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Collaborative Social Systems Lab
at Northeastern University
Digital business transformation and the rise of powerful generative AI will have a tremendous impact on the workforce of the future. Future work environments will be characterized by a growing emphasis on remote work and AI. The Collaborative Social Systems Lab, directed by Christoph Riedl, explores how the Future of Work will look like and how we can organize teams, crowds, and human-AI teams to be collectively intelligent.
  Learn about the lab:
  • ​Meet the team
  • Explore our research
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Latest News
08.14.24
How working with AI impacts the collective attention of teams in TechXplore.

06.27.24

Our lab hosts the ACM Collective Intelligence Conference 2024 at Northeastern University.

05.24.23
Brookings policy piece on Workforce Ecosystems and AI covered in Bloomberg

05.05.23
“Your boss is obsessed with productivity without knowing what it means," interview at VOX

02.01.22
“Remote work isn’t the problem. Work is," interview at VOX

More News
​Recent Publications
When Rivalry Backfires: How Individual Skill and Risk of Status Loss Moderate the Effects of Rivarly on Performance. Grad, T., Riedl, C., & Kilduff, G. (2025). Management Science, in press.

How to Use AI to Build Your Company's Collective  Intelligence.
 Riedl, C. (2024). Harvard Business Review, preprint.

Collective Attention in Human-AI Teams. Zvelebilova, J., Savage, S., Riedl, C. (2024). arXiv.

Competition and Collaboration in Crowdsourcing Communities: What happens when peers evaluate each other? Riedl, C., Grad, T., & Lettl, C. (2024). Organization Science, in press.

Cash or Non-Cash? Unveiling Ideators' Incentive Preferences in Crowdsourcing Contests.  Riedl, C., Hutter, K., Füller, J., & Tellis, G. (2024). Journal of Management Information Systems, 41(2), 487-514.

Spontaneous emergence of groups and signaling diversity in dynamic networks.  Fulker, Z., Forber, P., Smead, R., & Riedl, C. (2024). Phys. Rev. E 109, 014309.

Cooperation in the Gig Economy: Insights from Upwork Freelancers. Fulker, Z., & Riedl, C. (2024). Proceedings of the ACM on Human Computer Interaction, 8(CSCW1), 37.

Workforce Ecosystems and AI. Altman, L., Kiron, D. & Riedl, C. (2023). Brookings Institute.

Collective Intelligence in Human-AI Teams: A Bayesian Theory of Mind Approach. Westby, S. & Riedl, C. In Proceedings of the 37th 
AAAI Conference on Artificial Intelligence (2023). arXiv:2208.11660, Github.

Collective attention and collective intelligence: The role of hierarchy and team gender composition. Woolley, A.W., Chow, R., Mayo, A., Riedl, C., Chang, J. W. (2023). Organization Science, 34(3), 1315-1331.
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