Skip to main content Accessibility help

We use cookies to distinguish you from other users and to provide you with a better experience on our websites. Close this message to accept cookies or find out how to manage your cookie settings.

Close cookie message
×
Hostname: page-component-cd9895bd7-mkpzs Total loading time: 0 Render date: 2024-12-26T21:07:03.509Z Has data issue: false hasContentIssue false

32 - Collective Intelligence

from Part VI - Kinds of Intelligence

Published online by Cambridge University Press:  13 December 2019

By
Thomas W. Malone  and
Anita Williams Woolley
Edited by
Robert J. Sternberg
Robert J. Sternberg
Affiliation:
Cornell University, New York
Get access

Summary

In addition to human, animal, and artificial intelligence, there is another important kind of intelligence on our planet: the collective intelligence of groups of individuals acting collectively in ways that seem intelligent. This chapter analyzes collective intelligence in terms of what tasks are being done, who is doing them, and why and how the tasks are being done. For instance, the chapter shows how groups can have both specialized and general collective intelligence and how the collective intelligence of a group can depend on the task-relevant abilities of group members, their interpersonal abilities, their diversity, and their intrinsic or extrinsic motivations. The chapter also analyzes the factors involved in group-level processes such as deciding, creating, remembering, sensing, learning, and coordinating. Just as studying the neural basis for intelligence links neural processes to cognitive psychology, studying collective intelligence links cognitive psychology to higher-level social, organizational, and economic processes.

Keywords

collective intelligencegroup intelligencegroupsteamsorganizationswisdom of crowds
Type
Chapter
Information
The Cambridge Handbook of Intelligence , pp. 780 - 801
Publisher: Cambridge University Press
Print publication year: 2020

Access options

Get access to the full version of this content by using one of the access options below. (Log in options will check for institutional or personal access. Content may require purchase if you do not have access.)

