Groups of diverse problem solvers can outperform groups of high-ability problem solvers
Open accessAbstract
We introduce a general framework for modeling functionally diverse problem-solving agents. In this framework, problem-solving agents possess representations of problems and algorithms that they use to locate solutions. We use this framework to establish a result relevant to group composition. We find that when selecting a problem-solving team from a diverse population of intelligent agents, a team of randomly selected agents outperforms a team comprised of the best-performing agents. This result relies on the intuition that, as the initial pool of problem solvers becomes large, the best-performing agents necessarily become similar in the space of problem solvers. Their relatively greater ability is more than offset by their lack of problem-solving diversity.
The claims and statistics of this paper haven’t been checked yet.
Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.
Integrity signals
Registry
Cites
Statistics
Claims the paper makes
The claims and statistics of this paper haven’t been checked yet.
Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.
Claims other papers make about this one
Each is checked against this paper’s own text: does it say what the citing paper says it does?
Jury Theorems argue that under certain conditions, a diverse set of users can arrive at better solutions than experts.
“Jury Theorems argue that under certain conditions, a diverse set of users can arrive at better solutions than experts (Hong & Page, 2004;Dietrich & Spiekermann, 2021).”
From On Epistemic Diversity in Large Language Models (2026) · cites this paper as Hong & Page, 2004
By adding members with different life experiences and cognitive problem-solving skills, and given favourable conditions, diverse groups may even outperform experts.
“By adding members with different life experiences and cognitive problem-solving skills, and given favourable conditions, diverse groups may even outperform experts (Hong and Page 2004).”
From Institutionalised distrust and human oversight of artificial intelligence: towards a democratic design of AI governance under the European Union AI Act (2024) · cites this paper as Hong and Page 2004
Self-check
Percentages, sums and reported differences re-computed from the paper’s own numbers.
The self-check needs the paper’s full text.
Cites
Newell, A. (1972) · Cited by 6,222 · see citing works
Human Inference: Strategies and Shortcomings of Social Judgment.
Cherniak, C., Nisbett, R. E., & Ross, L. D. (1983) · The Philosophical Review · doi:10.2307/2184495 · Cited by 4,196 · see citing works
Miller, G. A., & Cantor, N. E. (1982) · Social Cognition · doi:10.1521/soco.1982.1.1.83 · Cited by 2,862 · see citing works
Watson, W. E., Kumar, K., & Michaelsen, L. K. (1993) · Academy of Management Journal · doi:10.5465/256593 · Cited by 1,454 · see citing works
Capitalizing on Diversity: Interpersonal Congruence in Small Work Groups
Polzer, J. T., Milton, L. P., & Swann, W. B. (2002) · Administrative Science Quarterly · doi:10.2307/3094807 · Cited by 608 · see citing works
Problem Solving by Heterogeneous Agents
Hong, L., & Page, S. E. (2001) · Journal of Economic Theory · doi:10.1006/jeth.2000.2709 · Cited by 460 · see citing works
Self-citationCooperative Solution of Constraint Satisfaction Problems
Clearwater, S. H., Huberman, B. A., & Hogg, T. (1991) · Science · doi:10.1126/science.254.5035.1181 · Cited by 154 · see citing works
The performance of cooperative processes
Huberman, B. A. (1990) · Physica D Nonlinear Phenomena · doi:10.1016/0167-2789(90)90065-w · Cited by 76 · see citing works
Decision, Contract, and Emotion: Some Economics for a Complex and Confusing World
MacLeod, W. B. (1996) · Canadian Journal of Economics/Revue canadienne d économique · doi:10.2307/136215 · Cited by 49 · see citing works
Selected research on work team diversity.
(1996) · American Psychological Association eBooks · doi:10.1037/10507-000 · Cited by 46 · see citing works
Flagged first, then by citations
Research works printed but not linked: 6
- [1]Huberman, B. (1990) Physica D 42, 38-47. [Google Scholar]
- [2]Clearwater, S., Huberman, B. & Hogg, T. (1991) Science 254, 1181-1183. [DOI] [PubMed] [Google Scholar]
- [3]Polzer, J. T., Milton, L. P. & Swann, W. B., Jr. (2002) Admin. Sci. Q. 47, 296-327. [Google Scholar]
- [8]Hong, L. & Page, S. E. (2001) J. Econ. Theor. 97, 123-163. [Google Scholar]
- [9]MacLeod, B. (1996) Can. J. Econ. 29, 788-810. [Google Scholar]
- [11]Watson, W., Kumar, K. & Michaelsen, L. (1993) Acad. Manage. J. 36, 590-602. [Google Scholar]
Cited by
Sorted by citations
The weirdest people in the world?
