Reimagining the way society organizes, cooperates, and governs itself.

Over millennia, humans have invented various forms of social organization to govern themselves, ranging from tribes and clubs, to technocracies and democracies. These institutions enabled us to scale up our ability to coordinate, cooperate, exchange information, and make decisions. Today, instant connectivity, online social networks, pervasive algorithms, crowdsourcing, and big data can help us improve our existing cooperative institutions. More significantly, however, these technologies invite us to completely reimagine the ways in which societies organize, cooperate and govern. Our group aims to (1) understand how technology is reshaping the nature of human cooperation; and (2) imagine and design radically new ways of scaling up cooperation.

Selected Projects

Ethics of Autonomous Vehicles

Adoption of self-driving, Autonomous Vehicles (AVs) promises to dramatically reduce the number of traffic accidents, but some inevitable accidents will require AVs to choose the lesser of two evils, such as running over a pedestrian on the road or the sidewalk. Defining the algorithms to guide AVs confronted with such moral dilemmas is a challenge, and manufacturers and regulators will need psychologists to apply methods of experimental ethics to these situations.

Scientific writings:

  • J. F. Bonnefon, A. Shariff, I. Rahwan (2016). The Social Dilemma of Autonomous Vehicles. Science. 352(6293):1573-1576.

  • Selected Media: New York Times (1), New York Times (2), Washington Post (1), Wall Street Journal, Time, Independent (1), Guardian, CBS News, LA Times, Forbes, Newsweek, CBC (Canada), ABC (Australia), Le Monde (FR), El Pais (ES), Science, Scientific American, New Scientist, PBS NOVA Next, PBS, Wired, Huffington Post, MIT News, Independent (2), Washington Post (2), Washington Post (3), BBC World Service (live interview), Huffington Post (live interview), New York Magazine, Popular Science, MIT Technology Review

    Moral Machine

    The Moral Machine is a platform for gathering a human perspective on moral decisions made by machine intelligence, such as self-driving cars. We generate moral dilemmas, where a driverless car must choose the lesser of two evils, such as killing two passengers or five pedestrians. As an outside observer, people judge which outcome they think is more acceptable. They can then see how their responses compare with other people. If they are feeling creative, people can also design their own scenarios, for others to view, share, and discuss.
    The platform can be visited at http://moralmachine.mit.edu

    Selected Media: New York Times, Guardian, The Times, Newsweek, LA Times, CBC, Der Spiegel (DE), Le Monde (FR), La Repubblica (IT), El Pais (ES) (1), El Pais (ES) (2), Yle (FI), Nieuwsblad (NL), The Straits Times, IB Times, PBS, Scientific American, Popular Science, TechCrunch, New Scientist, Wired, Huffington Post, Slate, CNET, The Next Web, Greenwire, TechTarget

    Nightmare Machine

    Since centuries, and across geographies, religions, and cultures, people have tried to innovate ways of scaring each other. Creating a visceral emotion such as fear remains one of the cornerstones of human creativity. This challenge is especially important in an age in which we wonder what the limits of artificial intelligence are -- in this case, can machines learn to scare us? Towards this goal, we present Haunted Faces and Haunted Places: computer-generated scary imagery powered by deep learning algorithms.
    The platform can be visited at http://nightmare.mit.edu

    Selected Media: Washington Post, The Atlantic, Forbes, BBC, NPR, CNET, NBC News, Vice

    Promoting Cooperation through Peer Pressure

    Cooperation in a large society of self-interested individuals is notoriously difficult to achieve when the externality of one individual's action is spread thin and wide on the whole society (e.g. in the case of pollution). We introduce a new approach to achieving global cooperation by localizing externalities to one's peers in a social network, thus leveraging the power of peer-pressure to regulate behavior. Global cooperation becomes more like local cooperation.

    Scientific writings:

  • A. Mani, I. Rahwan, and A. Pentland (2013). Inducing Peer Pressure to Promote Cooperation. Scientific Reports. 3(1735) doi:10.1038/srep01735.
  • Human-Machine Cooperation

    Since Alan Turing envisioned Artificial Intelligence (AI), a major driving force behind technical progress has been competition with human cognition (e.g. beating humans in Chess or Jeopardy!). Less attention has been given to developing autonomous machines that learn to cooperate with humans. Cooperation does not require sheer computational power, but relies on intuition, and pre-evolved dispositions toward cooperation, common-sense mechanisms that are difficult to encode in machines. We develop state-of-the-art machine-learning algorithms that cooperate with people and other machines at levels that rival human cooperation in two-player repeated games.

