Iyad Rahwan

Iyad Rahwan (Arabic: إياد رهوان‎), is a Syrian-Australian scientist. He is the director of the Center for Humans and Machines at the Max Planck Institute for Human Development[1] and an associate professor of Media Arts & Sciences at the MIT Media Lab.[2] 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.[3]

Iyad Rahwan
Born1978
Aleppo, Syria
Alma materUniversity of Melbourne
Scientific career
FieldsComputational Social Science, Artificial Intelligence, Ethics, Cognitive Science, Game Theory, Crowdsourcing,
InstitutionsMax Planck Institute for Human Development
Doctoral advisorLiz Sonenberg
Other academic advisorsAlex Pentland
Websitehttps://rahwan.me/

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,[4][5] the DARPA Shredder Challenge 2011,[6][7] and the 2012 US State Department Tag Challenge.[8][9][10] 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,[11] as well as an affiliate faculty at the MIT Institute of Data, Systems and Society.[12] Since 2019 Rahwan is a director of the Max Planck Institute for Human Development in Berlin, where he founded and directs the Center for Humans and Machines.[13]

Machine Behavior

Together with Manuel Cebrian and Nick Obradovich, Rahwan spearheaded an effort to establish the field of Machine Behavior.[14] This field is concerned with the scientific study of Artificial Intelligence systems, not as engineering artifacts, but as a class of actors with particular behavioral patterns and ecology. This field overlaps with, but is distinct from, computer science and robotics. It treats machine behaviour empirically, in the same way that ethology and behavioral ecology study animal behavior without a full understanding of the bio-chemical mechanisms. The contours and fundamental research questions in the field of Machine Behavior were outlined by Rahwan, Obradovich and Cebrian, together with twenty co-authors from across the computational and behavioral sciences, in an article in the journal Nature.[15].

Society-in-the-Loop

Rahwan coined the term Society-in-the-loop as a conceptual extension of Human-in-the-Loop systems.[16][17] 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.[18]

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.[19] The paper spurred lots of coverage about the role of ethics in the creation of artificially intelligent driving systems.[20][21][22][23][24][25][26]

Moral Machine

Moral Machine[27] 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. The presented scenarios are often variations of the trolley problem[28][29][30]. As of December 2017, the platform has collected 40 million decisions from millions of visitors from 233 countries and territories. Analysis of the data showed broad differences in relative preferences among different countries, and correlations between these preferences and various national metrics [31].

Cooperating with Machines

Together with Jacob Crandall and others, Rahwan studied human-machine cooperation by exploring how state-of-the-art reinforcement learning algorithms perform when playing repeated games against humans. The authors 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 these strategic games.[32][33][34]

AI and the Future of Work

Together with his student Morgan Frank and collaborators, Rahwan explored the relationship between city size and the potential impact of Artificial Intelligence and automation on employment. They used a variety of estimates of the risk of automation of different jobs.[35][36] Their main finding is that smaller cities may experience greater impact due to automation.[37] Related work explores the polarization of the US labor market, due to the underlying polarized structure of workplace skills.

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.[38][39][40]

The Nightmare Machine

The Nightmare Machine,[41] 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".[42][43]

