Computational Social Science Lab
The Computational Social Science Lab is an interdisciplinary research group within the Department of Digitalization at Copenhagen Business School. We use computational methods to study socio-technical systems and build digital tools for business and society.
News from the lab.
[20 November 2024] Sine Zambach delivers a keynote at the conference on Exploring Teaching for Active Learning in Engineering Education (ETALEE)
Sine Zambach presents on how generative AI will impact the education system and how to safeguard student learning competencies.
[9 November 2024] CSSL researcher contributes an article for Børsen
Sine Zambach co-authors an article in Børsen arguing that fear is an unconstructive way to meet the challenges and possibilities of generative AI.
[30 October 2024] New paper published in Scientific Reports
Jason Burton and colleagues examine public attitudes towards social media field experiments, highlighting the need for ethical considerations in online research.
[22 October 2024] CSSL represented at the Danish Digitalization, Data Science and AI (D3A) conference
Sine Zambach delivers a talk as part of the workshop on ‘How should we teach data science to the future generation? Reflections on the role of data science in high schools.’
[2 October 2024] CSSL represented at the 8th Conference on Digital Learning Technology at DTU Compute
Sine Zambach delivers a talk on ‘Experiences with teaching generative AI.’
[20 September 2024] New paper published in Nature Human Behaviour
A collaboration of 28 researchers led by Jason Burton synthesize their perspectives on ‘How large language models can reshape collective intelligence.’
[13 September 2024] Jason Burton speaks at the European Association for Decision Making (EADM) summer school
Jason Burton delivers a talk, ‘Large language models x collective intelligence,’ at the summer school on LLMs in Behavioral Science at the Max Planck Institute for Human Development.
[22 July 2024] New book on ‘AI i Gymnasiet’ by Sine Zambach
Sine Zambach provides a practical guide on the use of artificial intelligence in Danish high schools, from the perspective of a researcher, publisher, and, most importantly, a teacher.
[18 July 2024] CSSL represented at the International Conference on Computational Social Science (IC2S2) at the University of Pennsylvania
Jason Burton delivers a talk on how ‘Simple changes to content curation algorithms affect the beliefs people form in a collaborative filtering experiment’ and a talk on computational modelling of ‘Opinion averaging versus argument exchange.’
[22 June 2024] Sine Zambach gives a bonfire speech
Sine Zambach speaks about the human relationship with AI at the Copenhagen University Association’s Skt. Hans evening.
[1 June 2024] New project receives funding from the Carlsberg Foundation
The project, ‘Artificial compositions — What happens to the authentic and auratic when AI interacts with original art?,’ led by Sine Zambach, has been awarded a 2024-25 Carlsberg Mindelegat grant.
[2 May 2024] Sine Zambach appears on the DR1 radio show ‘Prompt’
Sine Zambach discusses the social effects of generative AI on Danish radio, offering tips for parents dealing with AI at home.
[18 April 2024] New paper published in Collective Intelligence
Jason Burton and colleagues demonstrate the potential of using rewiring algorithms to promote collective intelligence in ‘Algorithmically Mediating Communication to Enhance Collective Decision-Making in Online Social Networks.’
[31 January 2024] New preprint on ‘An Early Categorization of Prompt Injection Attacks on Large Language Models’
Team of researchers led by CBS alumnus, Sippo Rossi, including Raghava Rao Mukkamala, provide an overview of the emergent threats of prompt injection to increase awareness of vulnerabilities and guide future research.
[1 January 2024] New research on preserving user privacy in mixed reality presented at the Hawaii International Conference on System Sciences (HICSS)
CSSL researchers Somnath Mazumdar, Abid Hussain, and Raghava Rao Mukkamala propose a new framework to improve data protection through blockchain to let users know how their data is accessed.