    Scientific writings:

  • F. Ishowo-Oloko, J. Crandall, M. Cebrian, S. Abdallah, I. Rahwan (2014). Learning in Repeated Games: Human Versus Machine. arXiv preprint. arXiv:1404.4985 [cs.CY].
  • Corruption-Resistant Cooperation: Institutions vs. Crowds

    How to best govern society and promote cooperation is a centuries-old debate: is cooperation best maintained by a central authority, or is it better handled by more decentralized forms of governance? Using mathematical models, we show that when some actors can bribe a powerful centralized authority, they can completely undermine cooperation in society. Counterintuitively, a weaker centralized authority is more effective because it allows peer punishment to restore cooperation in the presence of corruption. Our results help explain why citizen participation is a fundamental necessity for policing the commons.

    Scientific writings:

  • S. Abdallah, R. Sayed, I. Rahwan, B. LeVeck, M. Cebrian, A. Rutherford, J. Fowler (2014). Corruption Drives the Emergence of Civil Society. Journal of the Royal Society Interface. 11(93).

  • Selected Media: Anti-Corruption Research Network (part of Transparency International)

    Cognitive Limits of Social Networks

    There is a wide cultural belief in the power of the Web and social media as enablers of collective intelligence. They help us spread information rapidly, and learn useful information from each other. But there are fundamental limits to the capabilities of those networks. Understanding these limits is essential to improving social media and allowing society to make the most of it.

    Scientific writings:

  • I. Rahwan, D. Krasnoshtan, A. Shariff, J. F. Bonnefon (2014). Analytical reasoning task reveals limits of social learning in networks. Journal of the Royal Society Interface. 11(93).

  • Selected Media: Royal Society, Daily Mail, Live Science, Phys.org

    Crowdsourcing Under Attack

    The Internet has unleashed the capacity for planetary-scale collective problem solving (also known as crowdsourcing). However, the very openness of crowdsourcing makes it vulnerable to sabotage by rogue or competitive actors. To explore the effect of errors and sabotage on the performance of crowdsourcing, we analyze data from the DARPA Shredder Challenge, a prize competition for exploring methods to reconstruct documents shredded by a variety of paper shredding techniques.

    Scientific writings:

  • N. Stefanovitch, A. Alshamsi, M. Cebrian, I. Rahwan (2014). Error and attack tolerance of collective problem solving: The DARPA Shredder Challenge. EPJ Data Science. vol 3, no 13, pages 1-27.

  • Selected Media: Nautilus, Backchannel, UCSD Press Release

    Crowdsourcing a Manhunt

    People often say that we live in a small world. In a brilliant experiment, legendary social psychologist Stanley Milgram proved the six degrees of separation hypothesis: that everyone is six or fewer steps away, by way of introduction, from any other person in the world. But how far are we, in time, from anyone on earth? Our team won the Tag Challenge, showing it is possible to find a person, using only his or her mug shot, within 12 hours.

    Scientific writings:

  • A. Rutherford et al (2013). Targeted social mobilization in a global manhunt. PLOS ONE 8 (9): e74628.
  • I. Rahwan et al (2013). Global Manhunt Pushes the Limits of Social Mobilization. Computer, vol. 46, no. 4, pp. 68-75.

  • Selected Media: New Scientist, Nature, Scientific American, Economist, New Scientist, Nextgov, MIT Technology Review

    The Red Balloon Challenge

    In 2009, DARPA launched the Network Challenge, to explore the roles the Internet and social networking play in the timely communication, wide-area team-building, and urgent mobilization required to solve broad-scope, time-critical problems. The challenge was to be the first to locate 10 moored, 8-foot, red weather balloons at 10 random locations in the continental United States. A team from MIT won by locating all balloons in under 9 hours. We helped analyze the factors behind the team's success. We then quantified the limits of this kind of mobilization, and introduced techniques for improving information verification in mass collaboration.

    Scientific writings:

  • A. Rutherford, M. Cebrian, S. Dsouza, E. Moro, A. Pentland, and I. Rahwan (2013). Limits of Social Mobilization. Proceedings of the National Academy of Sciences, vol. 110 no. 16 pp. 6281-6286
  • V. Naroditskiy, I. Rahwan, M. Cebrian, N. R. Jennings (2012). Verification in Referral-Based Crowdsourcing. PLOS ONE 7(10): e45924.
  • G. Pickard, W. Pan, I. Rahwan, M. Cebrian, R. Crane, A. Madan, A. Pentland (2011). Time-Critical Social Mobilization. Science. Vol. 334 no. 6055 pp. 509-512.
  • H. Chen, I. Rahwan, and M. Cebrian (2016). Bandit strategies in social search: the case of the DARPA red balloon challenge. EPJ Data Science, 2016 5:20
  • M. Cebrian, L. Coviello, A. Vattani, and P. Voulgaris (2012). Finding red balloons with split contracts: robustness to individuals' selfishness. Proceedings of the 44th annual ACM Symposium on Theory of Computing (STOC '12). 775-788.

