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Towards Scalable Governance: Sensemaking and Cooperation in the Age of Social Media

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Cybernetics, or self-governance of animal and machine, requires the ability to sense the world and to act on it in an appropriate manner. Likewise, self-governance of a human society requires groups of people to collectively sense and act on their environment. I argue that the evolution of political systems is characterized by a series of innovations that attempt to solve (among others) two ‘scalability’ problems: scaling up a group’s ability to make sense of an increasingly complex world, and to cooperate in increasingly larger groups. I then explore some recent efforts toward using the Internet and social media to provide alternative means for addressing these scalability challenges, under the banners of crowdsourcing and computer-supported argumentation. I present some lessons from those efforts about the limits of technology, and the research directions more likely to bear fruit.

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  1. See also the ambitious Project Cybersyn as an early example of cybernetic governance in 1970 Chile (Medina 2011).

  2. In modern Political Science, governance is a broad term that refers to “all processes of governing, whether undertaken by a government, market or network, whether over a family, tribe, formal, or informal organization or territory and whether through laws, norms, power or language” (Bevir 2012). As opposed to government, a formal body with the authority to make decisions in a given political system, governance includes all actors with the ability to influence the decision-making process, and encompasses not only how nation states are governed, but also corporations, universities, and so on.

  3. It is worth noting that ultimately, individual humans are themselves not monoliths either. In cognitive science, there is significant theoretical and empirical support for the idea that individuals are themselves made up of societies of simpler, possibly competing agents (Minsky 1988), and maintain internal coherence among competing goals and beliefs through a form of constraint satisfaction (Thagard 2002) or interapersonal strategic game (Read 2001). However, the problems posed by such distributed governance have been effectively handled by natural evolution at the individual level, but remain very much a work-in-progress as we scale societal governance.





  8. See: Six Degrees of Mobilization. The Economist, 2013.


  • Alstott, J., Madnick, S., Velu, C., & Sánchez, A. (2014). Homophily and the speed of social mobilization: the effect of acquired and ascribed traits. PloS one, 9(4), e95140.

    Article  Google Scholar 

  • Arrow, K.J., Forsythe, R., Gorham, M., Hahn, R., Hanson, R., Ledyard, J.O., Levmore, S., Litan, R., Milgrom, P., Nelson, F.D., & et al (2008). The promise of prediction markets. Science-new york then washington-, 320(5878), 877.

    Article  Google Scholar 

  • Awad, E., Booth, R., Tohme, F., & Rahwan, I. (2016). Judgement aggregation in multi-agent argumentation. Journal of Logic and Computation, (in press).

  • Baldassarri, D., & Grossman, G. (2011). Centralized sanctioning and legitimate authority promote cooperation in humans. Proceedings of the National Academy of Sciences, 108(27), 11023–11027.

    Article  Google Scholar 

  • Bernstein, A., Klein, M., & Malone, T.W. (2012). Programming the global brain. Communications of the ACM, 55(5), 41–43.

    Article  Google Scholar 

  • Bevir, M. (2012). Governance: A very short introduction, volume 333. Oxford University Press.

  • Bex, F., Lawrence, J., Snaith, M., & Reed, C. (2013). Implementing the argument web. Communications of the ACM, 56(10), 66–73.

    Article  Google Scholar 

  • Boyd, R., & Richerson, P.J. (2004). The origin and evolution of cultures. Oxford University Press.

  • Bryan, C., Tambini, D., & Tsagarousianou, R. (2002). Cyberdemocracy, Technology, cities and civic networks. Routledge.

  • Chadwick, A. (2006). Internet politics: States, citizens and new communication technologies. USA: Oxford University Press.

    Google Scholar 

  • Chen, Y., Lai, J.K., Parkes, D.C., & Procaccia, A.D. (2013). Truth, justice, and cake cutting. Games and Economic Behavior, 77(1), 284–297.

    Article  Google Scholar 

  • Chen, Y., & Pennock, D.M. (2010). Designing markets for prediction. AI Magazine, 31(4), 42–52.

    Google Scholar 

  • Chesñevar, C.I., McGinnis, J., Modgil, S., Rahwan, I., Reed, C., Simari, G., South, M., Vreeswijk, G., & Willmott, S. (2006). Towards an argument interchange format. The Knowledge Engineering Review, 21(4), 293–316.

