Iyad Rahwan
Iyad Rahwan | |
---|---|
إياد رهوان | |
Born | 1978 |
Alma mater | University of Melbourne |
Scientific career | |
Fields | Computational Social Science, Artificial Intelligence, Ethics, Cognitive Science, Game Theory, Crowdsourcing, |
Institutions | MIT |
Doctoral advisor | Liz Sonenberg |
Other academic advisors | Alex Pentland |
Website | https://rahwan.me/ |
Iyad Rahwan (Arabic: إياد رهوان), is a Syrian-Australian scientist. He is an associate professor of Media Arts & Sciences at the MIT Media Lab, and is the director and principal investigator of its Scalable Cooperation group.[1] Rahwan's work lies at the intersection of the computer and social sciences, where he has investigated topics in computational social science, collective intelligence, large-scale cooperation, and the social aspects of artificial intelligence.[2]
Biography
Rahwan was born in Aleppo, Syria. He earned an Information Systems PhD in 2005 from the University of Melbourne. As an assistant and then associate professor in Computing and Information Science at MIT-partnered Masdar Institute of Science and Technology, Rahwan investigated scalable social mobilization's possibilities, limits, and challenges in various contexts by analyzing data from the 2009 DARPA Network Challenge,[3][4] the DARPA Shredder Challenge 2011,[5][6] and the 2012 US State Department Tag Challenge.[7][8] In 2015, Rahwan started the Scalable Cooperation Group at the MIT Media Lab, where he is the AT&T Career Development Professor and an Associate Professor of Media Arts & Sciences,[9] as well as an affiliate faculty at the MIT Institute of Data, Systems and Society.[10]
Society-in-the-Loop
Rahwan coined the term Society-in-the-loop as a conceptual extension of Human-in-the-Loop systems.[11] Whereas HITL systems embed an individual's judgement into a narrowly defined control system, SITL is more about embedding the judgement of society as a whole in to system. He cites an AI that controls billions of self driving cars (and decides who is worth saving in certain cases), or a news filtering algorithm with the potential to influence the ideology of millions of citizens (that decides what content the users shall see). Rahwan highlights the importance of articulating ethics and social contracts in ways that machines can understand, towards building new governance algorithms.[12]
Morality and Machines
Ethics of Autonomous Vehicles
Rahwan is one of the first to consider the problem of self autonomous vehicles as an ethical dilemma. His 2016 paper, The Social Dilemma of Autonomous Vehicles, showed that people approved of utilitarian autonomous vehicles, and wanted others to purchase these vehicles, but they themselves would prefer to ride in an autonomous vehicle that protected its passenger at all costs, and would not use self-driving vehicles if utilitarianism was imposed on them by law. Thus the paper concludes the regulation of utilitarian algorithms could paradoxically increase casualties by driving by inadvertently postponing the adoption of a safer technology.[13] The paper spurred lots of coverage about the role of ethics in the creation of artificially intelligent driving systems.[14][15][16][17][18][19][20]
Moral Machine
Moral Machine[21] is an online platform that generates ethical dilemma scenarios faced by hypothetical autonomous machines, allowing visitors to assess the scenarios and vote on the most morally acceptable between two unavoidable harm outcomes. As of April 2017, the system has collected 28 million decisions from over 3 million visitors. [22] The presented scenarios are often variations of the trolley problem, and the information collected would be used for further research regarding the decisions that machine intelligence might have to make in the future.[23][24][25]
Cooperating with Machines
Rahwan's study of human-machine cooperation showed that providing a medium of communication can result in an algorithm learning to cooperate with its human partner faster and more effectively than a human in strategic games.[26][27]
Other projects
The Tag Challenge
Rahwan led the winning team in the 2012 US State Department Tag Challenge, using crowdsourcing and a referral-incentivizing reward mechanism (similar to the one used in the 2009 DARPA Network Challenge) to locate individuals in European and American cities within 12 hours each, given only their photographic portraits.[28][29][30]
The Nightmare Machine
The Nightmare Machine,[31] developed under Rahwan's guidance, creates computer generated imagery powered by deep learning algorithms to learn from human feedback and generate a visual approximation of what humans might find "scary".[32][33]
References
- ^ "Group Overview ‹ Scalable Cooperation – MIT Media Lab".
