The growing availability of large-scale datasets, combined with computational methods from network science, artificial intelligence, natural language processing, and related fields, has opened new possibilities for studying and understanding social phenomena. This interdisciplinary area, often called Social Data Science or Computational Social Science, is increasingly relevant to questions at the heart of the D3A community: how data and AI can be used responsibly, critically, and for the public good.

Building on a successful session at last year’s D3A, which attracted around 40 participants and generated lively discussion across academia, policy, industry, and civil society, this second edition will continue the conversation on the future of Social Data Science in Denmark and beyond. The workshop will bring together researchers, policymakers, data scientists, and practitioners to discuss how computational methods can help address societal challenges while also raising important ethical, democratic, and governance questions.

This year’s focus is on public-interest applications of social data science, including humanitarian uses of data, AI’s influence on democracy and policy, and the changing role of AI in science and research. 

Programme

The session will follow a workshop-style format, combining short invited talks with facilitated discussion and collective synthesis. The goal is to create an interactive forum where participants from academia, policy, industry, and civil society can reflect on the future of Social Data Science and AI for the public good.

Welcome and framing (5 minutes)
The organizers will introduce the aims of the session, connect it to last year’s D3A workshop, and frame the key questions for discussion.

Section 1 – Invited presentations (40 minutes)
Four invited speakers will each give a 10-minute presentation introducing a different perspective on the workshop topic. The presentations will focus on key open questions, ethical dilemmas, and practical challenges related to humanitarian data science, AI and democracy, AI in science and research, and AI policy.

Section 2 – Facilitated audience discussion (30 minutes)
The organizers will facilitate a broad discussion with the audience, structured around the themes raised by the speakers. Participants will be invited to reflect on the role Social Data Science can play in Denmark and beyond, and to identify urgent societal, ethical, and research challenges for the field.

Section 3 – Collective synthesis and next steps (15 minutes)
The final part of the session will synthesize the discussion and jointly outline the key points for a short community document or position paper on the state and future priorities of Social Data Science.

Speakers’ list

• AI for Public Good: Lessons from Non-profit organizations
  Paddy Brock, Senior Data Scientist, World Bank–UNHCR Joint Data Center on Forced Displacement (accepted)
• AI in Science & Research
  Roberta Sinatra, Professor, Copenhagen Center for Social Data Science & IT University of Copenhagen (tentatively accepted)
• AI & Democracy
  Gregory Eady, Associate Professor, Department of Political Science, University of Copenhagen (invited)
• AI & Policy
  Lucie Aimee-Kaffee, EU Policy Lead & Applied Researcher, Hugging Face (invited)

Level

Intermediate: For attendees who have basic understanding or some experience with the subject but are not yet advanced.

Organizers

• Arianna Pera, Postdoc, SODAS, University of Copenhagen and IT University of Copenhagen (ITU) (Session Co-lead)
• Anders Weile Larsen, PhD Student, ITU and P1
• Chiara Zappalá, Postdoc, SODAS, University of Copenhagen and ITU
• Vedran Sekara, Associate Professor, ITU and P1
• Akhil Arora, Assistant Professor, Aarhus University, SODAS, and P1 (Session Co-lead)