Henrich, J., Heine, S. J., & Norenzayan, A. (2010) · Behavioral and Brain Sciences · doi:10.1017/s0140525x0999152x · Cited by 12,641 · see citing works
On the Opportunities and Risks of Foundation Models
Bommasani, R., Hudson, D. A., Adeli, E., Altman, R., Arora, S., von Arx, S., Bernstein, M. S., Bohg, J., Bosselut, A., Brunskill, E., et al. (2021) · arXiv · doi:10.48550/arxiv.2108.07258 · Cited by 2,676 · see citing works
Tweeting From Left to Right: Is Online Political Communication More Than an Echo Chamber?
Barberá, P., Jost, J. T., Nagler, J., Tucker, J. A., & Bonneau, R. (2015) · Psychological Science · doi:10.1177/0956797615594620 · Cited by 1,472 · see citing works
Marginality and Problem-Solving Effectiveness in Broadcast Search
Jeppesen, L. B., & Lakhani, K. R. (2010) · Organization Science · doi:10.1287/orsc.1090.0491 · Cited by 1,178 · see citing works
Delphi Technique in Health Sciences: A Map
Niederberger, M., & Spranger, J. (2020) · Frontiers in Public Health · doi:10.3389/fpubh.2020.00457 · Cited by 1,072 · see citing works
Board diversity, firm risk, and corporate policies
Bernile, G., Bhagwat, V., & Yonker, S. E. (2017) · Journal of Financial Economics · doi:10.1016/j.jfineco.2017.12.009 · Cited by 1,038 · see citing works
The globalization of socio-ecological systems: An agenda for scientific research
Young, O. R., Berkhout, F., Gallopin, G. C., Janssen, M. A., Ostrom, E., & van der Leeuw, S. (2006) · Global Environmental Change · doi:10.1016/j.gloenvcha.2006.03.004 · Cited by 871 · see citing works
Anderson, E. (2006) · Episteme · doi:10.3366/epi.2006.3.1-2.8 · Cited by 724 · see citing works
Artificial intelligence and illusions of understanding in scientific research
Messeri, L., & Crockett, M. J. (2024) · Nature · doi:10.1038/s41586-024-07146-0 · Cited by 707 · see citing works
Brain basis of human social interaction: from concepts to brain imaging
Hari, R., & Kujala, M. V. (2009) · Physiological Reviews · doi:10.1152/physrev.00041.2007 · Cited by 638 · see citing works
A critical review of simulation‐based mastery learning with translational outcomes
McGaghie, W. C., Issenberg, S. B., Barsuk, J. H., & Wayne, D. B. (2014) · Medical Education · doi:10.1111/medu.12391 · Cited by 660 · see citing works
Can Twitter Help Predict Firm-Level Earnings and Stock Returns?
Bartov, E., Faurel, L., & Mohanram, P. S. (2016) · The Accounting Review · doi:10.2308/accr-51865 · Cited by 618 · see citing works
Cheryan, S., Plaut, V. C., Handron, C., & Hudson, L. (2013) · Sex Roles · doi:10.1007/s11199-013-0296-x · Cited by 522 · see citing works
The preeminence of ethnic diversity in scientific collaboration
AlShebli, B., Rahwan, T., & Woon, W. L. (2018) · Nature Communications · doi:10.1038/s41467-018-07634-8 · Cited by 505 · see citing works
Governing Institutional Complexity: The Ecology of Games Framework
Lubell, M. N. (2013) · Policy Studies Journal · doi:10.1111/psj.12028 · Cited by 438 · see citing works
No progress on diversity in 40 years
Bernard, R., & Cooperdock, E. H. G. (2018) · Nature Geoscience · doi:10.1038/s41561-018-0116-6 · Cited by 434 · see citing works
The manifold costs of being a non-native English speaker in science
Amano, T., Ramírez‐Castañeda, V., Berdejo‐Espinola, V., Borokini, I. T., Chowdhury, S., Golivets, M., González‐Trujillo, J. D., Montaño‐Centellas, F. A., Paudel, K., White, R. L., et al. (2023) · PLoS Biology · doi:10.1371/journal.pbio.3002184 · Cited by 415 · see citing works
Swarm intelligence in animals and humans
Krause, J., Ruxton, G. D., & Krause, S. (2009) · Trends in Ecology & Evolution · doi:10.1016/j.tree.2009.06.016 · Cited by 400 · see citing works
Quantitative evaluation of gender bias in astronomical publications from citation counts
Čaplar, N., Tacchella, S., & Birrer, S. (2017) · Nature Astronomy · doi:10.1038/s41550-017-0141 · Cited by 401 · see citing works
Diversity and leadership in a changing world.
