research-article

Re-incentivizing discovery: mechanisms for partial-progress sharing in research

Authors:

Siddhartha Banerjee,

Anilesh Kollagunta KrishnaswamyAuthors Info & Claims

EC '14: Proceedings of the fifteenth ACM conference on Economics and computation

Pages 149 - 166

https://doi.org/10.1145/2600057.2602888

Published: 01 June 2014 Publication History

Abstract

An essential primitive for an efficient research ecosystem is partial-progress sharing (PPS) -- whereby a researcher shares information immediately upon making a breakthrough. This helps prevent duplication of work; however there is evidence that existing reward structures in research discourage partial-progress sharing. Ensuring PPS is especially important for new online collaborative-research platforms, which involve many researchers working on large, multi-stage problems.

We study the problem of incentivizing information-sharing in research, under a stylized model: non-identical agents work independently on subtasks of a large project, with dependencies between subtasks captured via an acyclic subtask-network. Each subtask carries a reward, given to the first agent who publicly shares its solution. Agents can choose which subtasks to work on, and more importantly, when to reveal solutions to completed subtasks. Under this model, we uncover the strategic rationale behind certain anecdotal phenomena. Moreover, for any acyclic subtask-network, and under a general model of agent-subtask completion times, we give sufficient conditions that ensure PPS is incentive-compatible for all agents.

One surprising finding is that rewards which are approximately proportional to perceived task-difficulties, are sufficient to ensure PPS in all acyclic subtask-networks. The fact that there is no tension between local fairness and global information-sharing in multi-stage projects is encouraging, as it suggests practical mechanisms for real-world settings. Finally, we also characterize the efficiency of PPS -- we show that PPS is necessary, and in many cases, sufficient, to ensure a high rate of progress in research.

References

[1]

ACKERMAN, M. AND BRÂNZEI, S. 2012. Research quality, fairness, and authorship order. arXiv preprint arXiv:1208.3391.

[2]

BACHRACH, Y., SYRGKANIS, V., AND VOJNOVIC, M. 2013. Incentives and efficiency in uncertain collaborative environments. arXiv preprint arXiv:1308.0990.

[3]

BANERJEE, S., GOEL, A., AND KRISHNASWAMY, A. K. 2014. Re-incentivizing discovery: Mechanisms for partial-progress sharing in research. Tech. rep., Stanford University. available on ArXiv.

[4]

BOUDREAU, K. AND LAKHANI, K. R. 2013a. Cumulative innovation & open disclosure of intermediate results: Evidence from a policy experiment in bioinformatics. Working paper.

[5]

BOUDREAU, K. AND LAKHANI, K. R. 2013b. How disclosure policies impact search in open innovation. Working paper.

[6]

CHAWLA, S., HARTLINE, J. D., AND SIVAN, B. 2012. Optimal crowdsourcing contests. In Proceedings of the Twenty-Third Annual ACM-SIAM Symposium on Discrete Algorithms. SIAM, 856--868.

Digital Library

[7]

CRANSHAW, J. AND KITTUR, A. 2011. The polymath project: lessons from a successful online collaboration in mathematics. In Proceedings of the SIGCHI Conference on Human Factors in Computing Systems. ACM, 1865--1874.

Digital Library

[8]

GHOSH, A. AND HUMMEL, P. 2012. Implementing optimal outcomes in social computing: a game-theoretic approach. In Proceedings of the 21st international conference on World Wide Web. ACM, 539--548.

Digital Library

[9]

GHOSH, A. AND KLEINBERG, J. 2013. Incentivizing participation in online forums for education. In Proceedings of the fourteenth ACM conference on Electronic commerce. ACM, 525--542.

Digital Library

[10]

GOWERS, T. 2013. The polymath blog.

[11]

HARRIS, C. AND VICKERS, J. 1987. Racing with uncertainty. The Review of Economic Studies 54, 1, 1--21.

[12]

JAIN, S., CHEN, Y., AND PARKES, D. C. 2012. Designing incentives for online question and-answer forums. Games and Economic Behavior.

[13]

KLEINBERG, J. AND OREN, S. 2011. Mechanisms for (mis) allocating scientific credit. In Proceedings of the 43rd annual ACM Symposium on Theory of Computing. ACM, 529--538.

Digital Library

[14]

KONRAD, K. A. 2009. Strategy and dynamics in contests. OUP Catalogue.

[15]

NIELSEN, M. 2011. Reinventing discovery: the new era of networked science. Princeton University Press.

Digital Library

[16]

NOSEK, B. A. AND BAR-ANAN, Y. 2012. Scientific utopia: I. opening scientific communication. Psychological Inquiry 23, 3, 217--243.