  • Selected Media: MSNBC, Popular Mechanics, Science News, NBC News, ABC, La Repubblica, ACM, Red Orbit, Science 2.0, Science Daily, MIT News

    Mapping Social Influence: Beyond Contagion

    Social networks shape our mood, emotions, and behavior. New unobtrusive sensing techniques (wearable sensors, mobile phones, social media), allow us to study these social dynamics in the real world with unprecedented detail, complementing old methods like lab studies and surveys. We discovered that while some behaviors spread on social networks like a virus (you catch the blues from your friends), other behaviors work in the opposite direction, where our behavior changes to complement the behavior of others. Moreover, our individual personality traits affect how these processes work. These findings inform potential interventions designed to improve societal well-being.

    Scientific writings:

  • A. Alshamsi, F. Pianesi, B. Lepri, A. Pentland, and I. Rahwan (2016). Network Diversity and Affect Dynamics: The Role of Personality Traits. PLOS ONE, 11(4), e0152358.
  • A. Alshamsi, F. Pianesi, B. Lepri, A. Pentland, and I. Rahwan (2015). Beyond Contagion: Reality Mining Reveals Complex Patterns of Social Influence. PLOS ONE 10(8), e0135740.
  • A. Alshamsi, E. Awad, M. Almehrezi, V. Babushkin, P.J. Chang, Z. Shoroye, A.P. Tóth, and I. Rahwan (2015). Misery loves company: happiness and communication in the city. EPJ Data Science. 4(1), pp.1-12.
  • Ethics of Autonomous Vehicles

    Ethics of Autonomous Vehicles
     

    Moral Machine

    Moral Machine
     

    Moral Machine

    Nightmare Machine
     

    Promoting Cooperation through Peer Pressure

    Promoting Cooperation
    through Peer Pressure

    Human-Machine Cooperation

    Human-Machine Cooperation
     

    Corruption-Resistant Cooperation: Institutions vs. Crowds

    Corruption-Resistant Cooperation:
    Institutions vs. Crowds

    Cognitive Limits of Social Networks

    Cognitive Limits of Social Networks
     

    Crowdsourcing Under Attack

    Crowdsourcing Under Attack
     

    Crowdsourcing a Manhunt

    Crowdsourcing a Manhunt
     

    The Red Balloon Challenge

    The Red Balloon Challenge
     

    Mapping Social Influence: Beyond Contagion

    Mapping Social Influence:
    Beyond Contagion

    Publications

    Selected publications below; full list at Iyad Rahwan's homepage or Scholar profile

    J. F. Bonnefon, A. Shariff, I. Rahwan (2016). The Social Dilemma of Autonomous Vehicles. Science. 352(6293):1573-1576.
    [Paper] [Selected Media: New York Times, Wall Street Journal, Washington Post, Scientific American, Time, CNN, The Guardian, Gizmag, Wired, LA Times, IEEE Spectrum, Forbes, Washington Post, BBC Radio, Huffington Post (live interview), New York Magazine, Independent, MIT Technology Review, Popular Science]

    A. Alshamsi, F. Pianesi, B. Lepri, A. Pentland, I. Rahwan (2015). Beyond contagion: Reality mining reveals complex patterns of social influence. PLOS ONE. 10(8): e0135740.
    [Published Version (open access)]

    E. Awad, R. Booth, F. Tohme, I. Rahwan (2015). Judgment Aggregation in Multi-Agent Argumentation. Journal of Logic and Computation. (in press).
    [PDF Preprint] [Published Version]

    A. Alshamsi, E. Awad, M. Almehrezi, V. Babushkin, P.-J. Chang, Z. Shoroye, A.-P. Toth, I. Rahwan (2015). Misery Loves Company: Happiness and Communication in the City. EPJ Data Science. 4:7.
    [Published Version (open access)]

    N. Stefanovitch, A. Alshamsi, M. Cebrian, I. Rahwan (2014). Error and attack tolerance of collective problem solving: The DARPA Shredder Challenge. EPJ Data Science. vol 3, no 13, pages 1-27.
    [Paper] [Videos: Puzzle2, Puzzle4] [Media: Nautilus, UCSD Press Release, Backchannel]

