Confronting Data through Design Methods – Speculating with Generative AI (GAI)

Content

This course is aimed at PhD students, researching within the fields of Computer-Supported Cooperative Work (CSCW), Human-Computer Interaction (HCI), Science- and Technology Studies (STS), Participatory Design (PD) & Critical Data Studies, but the course is open to PhD students from all areas of work- and design studies. The course is given as a mix of hands-on exercises with GenAI tools and lectures and seminars on speculative design and critical responses to GenAI interwoven throughout the 3-day course. In addition, the students engage in peer-feedback as part of the development of their essays, which focus on applying GenAI in relation to their own PhD project.

The course explores how we can use design methods to probe, construct, question, and critique different types of data. The goal of the course is that participants are introduced to both theoretical, concrete, and practical knowledge about different modes of doing research through design as well as gaining an overview of current debates regarding how data-driven technologies can be made ethical and responsible.

This year’s course focus on applying GenAI for data analysis within this area of research.

The rapid introduction of GAI into organizational work through formal digital transformation initiatives as well as informal adoption of freely available tools is quickly reconfiguring the conditions of collaborative organizing and the means through which we speculate futures labor and society. How do we approach, for example, which practices and skills we automate or retain as requiring human experience? What futures are rendered more realizable through AI-enhanced data analysis methods and techniques? How is this moment of GAI hype and increased accessibility impacting forms of expertise, authority, and accountability in data work?

While GAI is entering data work for its expediency and utility, it is not always held accountable as a method of speculation and design even as it shapes the methods and tools through which we develop future scenarios with and through data analysis. Adopting a design perspective, we will also attend to the people in each case who are the subjects of data and have a stake in design outcomes of working with large-scale data, accessible for them with GAI.

Participants will obtain concrete skills in designing participatory “scenario-based workshops” utilizing GenAI tools, including DALL-E and ChatGPT. Furthermore, the course is set up to facilitate discussions and to generate ideas relating to the participants own PhD projects.

Working hands-on with GAI in a speculative design and research through design approach, will enable participants to enter into debates over responsible use of AI and other data-driven technologies through concrete application of these tools. By applying speculative methods to consider future scenarios of organizing and collaborative work students will problematize and concretize opportunities for designing/using data-driven technologies ethically and responsibly in their own cases.

The course is offered as a collaboration between DIREC, ITU and UCPH.  

Accessibility
If any participants have any special needs in order to attend the course, they are kindly requested to contact the organizers and we will try to accommodate such needs.

Preparation:
In order to prepare for the course, the course participants need to:

(1) Read the literature from the reading list prior to the course (the course curriculum will be distributed after enrollment in the course). Download free version of DALL-E and ChatGPT.

(2) Submit their essays before May 15 2024 (2-4 pages) reflecting on the question: “How might combining methods from speculative design and GenAI help you think about your data in new ways?

The readings and the essays are a way to reflect upon the topics prior to the course. The essays will also help us to identify participants interests/considerations prior to the course. Furthermore, this preparatory work aims to support their active participation throughout the course.

Learning outcome

Knowledge:
• Knowledge of methods for speculative design
• Knowledge of GenAI tools, limitations and possibilities

Skills:
• Skill 1, application of GenAI tools for research (DALL-E, ChatGPT)
• Skill 2, design of scenario-based workshops with GenAI

Competences:
• Competence 1, Reflect on prompting with GenAI tools for the purpose of speculative design.
• Competence 2, Design participatory scenario workshops with GenAI tools.

Lecturers

Naja Holten Møller is Associate Professor at the University of Copenhagen (UCPH), Department of Computer Science and founder and organizer of the Confronting Data Co-lab (www.confrontingdata.dk). Her research explores how data-driven technologies introduce continuous forms of change for bureaucracies and public decision-, but also for citizens and others who engage with these work processes. She was part of the expert group initiated by the Danish Ministry of Digitalization and public- and private partners that analyzed possibilities and challenges of using language models in the Danish public sector.

Marisa Leavitt Cohn is an Associate Professor in the Technologies in Practice Research Group at the IT University of Copenhagen where she directs ETHOS (ethos.itu.dk), a feminist methods lab working with emergent intersections of ethnographic and digital methods to explore computational culture and the politics of data. Cohn’s research is positioned within Science and Technology Studies (STS), Software Studies, Human Computer Interaction. She applies ethnography and research-through-design to examine software maintenance labor, infrastructural decay, and temporal politics of technological change. She is particularly interested in how temporal narratives of evolvability, emergence, decline, and obsolescence shape co-speculative approaches to designing computational futures.

Christopher Le Dantec is Full Professor at Northeastern University’s with a joint appointment at Computer Sciences and College of Art, Media, and Design. His research is focused on digital civics, an area of innovation that emerges at the intersection of Computer Science, Participatory Design, Digital Democracy, and Smart Cities. Together with students and community partners, he works to co-create new interactive digital technologies that assert identity, that enable new forms of civic participation through environmental sensing, and that respect community experiences, beliefs, and desires.

Christian Villum (https://autofunk.dk/about/) is an independent researcher at Autofunk. Driven by a keen interest in examining new boundaries for the application of digital technology, his work has two trajectories. On the one hand, exploring new technological currents and their impact on society, and on the other hand pushing the boundaries of digital art and culture, in particular in the electronic music realm. Recently, Villum has taken on GenAI as a medium for how he engages with the design field to co-create scenarios for imagining alternative future(s).

Mark Friis Hau is a postdoctoral researcher at the Department of Sociology, Research Center for Industrial Relations at the University of Copenhagen, where he leads the network at KU exploring the possibilities of using GenAI in teaching. As part of this work, he has developed and tested a “Socratic bot” that can ask guiding questions, and is experimenting with new ways to support students learning – but also people in general – by strengthening their “prompting” skills.

Thomas T Hildebrandt is Full Professor at the University of Copenhagen (UCPH), Department of Computer Science and an active participant in DIREC – the Digital Research Center Denmark. He engages in the public discussion of GenAI from the perspective of software engineering and how we can ensure reliable and flexible software systems that are suitable for the people who use them, including the digitization of legal, workflow and business process information systems.

Remarks

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