[17]

STREVENS, M. 2003. The role of the priority rule in science. The Journal of Philosophy 100, 2, 55--79.

[18]

STREVENS, M. 2013. Herding and the quest for credit. Journal of Economic Methodology 20, 1, 19--34.

[19]

TAYLOR, C. R. 1995. Digging for golden carrots: an analysis of research tournaments. The American Economic Review, 872--890.

Cited By

Carré SGabriel FHongler CLacerda GCapano G(2024)Smart Proofs via Recursive Information Gathering: Decentralized Refereeing by Smart ContractsDistributed Ledger Technologies: Research and Practice10.1145/35952983:1(1-19)Online publication date: 18-Mar-2024
https://dl.acm.org/doi/10.1145/3595298
Xing Lim JMonnot BPiliouras G(2022)Blockchain-based Mechanism Design for Collaborative Mathematical Research2022 IEEE International Conference on Blockchain and Cryptocurrency (ICBC)10.1109/ICBC54727.2022.9805513(1-9)Online publication date: 2-May-2022
https://doi.org/10.1109/ICBC54727.2022.9805513
Kleinberg JOren S(2022)Mechanisms for (Mis)allocating Scientific CreditAlgorithmica10.1007/s00453-021-00902-yOnline publication date: 6-Jan-2022
https://doi.org/10.1007/s00453-021-00902-y
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Index Terms

Re-incentivizing discovery: mechanisms for partial-progress sharing in research
1. Information systems
  1. Information systems applications

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cover image ACM Conferences

EC '14: Proceedings of the fifteenth ACM conference on Economics and computation

June 2014

1028 pages

ISBN:9781450325653

DOI:10.1145/2600057

General Chair:
Moshe Babaioff
Microsoft Research
,
Program Chairs:
Vincent Conitzer
Duke University
,
David Easley
Cornell University

Copyright © 2014 ACM.

Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than the author(s) must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from [email protected].

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New York, NY, United States

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Published: 01 June 2014

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EC '14: ACM Conference on Economics and Computation

June 8 - 12, 2014

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Cited By

Carré SGabriel FHongler CLacerda GCapano G(2024)Smart Proofs via Recursive Information Gathering: Decentralized Refereeing by Smart ContractsDistributed Ledger Technologies: Research and Practice10.1145/35952983:1(1-19)Online publication date: 18-Mar-2024
https://dl.acm.org/doi/10.1145/3595298
Xing Lim JMonnot BPiliouras G(2022)Blockchain-based Mechanism Design for Collaborative Mathematical Research2022 IEEE International Conference on Blockchain and Cryptocurrency (ICBC)10.1109/ICBC54727.2022.9805513(1-9)Online publication date: 2-May-2022
https://doi.org/10.1109/ICBC54727.2022.9805513
Kleinberg JOren S(2022)Mechanisms for (Mis)allocating Scientific CreditAlgorithmica10.1007/s00453-021-00902-yOnline publication date: 6-Jan-2022
https://doi.org/10.1007/s00453-021-00902-y
Lim JMonnot BLin SPiliouras G(2021)A Blockchain-Based Approach for Collaborative Formalization of Mathematics and Programs2021 IEEE International Conference on Blockchain (Blockchain)10.1109/Blockchain53845.2021.00051(321-326)Online publication date: Dec-2021
https://doi.org/10.1109/Blockchain53845.2021.00051
Allon GBabich V(2020)Crowdsourcing and Crowdfunding in the Manufacturing and Services SectorsManufacturing & Service Operations Management10.1287/msom.2019.0825Online publication date: 2-Jan-2020
https://doi.org/10.1287/msom.2019.0825
Tiokhin LDerex M(2019)Competition for novelty reduces information sampling in a research game - a registered reportRoyal Society Open Science10.1098/rsos.1809346:5(180934)Online publication date: 31-May-2019
https://doi.org/10.1098/rsos.180934
Azar PGoldwasser SPark SSudan M(2016)How to Incentivize Data-Driven Collaboration Among Competing PartiesProceedings of the 2016 ACM Conference on Innovations in Theoretical Computer Science10.1145/2840728.2840758(213-225)Online publication date: 14-Jan-2016
https://dl.acm.org/doi/10.1145/2840728.2840758
Groen-Xu MTeixeira PVoigt TKnapp B(undefined)Short-Termism in Science: Evidence from the UK Research Excellence FrameworkSSRN Electronic Journal10.2139/ssrn.3083692
https://doi.org/10.2139/ssrn.3083692

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