    I. Rahwan, D. Krasnoshtan, A. Shariff, J. F. Bonnefon (2014). Analytical reasoning task reveals limits of social learning in networks. Journal of the Royal Society Interface. 11(93).
    [Published Version] [Selected Media: Royal Society, Daily Mail, Live Science, Phys.org, Interview with Azim]

    S. Abdallah, R. Sayed, I. Rahwan, B. LeVeck, M. Cebrian, A. Rutherford, J. Fowler (2014). Corruption Drives the Emergence of Civil Society. Journal of the Royal Society Interface. 11(93).
    [arXiv preprint] [Published Version] [Media: Anti-Corruption Research Network (part of Transparency International)]

    A. Rutherford, M. Cebrian, I. Rahwan, S. Dsouza, J. McInerney, V. Naroditskiy, M. Venanzi, N. R. Jennings, J.R. deLara, E. Wahlstedt, S. U. Miller (2013). Targeted social mobilization in a global manhunt. PLOS ONE 8(9): e74628
    [Paper] [Selected Media: MIT Technology Review, New Scientist, Nature, Scientific American]

    A. Rutherford, M. Cebrian , S. Dsouza, E. Moro, A. Pentland, and I. Rahwan (2013). Limits of Social Mobilization. Proceedings of the National Academy of Sciences, vol. 110 no. 16 pp. 6281-6286
    [Paper] [Selected Media: NBC News, ABC, La Repubblica, Arabian Gazette, Gulf Today, The National]

    A. Mani, I. Rahwan, and A. Pentland (2013). Inducing Peer Pressure to Promote Cooperation. Scientific Reports, 3(1735) doi:10.1038/srep01735
    [Paper] [Media: Scientific American]

    I. Rahwan, S. Dsouza, A. Rutherford, V. Naroditskiy, J. McInerney, M. Venanzi, N. R. Jennings, M. Cebrian (2013). Global Manhunt Pushes the Limits of Social Mobilization. Computer, vol. 46, no. 4, pp. 68-75.
    [PDF Preprint] [Selected Media: The Economist, Nextgov, New Scientist, Popular Science, The National, Vision (cover story)]

    S. Dsouza, Y. Gal, P. Pasquier, S. Abdallah, and I. Rahwan (2013). Reasoning about Goal Revelation in Human Negotiation. IEEE Intelligent Systems. vol. 28, no. 2, pp. 74-80.
    [PDF]

    V. Naroditskiy, I. Rahwan, M. Cebrian, N. R. Jennings (2012). Verification in Referral-Based Crowdsourcing. PLOS ONE 7(10): e45924.
    [Paper] [Selected Media: ACM, Red Orbit, Science 2.0, Science Daily]

    G. Pickard, W. Pan, I. Rahwan, M. Cebrian, R. Crane, A. Madan, A. Pentland (2011). Time-Critical Social Mobilization. Science. Vol. 334 no. 6055 pp. 509-512.
    [Paper] [Selected Media: MSNBC, Popular Mechanics, MIT News, Science News]

    Team

    Director

    Iyad Rahwan

    Iyad Rahwan


    Research Consigliere

    Iyad Rahwan

    Manuel Cebrian


    Post-Docs & Research Scientists

    Lijun Sun

    Lijun Sun

    Yves-Alexandre de Montjoye

    Yves-Alexandre de Montjoye

    Pınar Yanardağ

    Pınar Yanardağ

    Nick Obradovich

    Nick Obradovich

    Andres Abeliuk

    Andres Abeliuk


    Graduate Students

    Morgan Frank

    Morgan Frank

    Edmond Awad

    Edmond Awad

    Sohan Dsouza

    Sohan Dsouza

    Richard Kim

    Richard Kim

    Neil Gaikwad

    Neil Gaikwad

    Bjarke Felbo

    Bjarke Felbo


    Visiting Scientists on Extended Stints

    Antonio Fernández Anta

    Antonio Fernández Anta

    Pai-Ju Chang

    Pai-Ju Chang

    Hye-Jin Youn

    Hye-Jin Youn


    Past Members

    Lorenzo Coviello

    Lorenzo Coviello


    Administrative Contact

    Contact

    Scalable Cooperation, MIT Media Lab
    E14-574K-A
    75 Amherst Street
    Cambridge, MA 02139, USA

    scalablecontactmedia.mit.edu

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