IDEAS home Printed from https://ideas.repec.org/a/eee/respol/v53y2024i4s0048733324000349.html
   My bibliography  Save this article

Algorithmic management in scientific research

Author

Listed:
  • Koehler, Maximilian
  • Sauermann, Henry

Abstract

Artificial intelligence (AI) can perform core research tasks such as generating research questions, processing data, and solving problems. We shift the focus from AI as a “worker” to ask whether, how, and when AI can also “manage” human workers who perform such tasks. Focusing on the context of crowd science, we find examples of algorithmic management (AM) in five key functions highlighted in prior organizational literature: task division and task allocation, direction, coordination, motivation, and supporting learning. These applications benefit from the instantaneous, comprehensive, and interactive capabilities of AI, and reflect several more general underlying functions such as matching, clustering, and forecasting. Quantitative comparisons show that projects using AM are larger and more likely to be associated with platforms than projects not using AM, pointing to potentially important contingency factors. We conclude by outlining an agenda for future research on algorithmic management in scientific research.

Suggested Citation

  • Koehler, Maximilian & Sauermann, Henry, 2024. "Algorithmic management in scientific research," Research Policy, Elsevier, vol. 53(4).
    • Handle: RePEc:eee:respol:v:53:y:2024:i:4:s0048733324000349
    DOI: 10.1016/j.respol.2024.104985
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0048733324000349
    Download Restriction: Full text for ScienceDirect subscribers only
    File URL: https://libkey.io/10.1016/j.respol.2024.104985?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    As the access to this document is restricted, you may want to search for a different version of it.