Eagly, A. H., & Chin, J. L. (2010) · American Psychologist · doi:10.1037/a0018957 · Cited by 404 · see citing works
Gender-Heterogeneous Working Groups Produce Higher Quality Science
Campbell, L. G., Mehtani, S., Dozier, M. E., & Rinehart, J. (2013) · PLoS ONE · doi:10.1371/journal.pone.0079147 · Cited by 393 · see citing works
National Institutes of Health addresses the science of diversity
Valantine, H. A., & Collins, F. S. (2015) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.1515612112 · Cited by 376 · see citing works
Fast and accurate decisions through collective vigilance in fish shoals
Ward, A. J. W., Herbert‐Read, J. E., Sumpter, D. J. T., & Krause, J. (2011) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.1007102108 · Cited by 375 · see citing works
Social Media, Echo Chambers, and Political Polarization
Barberá, P. (2020) · Social Media and Democracy · doi:10.1017/9781108890960.004 · Cited by 373 · see citing works
Gender bias in academia: A lifetime problem that needs solutions
Llorens, A., Tzovara, A., Bellier, L., Bhaya-Grossman, I., Bidet‐Caulet, A., Chang, W. K., Cross, Z. R., Dominguez-Faus, R., Flinker, A., Fonken, Y. M., et al. (2021) · Neuron · doi:10.1016/j.neuron.2021.06.002 · Cited by 388 · see citing works
Creativity in scientific teams: Unpacking novelty and impact
Lee, Y.-N., Walsh, J. P., & Wang, J. (2014) · Research Policy · doi:10.1016/j.respol.2014.10.007 · Cited by 364 · see citing works
Making the Difference: Applying a Logic of Diversity
Page, S. E. (2007) · Academy of Management Perspectives · doi:10.5465/amp.2007.27895335 · Cited by 350 · see citing works
Self-citationCultural Diversity, Innovation, and Entrepreneurship: Firm‐level Evidence from L ondon
Nathan, M., & Lee, N. (2013) · Economic Geography · doi:10.1111/ecge.12016 · Cited by 342 · see citing works
Clement, F. (2010) · Policy Sciences · doi:10.1007/s11077-009-9100-8 · Cited by 297 · see citing works
Intersectional inequalities in science
Kozlowski, D., Larivière, V., Sugimoto, C. R., & Monroe‐White, T. (2022) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.2113067119 · Cited by 342 · see citing works
Toward a better understanding of crowdfunding, openness and the consequences for innovation
Stanko, M. A., & Henard, D. H. (2017) · Research Policy · doi:10.1016/j.respol.2017.02.003 · Cited by 310 · see citing works
Will Humans-in-the-Loop Become Borgs? Merits and Pitfalls of Working with AI
Fügener, A., Grahl, J., Gupta, A., & Ketter, W. (2021) · MIS Quarterly · doi:10.25300/misq/2021/16553 · Cited by 322 · see citing works
Cheruvelil, K. S., Soranno, P. A., Weathers, K. C., Hanson, P. C., Goring, S. J., Filstrup, C. T., & Read, E. K. (2014) · Frontiers in Ecology and the Environment · doi:10.1890/130001 · Cited by 302 · see citing works
The role of diversity in organizational resilience: a theoretical framework
Duchek, S., Raetze, S., & Scheuch, I. (2019) · BuR - Business Research · doi:10.1007/s40685-019-0084-8 · Cited by 341 · see citing works
Facts and Where to Find Them: Empirical Research on Internet Platforms and Content Moderation