References

ACM (Association for Computing Machinery). (2018). Collective Intelligence Conference Series. https://ci.acm.org/Google Scholar
Aggarwal, I., & Woolley, A. W. (2013). Do you see what I see? The effect of members’ cognitive styles on team processes and performance. Organizational Behavior and Human Decision Processes, 122, 92–99.Google Scholar
Aggarwal, I., & Woolley, A. W. (2019). Team creativity, cognition, and cognitive style diversity. Management Science, 64(4), 1586–1599. https://doi.org/10.1287/mnsc.2017.3001Google Scholar
Aggarwal, I., Woolley, A. W., Chabris, C. F., & Malone, T. W. (2019). The impact of cognitive style diversity on implicit learning in teams. Frontiers in Psychology, (10), 112. https://doi.org/doi: 0.3389/fpsyg.2019.00112Google Scholar
Alchian, A. A., & Demsetz, H. (1972). Production, information costs, and economic organization. The American Economic Review, 62(5), 777–795.Google Scholar
Argote, L. (1999). Organizational learning: Creating, retaining, and transferring knowledge. Norwell, MA: Kluwer Academic.Google Scholar
Argote, L., & Epple, D. (1990). Learning curves in manufacturing. Science, 247, 920–924.Google Scholar
Argote, L., & Miron-Spektor, E. (2011). Organizational learning: From experience to knowledge. Organization Science, 22(5), 1123–1137.Google Scholar
Argote, L., & Ren, Y. (2012). Transactive memory systems: A microfoundation of dynamic capabilities. Journal of Management Studies, 49(8), 1375–1382.Google Scholar
Arrow, K. J., & Debreu, G. (1954). Existence of an equilibrium for a competitive economy. Econometrica, 22, 265–290.Google Scholar
Ashkanasy, N. M., & Daus, C. S. (2005). Rumors of the death of emotional intelligence in organizational behavior are vastly exaggerated. Journal of Organizational Behavior, 26(4), 441–452.Google Scholar
Atlee, T., & Por, G. (2000). Collective intelligence as a field of multi-disciplinary study and practice. www.academia.edu/1981875/Collective_Intelligence_as_a_Field_of_Multi-disciplinary_Study_and_PracticeGoogle Scholar
Baron-Cohen, S., Wheelwright, S., Hill, J., Raste, Y., & Plumb, I. (2001). The “Reading the Mind in the Eyes” Test revised version: A study with normal adults, and adults with Asperger syndrome or high-functioning autism. The Journal of Child Psychology and Psychiatry and Allied Disciplines, 42(2), 241–251.Google Scholar
Bastiaens, T. J., Baumol, U., & Kramer, B. J. (Eds.). (2010). On collective intelligence. In Proceedings of the Symposium on Collective Intelligence, Hagen, Germany, April 15–16, 2010. Berlin: Springer-Verlag.Google Scholar
Bates, T. C., & Gupta, S. (2016). Smart groups of smart people: Evidence for IQ as the origin of collective intelligence in the performance of human groups. Intelligence, 60, 46–56.CrossRefGoogle Scholar
Benkler, Y., Shaw, A., & Hill, B. M. (2015). Peer production: A form of collective intelligence. In Malone, T. W. & Bernstein, M. S. (Eds.), Handbook of collective intelligence. Cambridge, MA: MIT Press.Google Scholar
Bernstein, E., Shore, J., & Lazer, D. (2018). How intermittent breaks in interaction improve collective intelligence. Proceedings of the National Academy of Sciences, 115(35), 8734–8739.Google Scholar
Bigham, J. P., Bernstein, M. S., & Adar, E. (2015). Human-computer interaction and collective intelligence. In Malone, T. W. & Bernstein, M. S. (Eds.), Handbook of collective intelligence. Cambridge, MA: MIT Press.Google Scholar
Brennan, T. J., & Lo, A. W. (2012). An evolutionary model of bounded rationality and intelligence, PLoS One, 7, e50310. doi:10.1371/journal.pone.0050310.Google Scholar
Camerer, C. F., Loewenstein, G., & Rabin, M. (Eds.) (2004). Advances in Behavioral Economics. Princeton: Princeton University Press.Google Scholar
Chabris, C. F. (2007). Cognitive and neurobiological mechanisms of the law of general intelligence. In Roberts, M. J. (Ed.), Integrating the mind: Domain general versus domain specific processes in higher cognition (pp. 449–491). Hove: Psychology Press.Google Scholar
Chakrabarti, S. (2018). Hard questions: What effect does social media have on democracy? Facebook Newsroom, January 22. https://newsroom.fb.com/news/2018/01/effect-social-media-democracy/.Google Scholar
Condorcet, M. (1785/1976). Essay on the application of analysis to the probability of majority decisions. In Baker, K. M. (Ed.), Condorcet: Selected writings, Indianapolis, IN: Bobbs-Merrill.Google Scholar
