration practices that co-construct older users and later life. By using the concept of re-con-figuration, we critically reflect about conceptual, ethical and pragmatic challenges of involving older people in design processes.
The Sociolog of the Sciences Yearbook is now online and Open Access. It’s editors Karen Kastenhofer and Susan Molyneux-Hodgson have assembled an interesting collection of 13 contributions across a wide range of technosciences.
My contribution looks at ways in which the concept of “communities of practice” has been appropriated and argues that objects such as templates are not simply a means to share practices in digital communities but rather a means for enacting membership.
My new book is out & open access. It reviews stereotypical (mis-)conceptions about old age & technology (design), and proposes a methodology for more inclusive and participatory public sector innovation: Co-creation.
Here comes a short summary of each of the chapters.
The 6th chapter reports on a project in the city district Bremen Hemelingen. Co-creators defined design requirements and created content for a digital walking guide. The chapter describes different kinds of walking methods such as ideation walks, data walks and user test walks.
The 7th chapter reports on a project in Zaragoza that was facilitated by Zaragoza city council. The focus was on the improvement of an age-friendly city infrastructure. The result is an enhanced map service, which allows (older) citizens to report problems and/or propose improvements
The 8th chapter presents nine learning points from the three co-creation projects. It considers to what extent the openness of a co-creation process impacts on the sustainability of its results and the ways in which co-creation contributes to joint socio-technical future-making.
The final chapter concludes that co-creation processes are highly contingent and dependent on several factors. The learning points identified provide evidence on ways to co-create better, more user-centric public services with and for older adults.
Roland Becker (CEO & founder of JustAddAI) and Dr. Sirko Straube (German Research Institute for Artificial Intelligence – DFKI) invited me to the fourth episode of their podcast Think Reactor to discuss the discriminatory potential of Artificial Intelligence as well as the social and ethical challenges of digital innovation. Other topics they’ve covered so far are: What is AI (episode 1), AI in everyday life (episode 2) and How safe is AI (episode 3). The podcast provides a good introduction to a topic that affects us all in many different ways and also plays an increasingly important role in STS research.
*the podcast is in German.