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(help) - ^ "Iyad Rahwan - TEDxCambridge".
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(help) - ^ "How Social Media Mobilizes Society - LiveScience".
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(help) - ^ "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".
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(help) - ^ "How Crowdsourcing Turned On Me - Nautilus".
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(help) - ^ Stefanovitch, Nicolas; Alshamsi, Aamena; Cebrian, Manuel; Rahwan, Iyad (2014). "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". EPJ Data Science. 3. doi:10.1140/epjds/s13688-014-0013-1.
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(help) - ^ "Crowdsourcing in manhunts can work : Nature News & Comment".
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(help) - ^ Rutherford, Alex; Cebrian, Manuel; Rahwan, Iyad; Dsouza, Sohan; McInerney, James; Naroditskiy, Victor; Venanzi, Matteo; Jennings, Nicholas R.; Delara, J. R.; Wahlstedt, Eero; Miller, Steven U. (2013). "A. Rutherford et al (2013). Targeted social mobilization in a global manhunt. PLOS ONE 8 (9): e74628". PLoS ONE. 8 (9): e74628. Bibcode:2013PLoSO...874628R. doi:10.1371/journal.pone.0074628. PMID 24098660.
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(help)CS1 maint: unflagged free DOI (link) - ^ "Person Overview ‹ Iyad Rahwan – MIT Media Lab".
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(help) - ^ "Iyad Rahwan – IDSS".
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(help) - ^ "Society in the Loop Artificial Intelligence »".
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(help) - ^ "Society-in-the-loop".
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(help) - ^ "J. F. Bonnefon, A. Shariff, I. Rahwan (2016). The Social Dilemma of Autonomous Vehicles. Science. 352(6293):1573-1576".
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(help) - ^ "World Forum discuses how self-driving cars will make life or death decisions".
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(help) - ^ "Should Your Driverless Car Hit a Pedestrian to Save Your Life - The New York Times".
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(help) - ^ "Whose Life Should Your Car Save? - The New York Times".
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(help) - ^ "TedxCambridge: The social dilemma of driverless cars".
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(help) - ^ "Save the driver or save the crowd? Scientists wonder how driverless cars will 'choose' - The Washington Post".
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(help) - ^ "Driverless Cars Pose Difficult Ethical Question - Time.com".
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(help) - ^ "Driverless car safety revolution could be scuppered by moral dilemma - The Independent".
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(help) - ^ "Moral Machine".
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(help) - ^ "AI & Society at the Berkman Center".
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(help) - ^ "Ethical dilemma on four wheels: How to decide when your self-driving car should kill you - LA Times".
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(help) - ^ "For driverless cars, a moral dilemma: Who lives or dies? - Associated Press".
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(help) - ^ "Ethical dilemma on four wheels: How to decide when your self-driving car should kill you".
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(help) - ^ "[arXiv:1703.06207] Cooperating with Machines". arXiv:1703.06207.
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(help) - ^ "AI Can Beat Us at Poker—Now Let's See If It Can Work with Us - MIT Technology Review".
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(help) - ^ "Crowdsourcing in Manhunts Can Work - Scientific American".
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(help) - ^ "Nowhere to hide: The next manhunt will be crowdsourced - New Scientist".
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(help) - ^ "Six degrees of mobilisation - The Economist".
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(help) - ^ "THe Nightmare Machine".
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(help) - ^ "Researchers Build 'Nightmare Machine' : The Two-Way : NPR".
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(help) - ^ "Clinton, Trump, the White House too, terrifyingly transformed by MIT's 'Nightmare Machine' - The Washington Post".
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