Keller, D., & Leerssen, P. (2020) · Data Archiving and Networked Services (DANS) · doi:10.1017/9781108890960
Algorithm Selection for Combinatorial Search Problems: A Survey
Kotthoff, L. (2016) · Lecture notes in computer science · doi:10.1007/978-3-319-50137-6_7 · Cited by 299 · see citing works
The Value of Openness in Scientific Problem Solving
Lakhani, K. R., Jeppesen, L. B., Lohse, P. A., & Panetta, J. A. (2007) · Cited by 303 · see citing works
Reasoning Is for Arguing: Understanding the Successes and Failures of Deliberation
Mercier, H., & Landemore, H. E. (2012) · Political Psychology · doi:10.1111/j.1467-9221.2012.00873.x · Cited by 318 · see citing works
Lafont, C. (2019) · doi:10.1093/oso/9780198848189.001.0001 · Cited by 273 · see citing works
Gibbs, K. D., & Griffin, K. A. (2013) · CBE—Life Sciences Education · doi:10.1187/cbe.13-02-0021 · Cited by 261 · see citing works
The nexus between labor diversity and firm’s innovation
Parrotta, P., Pozzoli, D., & Pytlíková, M. (2013) · Journal of Population Economics · doi:10.1007/s00148-013-0491-7 · Cited by 266 · see citing works
Open collaboration for innovation: Principles and performance
Levine, S. S., & Prietula, M. J. (2014) · Organization Science · doi:10.1287/orsc.2013.0872 · Cited by 263 · see citing works
Making gender diversity work for scientific discovery and innovation
Nielsen, M. W., Bloch, C. W., & Schiebinger, L. L. (2018) · Nature Human Behaviour · doi:10.1038/s41562-018-0433-1 · Cited by 260 · see citing works
Ethnic diversity deflates price bubbles
Levine, S. S., Apfelbaum, E. P., Bernard, M. M., Bartelt, V. L., Zajac, E. J., & Stark, D. (2014) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.1407301111 · Cited by 254 · see citing works
Grover, P., Kar, A. K., Janssen, M., & Ilavarasan, P. V. (2019) · Enterprise Information Systems · doi:10.1080/17517575.2019.1599446 · Cited by 278 · see citing works
Culture, Ethnicity and Diversity
Klaus Desmet, A., Ortuño-Ortı́n, I., & Wacziarg, R. T. (2015) · American Economic Review · doi:10.1257/aer.20150243 · Cited by 251 · see citing works
The Role of Social Media in Corporate Governance
Ang, J. S. K., Hsu, C., Tang, D., & Wu, C. (2020) · The Accounting Review · doi:10.2308/tar-2018-0144 · Cited by 243 · see citing works
Quality of evidence revealing subtle gender biases in science is in the eye of the beholder
Handley, I. M., Brown, E. R., Moss-Racusin, C. A., & Smith, J. L. (2015) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.1510649112 · Cited by 240 · see citing works
Mentorship of Underrepresented Physicians and Trainees in Academic Medicine: a Systematic Review
Bonifacino, E., Ufomata, E. O., Farkas, A. H., Turner, R. L., & Corbelli, J. A. (2021) · Journal of General Internal Medicine · doi:10.1007/s11606-020-06478-7 · Cited by 236 · see citing works
Diversity Management: A Critical Review and Agenda for the Future
Köllen, T. (2019) · Journal of Management Inquiry · doi:10.1177/1056492619868025 · Cited by 230 · see citing works
Monetary policy by committee: Why and how?