    Article  Google Scholar 

  • Conover, M., Ratkiewicz, J., Francisco, M.R., Gonçalves, B., Menczer, F., & Flammini, A. (2011). Political polarization on twitter. ICWSM, 133, 89–96.

    Google Scholar 

  • Dahlberg, L. (2001). The internet and democratic discourse: exploring the prospects of online deliberative forums extending the public sphere. Information, Communication & Society, 4(4), 615– 633.

    Article  Google Scholar 

  • DARPA (2011). Darpa shredder challenge. Accessed: 2013-12-26.

  • Dickinson, J.L., Zuckerberg, B., & Bonter, D.N. (2010). Citizen science as an ecological research tool: challenges and benefits. Annual review of ecology, evolution, and systematics, 41, 149–172.

    Article  Google Scholar 

  • Dietrich, F., & List, C. (2007a). Arrow’s theorem in judgment aggregation. Social Choice and Welfare, 29(1), 19–33.

    Article  Google Scholar 

  • Dietrich, F., & List, C. (2007b). Strategy-proof judgment aggregation. Economics and Philosophy, 23(03), 269–300.

    Article  Google Scholar 

  • Dietz, T., Ostrom, E., & Stern, P.C. (2003). The struggle to govern the commons. Science, 302(5652), 1907–1912.

    Article  Google Scholar 

  • Doan, A., Ramakrishnan, R., & Halevy, A.Y. (2011). Crowdsourcing systems on the world-wide web. Communications of the ACM, 54(4), 86–96.

    Article  Google Scholar 

  • Endriss, U., Grandi, U., & Porello, D. (2012). Complexity of judgment aggregation. Journal of Artificial Intelligence Research, 45, 481–514.

    Google Scholar 

  • Faliszewski, P., & Procaccia, A.D. (2010). Ai’s war on manipulation: are we winning?. AI Magazine, 31(4), 53–64.

    Google Scholar 

  • Fukuyama, F. (2011). The origins of political order: from prehuman times to the French Revolution. Profile books.

  • Goodwin, J. (2009). The authority of wikipedia. In Argument cultures: Proceedings of the Ontario Society for the Study of Argumentation conference: Ontario Society for the Study of Argumentation.

  • Gupta, A., Kumaraguru, P., Castillo, C., & Meier, P. (2014). Tweetcred: Real-time credibility assessment of content on twitter. In Social Informatics (pp. 228–243): Springer.

  • Gürerk, Ö., Irlenbusch, B., & Rockenbach, B. (2006). The competitive advantage of sanctioning institutions. Science, 312(5770), 108–111.

    Article  Google Scholar 

  • Hague, B.N. (1999). Digital democracy: Discourse and decision making in the information age. Psychology Press.

  • Hamilton, W.D. (1963). The evolution of altruistic behavior, (pp. 354–356): American naturalist.

  • Hardin, G. (1968). The tragedy of the commons. science, 162(3859), 1243–1248.

    Article  Google Scholar 

  • Haviland, W., Prins, H., McBride, B., & Walrath, D. (2013). Cultural anthropology: the human challenge. Cengage Learning.

  • Hayek, F.A. (1945). The use of knowledge in society. The American Economic Review, 35(4), 519–530.

    Google Scholar 

  • Henrich, J. (2015a). The Secret of Our Success: How Culture Is Driving Human Evolution, Domesticating Our Species, and Making Us Smarter. Princeton University Press.

  • Henrich, J. (2015b). The secret of our success: how culture is driving human evolution, domesticating our species, and making us smarter. Princeton University Press.

  • Hobbes, T. (1651). Leviathan, or, the Matter, Forme, and Power of a Common-Wealth Ecclesiasticall and Civill.

  • Hoffman, K., Zage, D., & Nita-Rotaru, C. (2009). A survey of attack and defense techniques for reputation systems. ACM Computing Surveys (CSUR), 42(1), 1.

    Article  Google Scholar 

  • Holland, J.H. (2000). Emergence: from chaos to order. Oxford University Press.

  • Howe, J. (2006). The rise of crowdsourcing. Wired magazine, 14(6), 1–4.