Credé, M., & Howardson, G. (2017). The structure of group task performance: A second look at “collective intelligence”: Comment on Woolley et al. (2010), Journal of Applied Psychology, 102(10), 1483–1492.Google Scholar
Davis, J. H. (1973). Group decision and social interaction: A theory of social decision schemes. Psychological Review, 80(2), 97–125.Google Scholar
Deary, I. J. (2000). Looking down on human intelligence: From psychometrics to the brain. New York: Oxford University Press.Google Scholar
Deci, E. L., & Ryan, R. M. (1985). Intrinsic motivation and self-determination in human behavior. New York: Plenum Press.Google Scholar
Devine, D. J., & Philips, J. L. (2001). Do smarter teams do better? A meta-analysis of cognitive ability and team performance. Small Group Research, 32(5), 507–532.Google Scholar
DiMicco, J. M., Pandolfo, A., & Bender, W. (2004). Influencing group participation with a shared display. In Proceedings of the 2004 ACM conference on Computer supported cooperative work (pp. 614–623). New York: Association for Computing Machinery.Google Scholar
Druskat, V. U., & Wolff, S. B. (2001). Building the emotional intelligence of groups. Harvard Business Review, 79(3), 80–90.Google Scholar
Dutton, J. M., & Thomas, A. (1984). Treating progress functions as a managerial opportunity. Academy of Management Review, 9, 235–247.Google Scholar
Easley, D., & Kleinberg, J. (2010). Networks, crowds, and markets: Reasoning about a highly connected world. Cambridge: Cambridge University Press.Google Scholar
Ebbinghaus, H. (1885). Memory: A contribution to experimental psychology. New York: Dover Publications.Google Scholar
Edmondson, A. (1999). Psychological safety and learning behavior in work teams. Administrative Science Quarterly, 44(2), 350–383.Google Scholar
Engel, D., Woolley, A. W., Jing, L. X., Chabris, C. F., & Malone, T. W. (2014). Reading the mind in the eyes or reading between the lines? Theory of mind predicts collective intelligence equally well online and face-to-face. PLoS One, 9(12), e115212.Google Scholar
Engelbart, D. C. (1962). Augmenting human intellect: A conceptual framework. No. Summary Report AFOSR-3223 under Contract AF 49 (638)-1024, SRI Project 3578 for Air Force Office of Scientific Research, Stanford Research Institute.Google Scholar
Engelbart, D. C. (1995). Toward augmenting the human intellect and boosting our collective IQ. Communications of the ACM, 38(8), 30–32.Google Scholar
Engelbart, D. C., & English, W. K. (1968). A research center for augmenting human intellect. In Proceedings of the December 9–11,1968, Fall Joint Computer Conference (Vol. 33, pp. 395–410). San Francisco: Association for Computing Machinery.Google Scholar
Faraj, S., & Xiao, Y. (2006). Coordination in fast-response organizations. Management Science, 52(8), 1155–1169.Google Scholar
Fiol, C. M., & Lyles, M. A. (1985). Organizational learning. Academy of Management Review, 10(4), 803–813.Google Scholar
Franks, N. R. (1989). Army ants: A collective intelligence? American Scientist, 7(2), 138–145.Google Scholar
Galbraith, J. R. (2002). Designing organizations. San Francisco: Jossey-Bass.Google Scholar
Galton, F. (1907). Vox Populi. Nature, 75(7), 450–451.Google Scholar
Gardner, H. (1983). Frames of mind: The theory of multiple intelligences. New York: Basic books.Google Scholar
Girotra, K., Terwiesch, C., & Ulrich, K. T. (2010). Idea generation and the quality of the best idea. Management Science, 56(4), 591–605.Google Scholar
Gordon, D. M. (2015). Collective behavior in animals: An ecological perspective. In Malone, T. W. & Bernstein, M. S. (Eds.), Handbook of collective intelligence. Cambridge, MA: MIT Press.Google Scholar
Hackman, J. R. (1987). The design of work teams. In Lorsch, J. W. (Ed.), Handbook of organizational behavior (pp. 315–342). Englewood Cliffs, NJ: Prentice Hall.Google Scholar
Hackman, J. R. (2011). Collaborative intelligence: Using teams to solve hard problems. San Francisco: Berrett-Koehler Publishers.Google Scholar
Hackman, J. R., & Oldham, G. R. (1976). Motivation through the design of work: Test of a theory. Organizational Behavior and Human Decision Processes, 16(2), 250–279.Google Scholar
Hamilton, C. (2004). Come together: Can we discover a depth of wisdom far beyond what is available to individuals alone? What Is Enlightenment, May–July, 57–77.Google Scholar
Harrison, D. D., & Klein, K. J. (2007). What’s the difference? Diversity constructs as separation, variety, or disparity in organizations. Academy of Management Review, 32(4), 1199–1228.Google Scholar
