Christoph Riedl

Professor, Supply Chain & Information Management
Campus location Boston
Email [email protected]
Phone 617.373.5739

Selected publications

  • Riedl, C. & Rosas, F.E. (2026). Claims of AI emergence should be grounded
    in information decomposition. Advances in Neural Information Processing Systems (NeurIPS'26), volume 39. SPOTLIGHT paper.
  • Riedl, C. (2026). Emergent coordination in multi-agent language models. International Conference on Learning Representations, pages 120776-120799.
  • Prakash, N., Shapira, N., Sharma, A.S., Riedl, C., Belinkov, Y., Shaham, T.R., Bau, D., Geiger A.
    (2026). Language models use lookbacks to track beliefs. International Conference on Learning Representations.
  • Riedl, C., Savage, S., & Zvelebilova, J. (2026). “Cognitive Spillover in Human-AI Teams”. ACM
    Transactions on Computer-Human Interaction (TOCHI), 33(3), Article 32.
  • Urmi, T., Pant, B., Dewey, G., Quintana-Mathé, A., Lang, I., Druckman, J.N., Ognyanova, K.,
    Baum, M., Perlis, R.H., Riedl, C., Lazer, D., Santillana, M. (2025). “Characterizing
    Population-level Changes in Human Behavior during the COVID-19 Pandemic in the United
    States.” Proceedings of the National Academy of Sciences (PNAS), 122 (37) e2500655122.
  • Lee, J., Lazer, D., & Riedl, C.* (2025). “Complex Contagion in Social Networks: Causal Evidence
    from a Country-Scale Field Experiment.” Sociological Science, 12, 685-714.
  • Wan, A., Riedl, C., & Lazer, D. (2025). “Diffusion of Complex Contagions is Shaped by a Tradeoff Between Reach and Reinforcement.” Proceedings of the National Academy of Sciences (PNAS), 122(28) e2422892122.
  • Grad, T., Riedl, C., & Kilduff, G. (2025). “When Rivalry Backfires: How Individual Skill and Risk of Status Loss Moderate the Effects of Rivarly on Performance.” Management Science, in press.
  • Riedl, C. (2024). “How to Use AI to Build Your Company's Collective Intelligence.” Harvard Business Review, October, preprint.
  • Riedl, C., Grad, T., & Lettl, C. (2024). “Competition and Collaboration in Crowdsourcing Communities: What happens when peers evaluate each other?” Organization Science, 35(6), 1957-2332.
  • Riedl, C., Hutter, K., Füller, J., Tellis, G. (2024). “Cash or Non-Cash? Unveiling Ideators' Incentive Preferences in Crowdsourcing Contests,” Journal of Management Information Systems, 41(2), 487-514.
  • Fulker, Z., Riedl, C. (2024). “Cooperation in the Gig Economy: Insights from Upwork Freelancers,” Proceedings of the ACM on Human Computer Interaction, 8(CSCW1), 37.
  • Kiron, D., Altman, E.J., Riedl, C. (2023). “Workforce Ecosystems and AI,” Brookings Institute, in press.
  • Westby, S. & Riedl, C. (2023). Collective Intelligence in Human-AI Teams: A Bayesian Theory of Mind Approach.  In Proceedings of the 37th AAAI Conference on Artificial Intelligence (2023). arXiv:2208.11660.
  • Woolley, A.W., Chow, R., Mayo, A., Riedl, C., Chang, J. W. (2022). “Collective attention and collective intelligence: The role of hierarchy and team gender composition,” Organization Science, 34(3), 1315–1331.
  • Riedl, C., Malone, T.W., Woolley, A.W. (2021). “The Collective Intelligence of Remote Teams,” MIT Sloan Management Review, October, 2021, article.
  • Riedl, C., Kim, Y.J., Gupta, P., Malone, T.W., Woolley, A.W. (2021). “Quantifying Collective Intelligence in Human Groups,” Proceedings of the National Academy of Sciences (PNAS), 118 (21) e2005737118.
  • Balietti, S., Riedl, C. (2021). “Incentives, competition, and inequality in markets for creative production,” Research Policy, 50(4), 104212.
  • Fulker, Z., Forber, P., Smead, R., Riedl, C. (2021). “Spite is Contagious in Dynamic Networks,” Nature Communications, 12(260).
  • Riedl, C., Woolley, A. (2020). “Successful Remote Teams Communicate in Bursts,” Harvard Business Review, October, 2020.
  • Fraiberger, S., Sinatra, R., Resch, M., Riedl, C., Barabási, A.L. (2018). “Quantifying Reputation and Success in Art” (shared last author with ALB). Science, 362(6416), 825-829.
  • Riedl, C., Seidel, V. (2018). “Learning from Mixed Signals in Online Innovation Communities,” Organization Science, 29(6), 1010-1032.
  • Riedl,* C., Woolley, A.W. (2017). “Teams vs. Crowds: A Field Test of the Relative Contribution of Incentives, Member Ability, and Emergent Collaboration to Crowd-Based Problem Solving Performance,” Academy of Management Discoveries, 3(4), 382-403.
  • Boudreau, K., Guinan, E., Lakhani, K., Riedl, C. (2016). “Looking Across and Looking Beyond the Knowledge Frontier: Intellectual Distance and Resource Allocation in Science,” Management Science, 62(10), 2765-2783.
  • Blohm, I., Riedl, C., Füller, J., Leimeister, J.M. (2016). “Rate or Trade? Identifying Winning Ideas in Open Idea Sourcing,” Information Systems Research, 27(1), 27-48.

Selected presentations

  • “Collective Intelligence in Human-AI Teams: A Bayesian Theory of Mind Approach,” Harvard Business School, invited talk, February, 2023.
  • “Video Moves You,” invited talk CODE@MIT, Sloan School of Business, Cambridge, MA November 10th 2023.
  • “How Human-Agent Teams Will Revolutionize the Future of Work,” 2020 INGRoup conference, Seattle, WA.
  • Invited talk “Avoiding the Bullies: How High-Ability Agents Promote Cooperation in Social Networks”, IMT Lucca, March 12th, 2020.

Research & teaching interests

Riedl's research interests are in collective intelligence and human-AI interaction. Riedl teaches courses on AI and Machine Learning, Digital Business Transformation, and Network Economics.

Services to the profession

  • Member Editorial Review Board for Academy of Management Discoveries.
  • Core faculty, Network Science Institute.
  • Core faculty, Center for Digital Humanities & Computational Social Science (NUlab)
  • Visiting Fellow, Institute for Quantitative Social Science (IQSS), Harvard University

Awards & recognition

  • Spotlight paper at NeurIPS'26 (< 2% of all submissions).
  • James Coleman Paper Award of the American Sociological Association, 2026.
  • Research Methods Prize, Strategic Management Society, finalist, 2025.
  • Walsh Professorship (D'Amore-McKim School of Business, 2021-2023)
  • Research grant over $1,500,000 by Army Research Lab (ARL), 2019-2022
  • INFORMS TIMES Best Paper Award, runner-up, 2021
  • Best Teacher Award (D'Amore-McKim School of Business, 2018)
  • Best Paper Award of the Academy of Management Discoveries, finalist 2018

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