    Google Scholar 

  • Hunter, A. (2013). Modelling uncertainty in persuasion. In International Conference on Scalable Uncertainty Management (pp. 57–70): Springer.

  • Iribarren, J., & Moro, E. (2009). Impact of human activity patterns on the dynamics of information diffusion. Physical Review Letters, 103(3).

  • Jøsang, A., Ismail, R., & Boyd, C. (2007). A survey of trust and reputation systems for online service provision. Decision support systems, 43(2), 618–644.

    Article  Google Scholar 

  • Kittur, A., Chi, E., Pendleton, B.A., Suh, B., & Mytkowicz, T. (2007). Power of the few vs. wisdom of the crowd: Wikipedia and the rise of the bourgeoisie. World wide web, 1(2), 19.

    Google Scholar 

  • Kittur, A., Smus, B., Khamkar, S., & Kraut, R.E. (2011). Crowdforge: Crowdsourcing complex work. In Proceedings of the 24th annual ACM symposium on User interface software and technology (pp. 43–52): ACM.

  • Kulkarni, A., Can, M., & Hartmann, B. (2012). Collaboratively crowdsourcing workflows with turkomatic. In Proceedings of the ACM 2012 conference on Computer Supported Cooperative Work (pp. 1003–1012): ACM.

  • Kulkarni, A.P., Can, M., & Hartmann, B. (2011). Turkomatic: automatic recursive task and workflow design for mechanical turk. In CHI’11 Extended Abstracts on Human Factors in Computing Systems (pp. 2053–2058): ACM.

  • Lerman, K. (2016). Information is not a virus, and other consequences of human cognitive limits. Future Internet, 8(2), 21.

    Article  Google Scholar 

  • Lessig, L. (1998). Open code and open societies: values of internet governance. Chi.-Kent L. Rev., 74, 1405.

    Google Scholar 

  • Liben-Nowell, D., Novak, J., Kumar, R., Raghavan, P., & Tomkins, A. (2005). Geographic routing in social networks. Proceedings of the National Academy of Sciences, 102(33), 11623–11628.

    Article  Google Scholar 

  • Lin, A.Y.-M., Huynh, A., Lanckriet, G., & Barrington, L. (2014). Crowdsourcing the unknown: the satellite search for genghis khan. PloS one, 9(12), e114046.

    Article  Google Scholar 

  • List, C., & Polak, B. (2010). Introduction to judgment aggregation. Journal of economic theory, 145(2), 441–466.

    Article  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.

    Article  Google Scholar 

  • Lupia, A., & McCubbins, M. (1998). The democratic dilemma: Can citizens learn what they need to know?: Cambridge University Press.

  • Mani, A., Rahwan, I., & Pentland, A. (2013). Inducing peer pressure to promote cooperation. Scientific reports, 3.

  • Mao, A., Mason, W., Suri, S., & Watts, D.J. (2016). An experimental study of team size and performance on a complex task. PloS one, 11(4), e0153048.

    Article  Google Scholar 

  • Medina, E. (2011). Cybernetic revolutionaries: technology and politics in Allende’s Chile. MIT Press.

  • Meier, P. (2015). Digital humanitarians. How Big Data Is Changing the Face of Humanitarian Response. CRC.

  • Mercier, H., & Sperber, D. (2011). Why do humans reason? arguments for an argumentative theory. Behavioral and brain sciences, 34(02), 57–74.

    Article  Google Scholar 

  • Mesoudi, A., Whiten, A., & Laland, K.N. (2006). Towards a unified science of cultural evolution. Behavioral and Brain Sciences, 29(04), 329–347.

    Google Scholar 

  • Minsky, M. (1988). Society of mind. Simon and Schuster.

  • Morozov, E. (2011). The Net Delusion: How not to liberate the world. Penguin.

  • Moulin, H., Brandt, F., Conitzer, V., Endriss, U., Lang, J., & Procaccia, A.D. (2016). Handbook of Computational Social Choice. Cambridge University Press.

  • Muchnik, L., Aral, S., & Taylor, S.J. (2013). Social influence bias: a randomized experiment. Science, 341(6146), 647–651.

