Co-Learning with Data: A Workshop on Critical Data and Health Governance
Date: May 19 and 26, 2025
Location: College of Public Health, National Taiwan University
Exploring the Intersection of AI, Algorithms, Data, and Health Governance
In the wake of global public health crises, the increasing reliance on AI, algorithms, and data-driven governance has transformed the ways health policies are designed, implemented, and experienced. From digital contact tracing to algorithmic health risk assessments, these technologies have enabled and constrained compliance, trust, and ethics between governments, healthcare systems, and populations. As we move into a post-pandemic, datafied society, we must critically examine how data shapes health governance and practices, and how critical data perspectives can offer new insights into the future of health interventions.
This workshop seeks to bring together scholars engaged in comparative/critical analyses of digital health interventions to explore how national contexts shape the rollout, adoption, and consequences of these technologies. Additionally, we aim to examine how digital health data is used to govern, regulate, and mediate human/nonhuman relationships, agency, and intimacy.
Beyond political and regulatory implications, another pressing issue demands further scrutiny:
- How does AI generate algorithms that shape human/nonhuman interactions in healthcare, including companionship, therapy, and mental health interventions?
- What are the ethical, social, and policy implications of AI-driven decision-making in health governance?
We invite contributions that address theories, methods, policies, and teaching concerning the digital governance of health, broadly conceived. The workshop will engage perspectives from governments, big-tech companies, and NGOs to deepen international collaboration and foster interdisciplinary dialogue at the intersection of global health, digitization, and citizen science.
Workshop Structure
This two-day workshop will be divided into two parts:
- Morning Session (19 May): Idea Exchange & Research Formulation
- Participants will share ongoing research or ideas for journal articles on digital health governance, AI in healthcare, and algorithmic regulation, as well as research methodologies for such topics.
- Or, any critical take on the production, disposal, circulation, distribution, consumption, use, misuse and abuse of data.
- Afternoon Session (26 May): Pedagogical Practices in Critical Data Studies
- Discussions on incorporating AI and data studies into classroom teaching and thesis writing.
- Strategies for collaborative teaching with AI in higher education.
- Or, any methods and tips for teaching critical perspectives and approaches in health-related courses.
Who Should Apply?
We welcome scholars at all career stages, particularly early-career researchers and graduate students who wish to engage with critical perspectives on AI, data, and health governance. This is an opportunity to build sustainable partnerships among social scientists and generate practical policy recommendations for future health crises.
Throughout the workshop, Dr. Stephen Roberts, Lecturer in Global Health at the Institute for Global Health, UCL, and Dr. Gabrielle Samuel, Lecturer in Environmental Justice and Health at the Department of Global Health and Social Medicine, KCL, will serve as a key discussant, facilitating a dynamic and critical conversation among participants. His expertise in global health governance, AI ethics, and interdisciplinary methodologies will help guide discussions toward collaborative opportunities.
Submission Guidelines
- Abstract (300 words max) outlining your research topic and its relevance to the workshop themes.
- Short bio (150 words max) including your institutional affiliation.
Deadline for Submission: April 30, 2025
Submit to: poyaoh@g.ntu.edu.tw