    References listed on IDEAS

    as
    1. Benjamin F. Jones, 2009. "The Burden of Knowledge and the "Death of the Renaissance Man": Is Innovation Getting Harder?," The Review of Economic Studies, Review of Economic Studies Ltd, vol. 76(1), pages 283-317.
    2. Nicholas Bloom & Charles I. Jones & John Van Reenen & Michael Webb, 2020. "Are Ideas Getting Harder to Find?," American Economic Review, American Economic Association, vol. 110(4), pages 1104-1144, April.
    3. Gary S. Becker & Kevin M. Murphy, 1994. "The Division of Labor, Coordination Costs, and Knowledge," NBER Chapters, in: Human Capital: A Theoretical and Empirical Analysis with Special Reference to Education, Third Edition, pages 299-322, National Bureau of Economic Research, Inc.
    4. Gawer, Annabelle, 2014. "Bridging differing perspectives on technological platforms: Toward an integrative framework," Research Policy, Elsevier, vol. 43(7), pages 1239-1249.
    5. Kristina McElheran & J. Frank Li & Erik Brynjolfsson & Zachary Kroff & Emin Dinlersoz & Lucia Foster & Nikolas Zolas, 2024. "AI adoption in America: Who, what, and where," Journal of Economics & Management Strategy, Wiley Blackwell, vol. 33(2), pages 375-415, March.
    6. David H. Autor & Frank Levy & Richard J. Murnane, 2003. "The skill content of recent technological change: an empirical exploration," Proceedings, Federal Reserve Bank of San Francisco, issue Nov.
    7. Abhishek Nagaraj, 2021. "Information Seeding and Knowledge Production in Online Communities: Evidence from OpenStreetMap," Management Science, INFORMS, vol. 67(8), pages 4908-4934, August.
    8. Davide Castelvecchi, 2018. "Particle physicists turn to AI to cope with CERN’s collision deluge," Nature, Nature, vol. 557(7704), pages 147-148, May.
    9. Robert Gibbons, 1998. "Incentives in Organizations," Journal of Economic Perspectives, American Economic Association, vol. 12(4), pages 115-132, Fall.
    10. David H. Autor, 2015. "Why Are There Still So Many Jobs? The History and Future of Workplace Automation," Journal of Economic Perspectives, American Economic Association, vol. 29(3), pages 3-30, Summer.
    11. Maryam Lotfian & Jens Ingensand & Maria Antonia Brovelli, 2021. "The Partnership of Citizen Science and Machine Learning: Benefits, Risks, and Future Challenges for Engagement, Data Collection, and Data Quality," Sustainability, MDPI, vol. 13(14), pages 1-19, July.
    12. William G. Ouchi, 1979. "A Conceptual Framework for the Design of Organizational Control Mechanisms," Management Science, INFORMS, vol. 25(9), pages 833-848, September.
    13. Cohen, Wesley M., 2010. "Fifty Years of Empirical Studies of Innovative Activity and Performance," Handbook of the Economics of Innovation, in: Bronwyn H. Hall & Nathan Rosenberg (ed.), Handbook of the Economics of Innovation, edition 1, volume 1, chapter 0, pages 129-213, Elsevier.
    14. Morgan R. Frank & David Autor & James E. Bessen & Erik Brynjolfsson & Manuel Cebrian & David J. Deming & Maryann Feldman & Matthew Groh & José Lobo & Esteban Moro & Dashun Wang & Hyejin Youn & Iyad Ra, 2019. "Toward understanding the impact of artificial intelligence on labor," Proceedings of the National Academy of Sciences, Proceedings of the National Academy of Sciences, vol. 116(14), pages 6531-6539, April.
    15. Casey Ichniowski & Kathryn Shaw, 2003. "Beyond Incentive Pay: Insiders' Estimates of the Value of Complementary Human Resource Management Practices," Journal of Economic Perspectives, American Economic Association, vol. 17(1), pages 155-180, Winter.
    16. Jillian Grennan & Roni Michaely, 2020. "Artificial Intelligence and High-Skilled Work: Evidence from Analysts," Swiss Finance Institute Research Paper Series 20-84, Swiss Finance Institute.
    17. Haeussler, Carolin & Sauermann, Henry, 2020. "Division of labor in collaborative knowledge production: The role of team size and interdisciplinarity," Research Policy, Elsevier, vol. 49(6).
    18. Walsh, John P. & Lee, You-Na, 2015. "The bureaucratization of science," Research Policy, Elsevier, vol. 44(8), pages 1584-1600.
    19. Linus Dahlander & Lars Frederiksen, 2012. "The Core and Cosmopolitans: A Relational View of Innovation in User Communities," Organization Science, INFORMS, vol. 23(4), pages 988-1007, August.
    20. Erik Brynjolfsson, 2022. "The Turing Trap: The Promise & Peril of Human-Like Artificial Intelligence," Papers 2201.04200, arXiv.org.
    21. Nicholas Bloom & Christos Genakos & Raffaella Sadun & John Van Reenen, 2011. "Management Practices Across Firms and Countries," CEP Discussion Papers dp1109, Centre for Economic Performance, LSE.