    Article  Google Scholar 

  • Naroditskiy, V., Rahwan, I., Cebrian, M., & Jennings, N. (2012). Verification in referral-based crowdsourcing. PLoS ONE, 7(10), e45924.

    Article  Google Scholar 

  • Narodny, I. (1912). Marconi’s plans for the world. Technical World Magazine, 145–150.

  • Nisan, N., Roughgarden, T., Tardos, E., & Vazirani, V.V. (2007). Algorithmic game theory Vol. 1. Cambridge: Cambridge University Press.

    Book  Google Scholar 

  • Nowak, M.A., & Sigmund, K. (1998). Evolution of indirect reciprocity by image scoring. Nature, 393(6685), 573–577.

    Article  Google Scholar 

  • Parkes, D.C., & Wellman, M.P. (2015). Economic reasoning and artificial intelligence. Science, 349(6245), 267–272.

    Article  Google Scholar 

  • Pentland, A.S. (2013). Beyond the echo chamber. Harvard Business Review, 91 (11), 80–+.

  • Pickard, G., Pan, W., Rahwan, I., Cebrian, M., Crane, R., Madan, A., & Pentland, A. (2011). Time-critical social mobilization. Science, 334(6055), 509–512.

    Article  Google Scholar 

  • Piketty, T. (1999). The information-aggregation approach to political institutions. European Economic Review, 43(4), 791–800.

    Article  Google Scholar 

  • Plato (2015). First Alcibiades. CreateSpace Independent Publishing Platform.

  • Popoola, A., Krasnoshtan, D., Toth, A.-P., Naroditskiy, V., Castillo, C., Meier, P., & Rahwan, I. (2013). Information verification during natural disasters. In Proceedings of the 22nd international conference on World Wide Web companion (pp. 1029–1032): International World Wide Web Conferences Steering Committee.

  • Procaccia, A.D. (2013). Cake cutting: not just child’s play. Communications of the ACM, 56(7), 78–87.

    Article  Google Scholar 

  • Rahwan, I. (2008). Mass argumentation and the Semantic Web. Journal of Web Semantics, 6(1), 29–37.

    Article  Google Scholar 

  • Rahwan, I., Banihashemi, B., Reed, C., Walton, D., & Abdallah, S. (2011). Representing and classifying arguments on the semantic web. The Knowledge Engineering Review, 26(04), 487–511.

    Article  Google Scholar 

  • Rahwan, I., Dsouza, S., Rutherford, A., Naroditskiy, V., McInerney, J., Venanzi, M., Jennings, N.R., & Cebrian, M. (2013). Global manhunt pushes the limits of social mobilization. IEEE Computer, 46(4).

  • Rahwan, I., & Larson, K. (2008a). Mechanism design for abstract argumentation. In Padgham, L., Parkes, D., Mueller, J., & Parsons, S. (Eds.) 7th International Joint Conference on Autonomous Agents & Multi Agent Systems, AAMAS’2008, Estoril, Portugal (pp. 1031–1038).

  • Rahwan, I., & Larson, K. (2008b). Pareto optimality in abstract argumentation. In Fox, D., & Gomes, C. (Eds.) Proceedings of the 23rd AAAI Conference on Artificial Intelligence (AAAI-2008), Menlo Park CA, USA.

  • Rahwan, I., Larson, K., & Tohmé, F. (2009a). A characterisation of strategy-proofness for grounded argumentation semantics. In Proceedings of the 21st International Joint Conference on Artificial Intelligence (IJCAI) (pp. 251–256).

  • Rahwan, I., Simari, G.R., & van Benthem, J. (2009b). Argumentation in artificial intelligence Vol. 47: Springer.

  • Rahwan, I., & Tohmé, F. (2010). Collective argument evaluation as judgement aggregation. In Proceedings of the 9th International Conference on Autonomous Agents and Multiagent Systems: volume 1-Volume 1, pages 417–424. International Foundation for Autonomous Agents and Multiagent Systems.

  • Rahwan, I., Zablith, F., & Reed, C. (2007). Laying the foundations for a world wide argument web. Artificial Intelligence, 171(10–15), 897–921.

    Article  Google Scholar 

  • Read, D. (2001). Intrapersonal dilemmas. Human Relations, 54(8), 1093–1117.