Blinder, A. S. (2006) · European Journal of Political Economy · doi:10.1016/j.ejpoleco.2006.01.003 · Cited by 229 · see citing works
Earth, D. O. (2014) · International Linear Collider · Cited by 223 · see citing works
Biomedical Science Ph.D. Career Interest Patterns by Race/Ethnicity and Gender
Gibbs, K. D., McGready, J., Bennett, J., & Griffin, K. A. (2014) · PLoS ONE · doi:10.1371/journal.pone.0114736 · Cited by 221 · see citing works
Epistemic Democracy and Its Challenges
Schwartzberg, M. (2015) · Annual Review of Political Science · doi:10.1146/annurev-polisci-110113-121908 · Cited by 219 · see citing works
Effects of Heterogeneity in Residential Preferences on an Agent-Based Model of Urban Sprawl
Brown, D. G., & Robinson, D. T. (2006) · Ecology and Society · doi:10.5751/es-01749-110146 · Cited by 219 · see citing works
Larger groups are more successful in innovative problem solving in house sparrows
Liker, A., & Bókony, V. (2009) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.0900042106 · Cited by 221 · see citing works
Three Challenges for AI-Assisted Decision-Making
Steyvers, M., & Kumar, A. (2024) · Perspectives on Psychological Science · doi:10.1177/17456916231181102 · Cited by 217 · see citing works
Disparities in Vision Health and Eye Care
Elam, A. R., Tseng, V. L., Rodriguez, T. M., Mike, E. V., Warren, A., Coleman, A. L., Aguwa, U. T., Alabiad, C. R., Briceño, C. A., Capó, H., et al. (2022) · Ophthalmology · doi:10.1016/j.ophtha.2022.07.010 · Cited by 226 · see citing works
Larger groups of passerines are more efficient problem solvers in the wild
Morand‐Ferron, J., & Quinn, J. L. (2011) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.1111560108 · Cited by 211 · see citing works
Underrepresented faculty play a disproportionate role in advancing diversity and inclusion
Jimenez, M. F., Laverty, T. M., Bombaci, S., Wilkins, K., Bennett, D. E., & Pejchar, L. (2019) · Nature Ecology & Evolution · doi:10.1038/s41559-019-0911-5 · Cited by 210 · see citing works
When Passionate Advocates Meet Research on Diversity, Does the Honest Broker Stand a Chance?
Eagly, A. H. (2016) · Journal of Social Issues · doi:10.1111/josi.12163 · Cited by 209 · see citing works
Misinformation, Disinformation, and Online Propaganda
Guess, A. M., & Lyons, B. A. (2020) · Social Media and Democracy · doi:10.1017/9781108890960.003 · Cited by 284 · see citing works
Landemore, H. E. (2012) · Synthese · doi:10.1007/s11229-012-0062-6 · Cited by 207 · see citing works
Without inclusion, diversity initiatives may not be enough
Puritty, C. E., Strickland, L. R., Alia, E., Blonder, B. W., Klein, E. S., Kohl, M. T., McGee, E. N., Quintana, M., Ridley, R. E., Tellman, B., et al. (2017) · Science · doi:10.1126/science.aai9054 · Cited by 205 · see citing works
Human and AI Ensembles: When Can They Work?
Choudhary, V., Marchetti, A., Shrestha, Y. R., & Puranam, P. (2021) · Journal of Management · doi:10.1177/01492063231194968 · Cited by 223 · see citing works
Perceptions and Price: Evidence from CEO Presentations at IPO Roadshows
Blankespoor, E., Hendricks, B. E., & Miller, G. S. (2017) · Journal of Accounting Research · doi:10.1111/1475-679x.12164 · Cited by 192 · see citing works
What is the price of a skill? The value of complementarity
Stephany, F., & Teutloff, O. (2024) · Research Policy · doi:10.1016/j.respol.2023.104898 · Cited by 199 · see citing works
Openness and innovation in the US: Collaboration form, idea generation and implementation
Walsh, J. P., Lee, Y.-N., & Nagaoka, S. (2016) · Research Policy · doi:10.1016/j.respol.2016.04.013 · Cited by 197 · see citing works
Skills and global value chains
Grundke, R., Jamet, S., Kalamova, M., Keslair, F., & Squicciarini, M. (2017) · OECD science, technology and industry working papers · doi:10.1787/cdb5de9b-en · Cited by 201 · see citing works
Abizadeh, A. (2020) · Perspectives on Politics · doi:10.1017/s1537592719004626 · Cited by 192 · see citing works
Arlinghaus, R., Laskowski, K. L., Alós, J., Klefoth, T., Monk, C. T., Nakayama, S., & Schröder, A. (2016) · Fish and Fisheries · doi:10.1111/faf.12176 · Cited by 184 · see citing works