    22. Stefano Bianchini & Moritz Müller & Pierre Pelletier, 2022. "Artificial intelligence in science: An emerging general method of invention," Post-Print hal-03958025, HAL.
    23. Henry Sauermann & Paula Stephan, 2013. "Conflicting Logics? A Multidimensional View of Industrial and Academic Science," Organization Science, INFORMS, vol. 24(3), pages 889-909, June.
    24. Scott Stern, 2004. "Do Scientists Pay to Be Scientists?," Management Science, INFORMS, vol. 50(6), pages 835-853, June.
    25. Miric, Milan & Jeppesen, Lars Bo, 2023. "How does competition influence innovative effort within a platform-based ecosystem? Contrasting paid and unpaid contributors," Research Policy, Elsevier, vol. 52(7).
    26. Beck, Susanne & Brasseur, Tiare-Maria & Poetz, Marion & Sauermann, Henry, 2022. "Crowdsourcing research questions in science," Research Policy, Elsevier, vol. 51(4).
    27. Henry Sauermann & Chiara Franzoni & Kourosh Shafi, 2019. "Crowdfunding scientific research: Descriptive insights and correlates of funding success," PLOS ONE, Public Library of Science, vol. 14(1), pages 1-26, January.
    28. Chiara Franzoni & Marion Poetz & Henry Sauermann, 2022. "Crowds, citizens, and science: a multi-dimensional framework and agenda for future research," Industry and Innovation, Taylor & Francis Journals, vol. 29(2), pages 251-284, February.
    29. Wesley M. Cohen & Henry Sauermann & Paula Stephan, 2020. "Not in the Job Description: The Commercial Activities of Academic Scientists and Engineers," Management Science, INFORMS, vol. 66(9), pages 4108-4117, September.
    30. Hanchen Wang & Tianfan Fu & Yuanqi Du & Wenhao Gao & Kexin Huang & Ziming Liu & Payal Chandak & Shengchao Liu & Peter Katwyk & Andreea Deac & Anima Anandkumar & Karianne Bergen & Carla P. Gomes & Shir, 2023. "Scientific discovery in the age of artificial intelligence," Nature, Nature, vol. 620(7972), pages 47-60, August.
    31. Iain M. Cockburn & Rebecca Henderson & Scott Stern, 2018. "The Impact of Artificial Intelligence on Innovation," NBER Working Papers 24449, National Bureau of Economic Research, Inc.
    32. Siliang Tong & Nan Jia & Xueming Luo & Zheng Fang, 2021. "The Janus face of artificial intelligence feedback: Deployment versus disclosure effects on employee performance," Strategic Management Journal, Wiley Blackwell, vol. 42(9), pages 1600-1631, September.
    33. Rocha, Augusto & Brown, Ross & Mawson, Suzanne, 2021. "Capturing conversations in entrepreneurial ecosystems," Research Policy, Elsevier, vol. 50(9).
    34. Franzoni, Chiara & Sauermann, Henry, 2014. "Crowd science: The organization of scientific research in open collaborative projects," Research Policy, Elsevier, vol. 43(1), pages 1-20.
    35. Cardoen, Brecht & Demeulemeester, Erik & Beliën, Jeroen, 2010. "Operating room planning and scheduling: A literature review," European Journal of Operational Research, Elsevier, vol. 201(3), pages 921-932, March.
    36. Shibayama, Sotaro & Baba, Yasunori & Walsh, John P., 2015. "Organizational design of University laboratories: Task allocation and lab performance in Japanese bioscience laboratories," Research Policy, Elsevier, vol. 44(3), pages 610-622.
    37. Yue Maggie Zhou, 2013. "Designing for Complexity: Using Divisions and Hierarchy to Manage Complex Tasks," Organization Science, INFORMS, vol. 24(2), pages 339-355, April.
    38. Hanchen Wang & Tianfan Fu & Yuanqi Du & Wenhao Gao & Kexin Huang & Ziming Liu & Payal Chandak & Shengchao Liu & Peter Katwyk & Andreea Deac & Anima Anandkumar & Karianne Bergen & Carla P. Gomes & Shir, 2023. "Publisher Correction: Scientific discovery in the age of artificial intelligence," Nature, Nature, vol. 621(7978), pages 33-33, September.
    39. Tamay Besiroglu & Nicholas Emery-Xu & Neil Thompson, 2022. "Economic impacts of AI-augmented R&D," Papers 2212.08198, arXiv.org, revised Jan 2023.
    40. Iain M. Cockburn & Rebecca Henderson & Scott Stern, 2018. "The Impact of Artificial Intelligence on Innovation: An Exploratory Analysis," NBER Chapters, in: The Economics of Artificial Intelligence: An Agenda, pages 115-146, National Bureau of Economic Research, Inc.
    41. Link, Albert N. & Swann, Christopher A. & Bozeman, Barry, 2008. "A time allocation study of university faculty," Economics of Education Review, Elsevier, vol. 27(4), pages 363-374, August.
    42. Benjamin L. Hallen & Susan L. Cohen & Christopher B. Bingham, 2020. "Do Accelerators Work? If So, How?," Organization Science, INFORMS, vol. 31(2), pages 378-414, March.
    Full references (including those not matched with items on IDEAS)