    Article  Google Scholar 

  • Reagle, J.M. (2010). Good faith collaboration: The culture of Wikipedia. MIT Press.

  • Rienstra, T., Thimm, M., & Oren, N. (2013). Opponent models with uncertainty for strategic argumentation. In IJCAI.

  • Rutherford, A., Cebrian, M., Dsouza, S., Moro, E., Pentland, A., & Rahwan, I. (2013a). The limits of social mobilization. PNAS, 110(16), 6281–6286.

    Article  Google Scholar 

  • Rutherford, A., Cebrian, M., Rahwan, I., Dsouza, S., McInerney, J., Naroditskiy, V., Venanzi, M., Jennings, N., deLara, J., Wahlstedt, E., & Miller, S. (2013b). Targted social mobilisation in a global manhunt. PLOS ONE, (in press).

  • Sakama, C., Caminada, M., & Herzig, A. (2015). A formal account of dishonesty. Logic Journal of IGPL, 23(2), 259–294.

    Article  Google Scholar 

  • Schelling, T.C. (2006). Micromotives and macrobehavior. WW Norton & Company.

  • Sigmund, K., De Silva, H., Traulsen, A., & Hauert, C. (2010). Social learning promotes institutions for governing the commons. Nature, 466(7308), 861–863.

    Article  Google Scholar 

  • Stefanovitch, N., Alshamsi, A., Cebrian, M., & Rahwan, I. (2014). Error and attack tolerance of collective problem solving: The darpa shredder challenge. EPJ Data Science, 3(13).

  • Strogatz, S.H. (2014). Nonlinear dynamics and chaos: with applications to physics, biology, chemistry, and engineering. Westview press.

  • Taleb, N.N. (2012). Antifragile: Things that gain from disorder, Vol. 3: Random House Incorporated.

  • Tang, J., Cebrian, M., Giacobe, N., Kim, H., Kim, T., & Wickert, D. (2011). Reflecting on the DARPA Red Balloon Challenge. Communications of the ACM, 54(4), 78–85.

    Article  Google Scholar 

  • Tausczik, Y.R., Kittur, A., & Kraut, R.E. (2014). Collaborative problem solving: a study of mathoverflow. In Proceedings of the 17th ACM conference on Computer supported cooperative work & social computing (pp. 355–367): ACM.

  • Thagard, P. (2002). Coherence in thought and action. MIT press.

  • Tomasello, M. (2009). Why we cooperate. MIT press.

  • Trivers, R.L. (1971). The evolution of reciprocal altruism. Quarterly review of biology, 35–57.

  • Weng, L., Flammini, A., Vespignani, A., & Menczer, F. (2012). Competition among memes in a world with limited attention. Scientific reports, 2.

  • Wiener, N., & et al (1948). Cybernetics. Hermann Paris.

  • Wolfers, J., & Zitzewitz, E. (2004). Prediction markets. The Journal of Economic Perspectives, 18(2), 107–126.

    Article  Google Scholar 

  • Wu, T., & Vietor, M. (2011). The master switch: The rise and fall of information empires. Vintage Books.

  • Yoeli, E., Hoffman, M., Rand, D.G., & Nowak, M.A. (2013). Powering up with indirect reciprocity in a large-scale field experiment. Proceedings of the National Academy of Sciences, 110(Supplement 2), 10424–10429.

    Article  Google Scholar 

  • Young, H.P. (2001). Individual strategy and social structure: An evolutionary theory of institutions. Princeton University Press.

  • Zhang, H., Law, E., Miller, R., Gajos, K., Parkes, D., & Horvitz, E. (2012). Human computation tasks with global constraints. In Proceedings of the SIGCHI Conference on Human Factors in Computing Systems (pp. 217–226): ACM.

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Correspondence to Iyad Rahwan.

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This article is based on a keynote I delivered at the European Network for Social Intelligence (SINTELNET) workshop on Arguing on the Web 2.0, Amsterdam, under the title “Beyond Web Argumentation: Towards Scalable Civics.” It should therefore be read as a personal reflection, based on projects in which I was involved, rather than an exhaustive survey.

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Rahwan, I. Towards Scalable Governance: Sensemaking and Cooperation in the Age of Social Media. Philos. Technol. 30, 161–178 (2017).

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