Making better decisions in groups
Bang, D., & Frith, C. (2017) · Royal Society Open Science · doi:10.1098/rsos.170193 · Cited by 194 · see citing works
Davis‐Stober, C. P., Budescu, D. V., Dana, J. D., & Broomell, S. B. (2014) · Decision · doi:10.1037/dec0000004 · Cited by 184 · see citing works
Aggregated knowledge from a small number of debates outperforms the wisdom of large crowds
Navajas, J., Niella, T., Garbulsky, G., Bahrami, B., & Sigman, M. (2018) · Nature Human Behaviour · doi:10.1038/s41562-017-0273-4 · Cited by 183 · see citing works
Peek, L., Tobin-Gurley, J., Adams, R. M., Wu, H., & Mathews, M. C. (2020) · Frontiers in Built Environment · doi:10.3389/fbuil.2020.00110 · Cited by 177 · see citing works
Algorithm Selection for Combinatorial Search Problems: A Survey
Kotthoff, L. (2014) · AI Magazine · doi:10.1609/aimag.v35i3.2460 · Cited by 173 · see citing works
Kahn, S., & Ginther, D. K. (2017) · National Bureau of Economic Research · doi:10.3386/w23525 · Cited by 180 · see citing works
Optimal diversity: Increasing returns versus recombinant innovation
van den Bergh, J. C. J. M. (2008) · Journal of Economic Behavior & Organization · doi:10.1016/j.jebo.2008.09.003 · Cited by 167 · see citing works
Labor diversity and firm productivity
Parrotta, P., Pozzoli, D., & Pytlíková, M. (2014) · European Economic Review · doi:10.1016/j.euroecorev.2013.12.002 · Cited by 166 · see citing works
Bikard, M. A., Vakili, K., & Teodoridis, F. (2018) · Organization Science · doi:10.1287/orsc.2018.1235 · Cited by 163 · see citing works
The Costs and Benefits of Calculation and Moral Rules
Bennis, W. M., Medin, D., & Bartels, D. M. (2010) · Perspectives on Psychological Science · doi:10.1177/1745691610362354 · Cited by 162 · see citing works
The wisdom of polarized crowds
Shi, F., Teplitskiy, M., Duede, E., & Evans, J. A. (2019) · Carolina Digital Repository (University of North Carolina at Chapel Hill) · Cited by 162 · see citing works
The ensemble approach to forecasting: A review and synthesis
Wu, H., & Levinson, D. M. (2021) · Transportation Research Part C Emerging Technologies · doi:10.1016/j.trc.2021.103357 · Cited by 161 · see citing works
Seeking Similarity: How Immigrants and Natives Manage in the Labor Market
Åslund, O., Hensvik, L., & Skans, O. N. (2014) · Journal of Labor Economics · doi:10.1086/674985 · Cited by 158 · see citing works
Point of Departure and Key Concepts
(IPCC), I. P. O. C. C. (2023) · Cambridge University Press eBooks · doi:10.1017/9781009325844.003 · Cited by 171 · see citing works
The Independence Thesis: When Individual and Social Epistemology Diverge
Mayo‐Wilson, C., Zollman, K., & Danks, D. J. (2011) · Philosophy of Science · doi:10.1086/661777 · Cited by 150 · see citing works
Networks and the Challenge of Sustainable Development
Henry, A. D., & Vollan, B. (2014) · Annual Review of Environment and Resources · doi:10.1146/annurev-environ-101813-013246 · Cited by 147 · see citing works
The Epistemic Value of Democratic Deliberation
Estlund, D., & Landemore, H. E. (2018) · Oxford University Press eBooks · doi:10.1093/oxfordhb/9780198747369.013.26 · Cited by 146 · see citing works
Review of contact and contactless active space debris removal approaches
Ledkov, A. S., & Aslanov, V. S. (2022) · Progress in Aerospace Sciences · doi:10.1016/j.paerosci.2022.100858 · Cited by 145 · see citing works
Landemore, H. E. (2012) · Cambridge University Press eBooks · doi:10.1017/cbo9780511846427.012 · Cited by 143 · see citing works
Cultural Neuroscience: Progress and Promise
Chiao, J. Y., Cheon, B. K., Pornpattananangkul, N., Mrazek, A. J., & Blizinsky, K. D. (2013) · Psychological Inquiry · doi:10.1080/1047840x.2013.752715 · Cited by 143 · see citing works
Dalal, S. R., Khodyakov, D., Srinivasan, R., Straus, S. G., & Adams, J. (2011) · Technological Forecasting and Social Change · doi:10.1016/j.techfore.2011.03.021 · Cited by 138 · see citing works
Diversity among Norwegian Boards of Directors: Does a Quota for Women Improve Firm Performance?