Hart, O. (1995). Firms, contracts, and financial structure. London: Oxford University Press.Google Scholar
Heylighen, F. (1999). Collective Intelligence and its implementation on the Web: Algorithms to develop a collective mental map. Computational and Mathematical Organization Theory, 5(3), 253–280.Google Scholar
Hill, G.W. (1982). Group versus individual performance: Are N + 1 heads better than one? Psychological Bulletin, 91, 517–539.Google Scholar
Hiltz, S. R., & Turoff, M. (1978). The network nation: Human communication via computer. Reading, MA: Addison-Wesley.Google Scholar
Hollingshead, A. B. (2001). Cognitive interdependence and convergent expectations in transactive memory. Journal of Personality and Social Psychology, 81(6), 1080–1089.Google Scholar
Holmstrom, B. (1982). Moral hazard in teams. The Bell Journal of Economics, 13(2), 324–340.Google Scholar
Hong, L., & Page, S. E. (2004). Groups of diverse problem solvers can outperform groups of high-ability problem solvers. Proceedings of the National Academy of Sciences, 101(46), 16385–16389.Google Scholar
Horwitz, S. K., & Horwitz, I. B. (2007). The effects of team diversity on team outcomes: A meta-analytic review of team demography. Journal of Management, 33(6), 987–1015.Google Scholar
Howe, J. (2008). Crowdsourcing: How the power of the crowd is driving the future of business. New York: Three Rivers Press.Google Scholar
Isenberg, D. J. (1986). Group polarization: A critical review and meta-analysis. Journal of Personality and Social Psychology, 50(6), 1141–1151.Google Scholar
Isaacs, W. (1999). Dialogue and the art of thinking together. New York: Doubleday Currency.Google Scholar
Janis, I. L., & Mann, L. (1977). Decision making: A psychological analysis of conflict, choice, and commitment. New York, NY: Free Press.Google Scholar
Jenkins, G. D., Mitra, A., Gupta, N., & Shaw, J. D. (1998). Are financial incentives related to performance? A meta-analytic review of empirical research. Journal of Applied Psychology, 83(5), 777–787.Google Scholar
Joshi, A., & Roh, H. (2009). The role of context in work team diversity research: A meta-analytic review. Academy of Management Journal, 52(3), 599–627.Google Scholar
Kahneman, D., & Tversky, A. (1979). Prospect theory: An analysis of decision and risk. Econometrica, 47(2), 263–291.Google Scholar
Kerr, N. L., MacCoun, R. J., & Kramer, G. P. (1996). Bias in judgment: Comparing individuals and groups. Psychological Review, 103(4), 687–719.Google Scholar
Kim, Y. J., Engel, D., Woolley, A., Lin, J., McArthur, N., & Malone, T. W. (2017). What makes a strong team? Using collective intelligence to predict performance of teams in League of Legends. In Proceedings of the 20th ACM conference on computer-supported cooperative work and social computing (CSCW 2017) (pp. 2316–2329). New York: Association for Computing Machinery.Google Scholar
Kim, Y. J., Gupta, P., Glikson, E., Woolley, A.W., & Malone, T. W. (2018). Enhancing collective of human-machine teams. Paper presented at the ACM Conference on Collective Intelligence, Zurich, Switzerland, July 7–8.Google Scholar
Knott, A. M. (2008). R&D/returns causality: Absorptive capacity or organizational IQ. Management Science, 54(12), 2054–2067.Google Scholar
Kogut, B., & Zander, U. (1992). Knowledge of the firm, combinative capabilities, and the replication of technology. Organization Science, 3(3), 383–397.Google Scholar
Korde, R., & Paulus, P. B. (2017). Alternating individual and group idea generation: Finding the elusive synergy. Journal of Experimental Social Psychology, 70, 177–190.Google Scholar
Kowalczyk, R. (Ed.). (2009). Computational collective intelligence. Paper presented at the Proceedings of the First International Conference on Computational Collective Intelligence, Wroclaw, Poland, October 5–7.Google Scholar
Krych-Appelbaum, M., Law, J. B., Barnacz, A., Johnson, A., & Keenan, J. P. (2007). The role of theory of mind in communication. Journal of Interaction Studies, 8(2), 267–280.Google Scholar
Larson, J. R. (2009). In search of synergy in small group performance. New York: Psychology Press.Google Scholar
Latane, B., Williams, K., & Harkins, S. (1979). Many hands make light the work: The causes and consequences of social loafing. Journal of Personality and Social Psychology, 37(6), 822–832.Google Scholar
Lawrence, P. R., & Lorsch, J. W. (1967). Organization and environment: Managing differentiation and integration. Cambridge, MA: Harvard Business School Press.Google Scholar
