Thoughts from the PIT: Introducing Lea Stöter

I have recently visited my first academic conference – the closing event of a project titled “Shaping AI” – and on the train journey back, after two days of presentations, soaking up knowledge, attempts at networking, and questions-turning-monologues, I left with one question: “Can this someday be me up there on the stage sharing my passion?”

And with that, let me introduce myself: I’m Lea Stöter, a first-year PhD candidate at PIT – the department for Participatory IT Design at Kassel University. I was asked to write a brief post introducing myself as a new member of the team, so in what follows I provide a couple of paragraphs on my background and research interests.

I started my educational odyssey seeing myself as an organizer. In the bachelor’s program “Creative Business and Media Management” at NHL Stenden University of Applied Science in Leeuwarden (NL), I started with a practical education in writing marketing plans, planning media productions, doing audience research, and overall dipping my toes into the world of media studies for the first time. But most importantly, during my work with the Creative Business student council, I discovered about myself that I liked to learn, and I liked to help other people learn and understand things.

After a rather unsuccessful detour into the corporate world, I quickly returned to an educational environment building on the things I enjoyed during my first study. This is how I ended up at Utrecht University. While helping students in vocational education learn English and German in Leeuwarden, I learned about forms of green media, how to analyse debates on online platforms, how to turn a Let’s Play into an academic assignment, and how to write philosophical essays in Utrecht. To be fair, it wasn’t an easy switch: To make the move from an applied science university (in short, hbo) to a research university (in short, wo) in the Netherlands, the university can require you to do a premaster program to prepare you for an academic way of working. Nevertheless, this slight detour gave me the opportunity to work at the Data School that investigates how big data and AI affect citizenship and democracy, and how public debates are carried out on various social media platforms.

My academic research trajectory started by following the data school practicum – a course focusing on using digital tools for online research in an ethical manner – and later by being offered an internship on the project “Expertise in the Platform Society.” Here I experienced working on research projects and academic processes for the first time and contributed for the first time as well.

Having discovered a passion for learning, understanding concepts and how their relate to each other, and helping others along this path, I continued to pursue a master’s degree “New Media and Digital Culture.” Specializing on the platforms/data trajectory, I started asking questions about what authorship means in regard to procedurally generated media forms, about self-tracking apps and embodiment, and about the ethical implications of the algorithm usage of public broadcasters. My educational journey in the Netherlands culminated in a master’s thesis focusing on how platform affordances shape political debates in online environments.  Here I investigated how on platforms like Twitter the dynamics of exchange between politicians and citizens are shifting through visibility and spreadability affordances.

Coming from these areas of inquiries – expertise, authorship, ethics, online debates, and more – I am now interested in the broader areas of datafication and algorithmization of societal and cultural processes, drawing mostly on perspectives from media, software, and critical data studies, as well as feminist theory. Specifically, I would like to ask questions about the use of digital, algorithmized, or AI-driven tools in knowledge production processes: How do researchers co-produce knowledge with the tools they use? How do AI-driven tools impact our idea of authorship? How are these tools changing our methodological understandings and processes within research endeavours? And how are these “research media” understood in different disciplines?   

Consequently, I ended up in Kassel and specifically at PIT, which I see both as an opportunity and a challenge. As a humanities scholar (if I dare call myself that), I am entering uncharted territory at the Faculty of Electrical Engineering and Computer Science. At the same time, I am encouraged by the need for interdisciplinary and cross-disciplinary perspectives in contemporary digital landscapes.  I therefore hope to both learn from existing computer science and HCI expertise at PIT as well as bring ideas and ways of inquiry from the Humanities and media studies to the group.

I am at the start of my research trajectory, and I look forward to establishing interesting cross-disciplinary links and contribute to the vibrant research environment here. For collaboration on research and projects in areas such as the social and cultural dimensions of algorithm use, or epistemic software and knowledge production, please feel free to contact me.

* The image for this post has been generated with AI, using the following prompt: “A portrait of an androgynous white woman in her mid-twenties. She has short brown curly hair and an undercut. She has grey-blue eyes, a round face, and a small nose. She has dark circles under her eyes. Her eyebrows are not visible. She is a researcher at a university“.