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Carolin Haeussler & Henry Sauermann, 2016. "The Division of Labor in Teams: A Conceptual Framework and Application to Collaborations in Science," NBER Working Papers 22241, National Bureau of Economic Research, Inc.
    2. Haeussler, Carolin & Sauermann, Henry, 2020. "Division of labor in collaborative knowledge production: The role of team size and interdisciplinarity," Research Policy, Elsevier, vol. 49(6).
    3. Montobbio, Fabio & Staccioli, Jacopo & Virgillito, Maria Enrica & Vivarelli, Marco, 2022. "Robots and the origin of their labour-saving impact," Technological Forecasting and Social Change, Elsevier, vol. 174(C).
    4. Beck, Susanne & Brasseur, Tiare-Maria & Poetz, Marion & Sauermann, Henry, 2022. "Crowdsourcing research questions in science," Research Policy, Elsevier, vol. 51(4).
    5. Kyle R. Myers & Wei Yang Tham & Jerry Thursby & Marie Thursby & Nina Cohodes & Karim Lakhani & Rachel Mural & Yilun Xu, 2023. "New Facts and Data about Professors and their Research," Papers 2312.01442, arXiv.org.
    6. Hanna Halaburda & Jeffrey Prince & D. Daniel Sokol & Feng Zhu, 2024. "The business revolution: Economy‐wide impacts of artificial intelligence and digital platforms," Journal of Economics & Management Strategy, Wiley Blackwell, vol. 33(2), pages 269-275, March.
    7. Xueyuan Gao & Hua Feng, 2023. "AI-Driven Productivity Gains: Artificial Intelligence and Firm Productivity," Sustainability, MDPI, vol. 15(11), pages 1-21, June.
    8. Azar, José & Alekseeva, Liudmila & Gine, Mireia & Samila, Sampsa & Taska, Bledi, 2020. "The Demand for AI Skills in the Labor Market," CEPR Discussion Papers 14320, C.E.P.R. Discussion Papers.
    9. Gries, Thomas & Naude, Wim, 2018. "Artificial intelligence, jobs, inequality and productivity: Does aggregate demand matter?," MERIT Working Papers 2018-047, United Nations University - Maastricht Economic and Social Research Institute on Innovation and Technology (MERIT).
    10. Bianchini, Stefano & Müller, Moritz & Pelletier, Pierre, 2022. "Artificial intelligence in science: An emerging general method of invention," Research Policy, Elsevier, vol. 51(10).
    11. Giacomo Damioli & Vincent Van Roy & Daniel Vertesy & Marco Vivarelli, 2024. "AI as a new emerging technological paradigm: evidence from global patenting," DISCE - Quaderni del Dipartimento di Politica Economica dipe0038, Università Cattolica del Sacro Cuore, Dipartimenti e Istituti di Scienze Economiche (DISCE).
    12. Lynn Wu & Bowen Lou & Lorin Hitt, 2019. "Data Analytics Supports Decentralized Innovation," Management Science, INFORMS, vol. 65(10), pages 4863-4877, October.
    13. Moshe A. Barach & Aseem Kaul & Ming D. Leung & Sibo Lu, 2019. "Strategic Redundancy in the Use of Big Data: Evidence from a Two-Sided Labor Market," Strategy Science, INFORMS, vol. 4(4), pages 298-322, December.
    14. Damioli, Giacomo & Van Roy, Vincent & Vertesy, Daniel & Vivarelli, Marco, 2024. "Is Artificial Intelligence Generating a New Paradigm? Evidence from the Emerging Phase," IZA Discussion Papers 17183, Institute of Labor Economics (IZA).
    15. Prithwiraj Choudhury & Evan Starr & Rajshree Agarwal, 2020. "Machine learning and human capital complementarities: Experimental evidence on bias mitigation," Strategic Management Journal, Wiley Blackwell, vol. 41(8), pages 1381-1411, August.
    16. Hoekman, Jarno & Rake, Bastian, 2024. "Geography of authorship: How geography shapes authorship attribution in big team science," Research Policy, Elsevier, vol. 53(2).
    17. Christoph Riedl & Eric Bogert, 2024. "Effects of AI Feedback on Learning, the Skill Gap, and Intellectual Diversity," Papers 2409.18660, arXiv.org.
    18. Balland, Pierre-Alexandre & Broekel, Tom & Diodato, Dario & Giuliani, Elisa & Hausmann, Ricardo & O'Clery, Neave & Rigby, David, 2022. "Reprint of The new paradigm of economic complexity," Research Policy, Elsevier, vol. 51(8).
    19. Spyros Arvanitis & Florian Seliger & Tobias Stucki, 2013. "The Relative Importance of Human Resource Management Practices for a Firm's Innovation Performance," KOF Working papers 13-341, KOF Swiss Economic Institute, ETH Zurich.
    20. David J. Deming, 2017. "The Growing Importance of Social Skills in the Labor Market," The Quarterly Journal of Economics, President and Fellows of Harvard College, vol. 132(4), pages 1593-1640.

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:eee:respol:v:53:y:2024:i:4:s0048733324000349. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Catherine Liu (email available below). General contact details of provider: http://www.elsevier.com/locate/respol .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.