Lazear, E. P. (2000). Performance pay and productivity. The American Economic Review, 90(5), 1346–1361.Google Scholar
Levy, P. (1997). Collective intelligence: Mankind’s emerging world in cyberspace. New York: Plenum Press.Google Scholar
Lewis, K. (2004). Knowledge and performance in knowledge-worker teams: A longitudinal study of transactive memory systems. Management Science, 50, 1519–1533.Google Scholar
Lewis, K., & Herndon, B. (2011). The relevance of transactive memory systems for complex, dynamic group tasks. Organization Science, 22(5), 1254–1265.Google Scholar
Lo, A. (2015). The wisdom of crowds vs. the madness of mobs. In Malone, T. W. & Bernstein, M. S. (Eds.), Handbook of collective intelligence. Cambridge, MA: MIT Press.Google Scholar
Lorenz, J., Rauhut, H., Schweitzer, F., & Helbing, D. (2011). How social influence can undermine the wisdom of crowd effect. Proceedings of the National Academy of Sciences, 108(22), 9020–9025. https://doi.org/10.1073/pnas.1008636108.Google Scholar
Mackay, C. (1841). Memoirs of extraordinary popular delusions and the madness of crowds (1st ed.). London: Richard Bentley.Google Scholar
Malone, T. W. (2004). The future of work: How the new order of business will shape your organization, your management style and your life. Boston: Harvard Business School Press.Google Scholar
Malone, T. W. (2018). Superminds: The surprising power of people and computers thinking together. Boston: Little, Brown and Company.Google Scholar
Malone, T. W., & Bernstein, M. S. (2015). Introduction. In Malone, T. W. & Bernstein, M. S. (Eds.), Handbook of collective intelligence. Cambridge, MA: MIT Press.Google Scholar
Malone, T. W., Crowston, K., Lee, J., Pentland, B., Dellarocas, C., Wyner, G., et al. (1999). Tools for inventing organizations: Toward a handbook of organizational processes. Management Science, 45(3), 425–443.Google Scholar
Malone, T. W., Laubacher, R., & Dellarocas, C. (2010). The collective intelligence genome. MIT Sloan Management Review, 51(3), 21–31.Google Scholar
Malone, T. W., & von Ahn, L. (2012). Proceedings of the Collective Intelligence 2012 Conference. Cambridge, MA. http://arxiv.org/abs/1204.2991v3Google Scholar
Malone, T. W., Yates, J., & Benjamin, R. I. (1987). Electronic markets and electronic hierarchies. Communications of the ACM, 30(6), 484–497.CrossRefGoogle Scholar
Mann, R. D. (1959). A review of the relationships between personality and performance in small groups. Psychological Bulletin, 56(4), 241–270. https://doi.org/10.1037/h0044587CrossRefGoogle Scholar
Mataric, M. J. (1993). Designing emergent behaviors: From local interactions to collective intelligence. In Meyer, A., Roitblat, H, & Wilson, S. (Eds.), Proceedings of the Second International Conference on Simulation of Adaptive Behavior (pp. 432–441). Cambridge, MA: MIT Press.Google Scholar
McGrath, J. E. (1984). Groups: Interaction and performance. Englewood Cliffs, NJ: Prentice-Hall.Google Scholar
Meslec, N., Aggarwal, I., & Curşeu, P. L. (2016). The insensitive ruins it all: Compositional and compilational influences of social sensitivity on collective intelligence in groups. Frontiers in Psychology, 7, 676. https://doi.org/10:3389/fpsyg.2016.00676Google Scholar
Mesmer-Magnus, J. R., & DeChurch, L. A. (2009). Information sharing and team performance: A meta-analysis. Journal of Applied Psychology, 94(2), 535.Google Scholar
Milliken, F. J., & Martins, L. L. (1996). Searching for common threads: Understanding the multiple effects of diversity in organizational groups. Academy of Management Review, 21(2), 402–433.Google Scholar
Mulgan, G. (2017). Big mind: How collective intelligence can change our world. Princeton: Princeton University Press.Google Scholar
Nelson, R. R., & Winter, S. (1982). An evolutionary theory of economic change. Cambridge, MA: Harvard University Press.Google Scholar
Nonaka, I. (1994). A dynamic theory of organizational knowledge creation. Organization Science, 5(1), 14–37.Google Scholar
Ocasio, W. (1997). Towards an attention-based view of the firm. Strategic Management Journal, 18(S1), 187–206.Google Scholar
Ocasio, W. (2011). Attention to attention. Organization Science, 22(5), 1286–1296.Google Scholar
Okhuysen, G. A., & Bechky, B. A. (2009). Coordination in organizations: An integrative perspective. The Academy of Management Annals, 3(1), 463–502.Google Scholar
Page, S. E. (2008). The difference: How the power of diversity creates better groups, firms, schools, and societies. Princeton: Princeton University Press.Google Scholar