Dale‐Olsen, H., Schøne, P., & Verner, M. (2013) · Feminist Economics · doi:10.1080/13545701.2013.830188 · Cited by 140 · see citing works
Inequality in science and the case for a new agenda
Graves, J. L., Kearney, M., Barabino, G. A., & Malcom, S. M. (2022) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.2117831119 · Cited by 139 · see citing works
Philip, T. M., Bang, M., & Jackson, K. J. (2018) · Cognition and Instruction · doi:10.1080/07370008.2018.1413530 · Cited by 137 · see citing works
Citizen Science: New Research Challenges for Human–Computer Interaction
Preece, J. (2016) · International Journal of Human-Computer Interaction · doi:10.1080/10447318.2016.1194153 · Cited by 135 · see citing works
Bayesian modeling of human–AI complementarity
Steyvers, M., Tejeda, H., Kerrigan, G., & Smyth, P. (2022) · Proceedings of the National Academy of Sciences of the United States of America · doi:10.1073/pnas.2111547119 · Cited by 207 · see citing works
I nvestigate D iscuss E stimate A ggregate for structured expert judgement
Hanea, A., McBride, M., Burgman, M., Wintle, B., Fidler, F., Flander, L., Twardy, C. R., Manning, B., & Mascaro, S. (2017) · International Journal of Forecasting · doi:10.1016/j.ijforecast.2016.02.008 · Cited by 95 · see citing works
Algorithm-mediated social learning in online social networks
Brady, W. J., Jackson, J. C., Lindström, B., & Crockett, M. J. (2023) · Trends in Cognitive Sciences · doi:10.1016/j.tics.2023.06.008 · Cited by 132 · see citing works
Wisdom of stakeholder crowds in complex social–ecological systems
Aminpour, P., Gray, S. A., Jetter, A. J. M., Introne, J. E., Singer, A., & Arlinghaus, R. (2020) · Nature Sustainability · doi:10.1038/s41893-019-0467-z · Cited by 135 · see citing works
- Authors
- Hong, L., & Page, S. E.
- Affiliations
- Loyola University Chicago (US)
- Corresponding author
- Hong, Lu
- Venue
- Proceedings of the National Academy of Sciences
- Publisher
- National Academy of Sciences
- Published
- 2004-11-08
- Volume
- 101
- Issue
- 46
- Pages
- 16385-16389
- ISSN
- 0027-8424 (ISSN-L)
- 1091-6490
- PMC
- PMC528939
- OpenAlex
- W2158392329
- Cited by
- 2,103
- References
- 10
- Citations by year
- 2026: 168 · 2025: 183 · 2024: 197 · 2023: 215 · 2022: 189 · 2021: 175 · 2020: 157 · 2019: 127 · 2018: 154 · 2017: 84 · 2016: 87 · 2015: 77 · 2014: 63 · 2013: 54 · 2012: 47
- FWCI
- 9.73
- Type
- journal article
- Language
- en
- Open access
- green
- europepmc.org
- Locations
- Proceedings of the National Academy of Sciences (publishedVersion)
- Europe PMC (PubMed Central) (publishedVersion)
- PubMed Central (publishedVersion)
- PubMed (publishedVersion)
- Topics
- Social Sciences › Psychology › Social Psychology › Team Dynamics and Performance
- Social Sciences › Economics, Econometrics and Finance › Economics and Econometrics › Game Theory and Voting Systems
- Physical Sciences › Computer Science › Computer Networks and Communications › Distributed Control Multi-Agent Systems
- Keywords
- group composition, team performance, problem-solving agents, agent selection, problem representation, algorithmic search
About these checks
Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.
Statistics and arithmetic are recomputed, not judged.
Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.
What counts as a claim ›How we measure confidence ›How we check this ›
Are you an author, or do you see a problem with this page? Request a review
