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.

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