Pirolli, P., & Russell, D. M. (2011). Introduction to this special issue on sensemaking. Human-Computer Interaction, 26(1–2), 1–8.Google Scholar
Premack, D., & Woodruff, G. (1978). Does the chimpanzee have a theory of mind? Behavioral and Brain Sciences, 1(04), 515–526.Google Scholar
Prendergast, C. (1999). The provision of incentives in firms. Journal of Economic Literature, 37(1), 7–63.Google Scholar
Ridley, M. (2010). The rational optimist: How prosperity evolves. New York: Harper Collins.CrossRefGoogle Scholar
Roloff, K. S., Woolley, A. W., & Edmondson, A. C. (2011). The contribution of teams to organizational learning. In Easterby-Smith, M. & Lyles, M. (Eds.) Handbook of Organizational learning and knowledge management (2nd ed., pp. 249–271). London: Blackwell.Google Scholar
Sanders, G. S., & Baron, R. S. (1977). Is social comparison irrelevant for producing choice shifts? Journal of Experimental Social Psychology, 13(4), 303–314.Google Scholar
Senge, P. M., & Sterman, J. D. (1992). Systems thinking and organizational learning: Acting locally and thinking globally in the organization of the future. In Kochan, T. A. & Useem, M. (Eds.) Transforming organization (pp. 353–371). New York: Oxford University Press.Google Scholar
Simon, H. A. (1947). Administrative behavior: A study of decision-making processes in administrative organizations. Chicago: Macmillan.Google Scholar
Smith, J. B. (1994). Collective intelligence in computer-based collaboration. Hillsdale, NJ: Lawrence Erlbaum Associates.Google Scholar
Spearman, C. (1904). General intelligence, objectively determined and measured. The American Journal of Psychology, 15(2), 201.Google Scholar
Stasser, G., & Titus, W. (1985). Pooling of unshared information in group decision making: Biased information sampling during discussion. Journal of Personality and Social Psychology, 57, 67–78.Google Scholar
Steiner, I. D. (1966). Models for inferring relationships between group size and potential group productivity. Behavioral Science, 11(4), 273–283.Google Scholar
Steiner, I. D. (1972). Group process and productivity. New York: Academic Press.Google Scholar
Steyvers, M., & Miller, B. (2015). Cognition and collective intelligence. In Malone, T. W. & Bernstein, M. S. (Eds.), Handbook of collective intelligence. Cambridge, MA: MIT Press.Google Scholar
Stroebe, W., Nijstad, B. A., & Rietzschel, E. F. (2010). Beyond productivity loss in brainstorming groups: The evolution of a question. Advances in Experimental Social Psychology, 43, 157–203.Google Scholar
Surowiecki, J. (2004). The wisdom of crowds: Why the many are smarter than the few and how collective wisdom shapes business, economies, societies and nations. New York: Anchor Books.Google Scholar
Szuba, T. M. (2001). Computational collective intelligence. New York: John Wiley & Sons.Google Scholar
Tapscott, D., & Williams, A. D. (2006). Wikinomics: How mass collaboration changes everything. New York: Portfolio/Penguin.Google Scholar
Thompson, J. D. (1967). The structure of complex organizations. Harmondsworth: Penguin Books.Google Scholar
Thorndike, E. L. (1898). Animal intelligence: An experimental study of the associative processes in animals. Psychological Review, 2(4), 1–109.Google Scholar
Toma, C., & Butera, F. (2009). Hidden profiles and concealed information: Strategic information sharing and use in group decision making. Personality and Social Psychology Bulletin, 35(6), 793–806.Google Scholar
Ulrich, K. T., & Eppinger, S. D. (2015). Product design and development. New York: McGraw-Hill.Google Scholar
Van de Ven, A. H., Delbecq, A. L., & Koenig, R. (1976). Determinants of coordination modes within organizations. American Sociological Review, 41(2), 322–338.Google Scholar
van Knippenberg, D., & Mell, J. N. (2016). Past, present, and potential future of team diversity research: From compositional diversity to emergent diversity. Organizational Behavior and Human Decision Processes, 136, 135–145.Google Scholar
Vosoughi, S., Roy, D., & Aral, S. (2018). The spread of true and false news online. Science, 359(6380), 1146–1151.Google Scholar
Wageman, R., & Baker, G. (1997). Incentives and cooperation: The joint effects of task and reward interdependence on group performance. Journal of Organizational Behavior, 18(2), 139–158.Google Scholar
Watson, A. C., Nixon, C. L., Wilson, A., & Capage, L. (1999). Social interaction skills and theory of mind in young children. Developmental Psychology, 35(2), 386.Google Scholar
Wechsler, D. (1971). Concept of collective intelligence. American Psychologist, 26(10), 904–907.Google Scholar
Wegner, D. M. (1987). Transactive memory: A contemporary analysis of the group mind. In Mullen, B & Goethals, G. R. (Eds.), Theories of group behavior (pp. 185–208). New York: Springer-Verlag.Google Scholar
Weick, K. E. (1993). The collapse of sensemaking in organizations: The Mann Gulch disaster. Administrative Science Quarterly, 38, 628–652.Google Scholar
Weick, K. E. (1995). Sensemaking in organizations. Thousand Oaks, CA: Sage Publications.Google Scholar
Weick, K. E., Sutcliffe, K. M., & Obstfeld, D. (2005). Organizing and the process of sensemaking. Organization Science, 16(4), 409–421.Google Scholar
Weld, D. S., Mausam, , Lin, C. H., & Bragg, J. (2015). Artificial intelligence and collective intelligence. In Malone, T. W & Bernstein, M. S (Eds.), Handbook of collective intelligence (pp. 89–118). Cambridge, MA: MIT Press.Google Scholar
Williams, W. M., & Sternberg, R. J. (1988). Group intelligence: Why some groups are better than others. Intelligence, 12(4), 351–377.Google Scholar
Williamson, O. E. (1973). Markets and hierarchies. American Economic Review, 63, 316–325.Google Scholar
Williamson, O. E. (1981). The economics of organization: The transaction cost approach. American Journal of Sociology, 87(3), 548–577.Google Scholar
Wilson, J. M., Goodman, P. S., & Cronin, M. A. (2007). Group learning. Academy of Management Review, 32(4), 1041–1059.Google Scholar
Woolley, A. W. (2009a). Means versus ends: Implications of outcome and process focus for team adaptation and performance. Organization Science, 20, 500–515.Google Scholar
Woolley, A. W. (2009b). Putting first things first: Outcome and process focus in knowledge work teams. Journal of Organizational Behavior, 30, 427–452.Google Scholar
Woolley, A. W., Chabris, C. F., Pentland, A., Hashmi, N., & Malone, T. W. (2010). Evidence for a collective intelligence factor in the performance of human groups. Science, 330(6004), 686–688.Google Scholar
Woolley, A. W., Gerbasi, M. E., Chabris, C. F., Kosslyn, S. M., & Hackman, J. R. (2008). Bringing in the experts: How team composition and work strategy jointly shape analytic effectiveness. Small Group Research, 39(3), 352–371.Google Scholar
Woolley, A. W., Hackman, J. R., Jerde, T. J., Chabris, C. F., Bennett, S. L., & Kosslyn, S. M. (2007). Using brain-based measures to compose teams: How individual capabilities and team collaboration strategies jointly shape performance. Social Neuroscience, 2, 96–105.Google Scholar
Woolley, A. W., Kim, Y., & Malone, T. W. (2018). Measuring collective intelligence in groups: A reply to Credé and Howardson. Social Science Research Network Paper No. ID 3187373, Rochester, NY. https://papers.ssrn.com/abstract=3187373Google Scholar
Woolley, A. W., Riedl, C., Kim, Y. J., & Malone, T. W. (2017). More evidence for a general collective intelligence factor in human groups: A meta-analysis. Paper presented at the 2017 Collective Intelligence Conference, New York, June 16, 2017.Google Scholar

Save book to Kindle

To save this book to your Kindle, first ensure no-reply@cambridge.org is added to your Approved Personal Document E-mail List under your Personal Document Settings on the Manage Your Content and Devices page of your Amazon account. Then enter the ‘name’ part of your Kindle email address below. Find out more about saving to your Kindle.

Note you can select to save to either the @free.kindle.com or @kindle.com variations. ‘@free.kindle.com’ emails are free but can only be saved to your device when it is connected to wi-fi. ‘@kindle.com’ emails can be delivered even when you are not connected to wi-fi, but note that service fees apply.

Find out more about the Kindle Personal Document Service.

Available formats
×

Save book to Dropbox

To save content items to your account, please confirm that you agree to abide by our usage policies. If this is the first time you use this feature, you will be asked to authorise Cambridge Core to connect with your account. Find out more about saving content to Dropbox.

Available formats
×

Save book to Google Drive

To save content items to your account, please confirm that you agree to abide by our usage policies. If this is the first time you use this feature, you will be asked to authorise Cambridge Core to connect with your account. Find out more about saving content to Google Drive.

Available formats
×