References
  1. "New Director: Iyad Rahwan's research focuses on the societal challenges of digitization | Max Planck Institute for Human Development". www.mpib-berlin.mpg.de. Retrieved 2019-06-20.
  2. "Iyad Rahwan". Iyad Rahwan. Retrieved 2019-06-20.
  3. "Iyad Rahwan - TEDxCambridge".
  4. "How Social Media Mobilizes Society - LiveScience".
  5. Rutherford, A.; Cebrian, M.; Dsouza, S.; Moro, E.; Pentland, A.; Rahwan, I. (2013). "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. 110 (16): 6281–6286. doi:10.1073/pnas.1216338110. PMC 3631633. PMID 23576719.
  6. "How Crowdsourcing Turned On Me - Nautilus". 2014-10-23.
  7. 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. 3. doi:10.1140/epjds/s13688-014-0013-1.
  8. Ball, Philip (2013). "Crowdsourcing in manhunts can work : Nature News & Comment". Nature. doi:10.1038/nature.2013.12867.
  9. 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). "Targeted Social Mobilization in a Global Manhunt". PLoS ONE. 8 (9): e74628. arXiv:1304.5097. Bibcode:2013PLoSO...874628R. doi:10.1371/journal.pone.0074628. PMC 3786994. PMID 24098660.
  10. Rahwan, Iyad; Dsouza, Sohan; Rutherford, Alex; Naroditskiy, Victor; McInerney, James; Venanzi, Matteo; Jennings, Nicholas R.; Cebrian, Manuel (April 2013). "Global Manhunt Pushes the Limits of Social Mobilization" (PDF). Computer. 46 (4): 68–75. doi:10.1109/mc.2012.295. ISSN 0018-9162.
  11. "Person Overview ‹ Iyad Rahwan – MIT Media Lab".
  12. "Iyad Rahwan – IDSS".
  13. "Humans and Machines | Max Planck Institute for Human Development". www.mpib-berlin.mpg.de. Retrieved 2019-06-20.
  14. McKendrick, Joe. "Artificial Intelligence Is Now Far Too Big To Be Limited To Computer Science". Forbes.
  15. Rahwan, Iyad; Obradovich, Nick; Bongard, Josh; Bonnefon, Jean-François; Breazeal, Cynthia; Crandall, Jacob W.; Bonnefon, Jean-François; Christakis, Nicholas A.; Iain D., Couzin; Jackson, Matthew O.; Jennings, Nicholas R.; Kamar, Ece; Kloumann, Isabel M.; Larochelle, Hugo; Lazer, David; McElreath, Richard; Mislove, Alan; Parkes, David C.; Pentland, Alex; Roberts, Margaret E.; Shariff, Azim; Tenenbaum, Joshua B.; Wellman, Michale (24 April 2019). "Machine Behaviour". Nature. 568 (7753): 477–486. doi:10.1038/s41586-019-1138-y. PMID 31019318.
  16. "Society in the Loop Artificial Intelligence »".
  17. Rahwan, Iyad (2018-03-01). "Society-in-the-loop: programming the algorithmic social contract". Ethics and Information Technology. 20 (1): 5–14. arXiv:1707.07232. doi:10.1007/s10676-017-9430-8. ISSN 1388-1957.
  18. "Society-in-the-loop". 2016-08-12.
  19. Bonnefon, J.-F.; Shariff, A.; Rahwan, I. (2016). "J. F. Bonnefon, A. Shariff, I. Rahwan (2016). The Social Dilemma of Autonomous Vehicles". Science. 352 (6293): 1573–1576. arXiv:1510.03346. Bibcode:2016Sci...352.1573B. doi:10.1126/science.aaf2654. PMID 27339987.
  20. "World Forum discuses how self-driving cars will make life or death decisions".
  21. Markoff, John (2016-06-23). "Should Your Driverless Car Hit a Pedestrian to Save Your Life - The New York Times". The New York Times.
  22. Shariff, Azim; Rahwan, Iyad; Bonnefon, Jean-François (2016-11-03). "Whose Life Should Your Car Save? - The New York Times". The New York Times.
  23. "TedxCambridge: The social dilemma of driverless cars".
  24. "Save the driver or save the crowd? Scientists wonder how driverless cars will 'choose' - The Washington Post".
  25. "Driverless Cars Pose Difficult Ethical Question - Time.com".
  26. "Driverless car safety revolution could be scuppered by moral dilemma - The Independent". 2016-06-23.
  27. "Moral Machine".
  28. "Ethical dilemma on four wheels: How to decide when your self-driving car should kill you - LA Times".
  29. "For driverless cars, a moral dilemma: Who lives or dies? - Associated Press".
  30. "Ethical dilemma on four wheels: How to decide when your self-driving car should kill you".
  31. Awad, Edmond; Dsouza, Sohan; Kim, Richard; Schulz, Jonathan; Henrich, Joseph; Shariff, Azim; Bonnefon, Jean-François; Rahwan, Iyad (24 October 2018). "The Moral Machine experiment". Nature. 563 (7729): 59–64. Bibcode:2018Natur.563...59A. doi:10.1038/s41586-018-0637-6. hdl:10871/39187. PMID 30356211.
  32. Crandall, Jacob W.; Oudah, Mayada; Tennom; Ishowo-Oloko, Fatimah; Abdallah, Sherief; Bonnefon, Jean-François; Cebrian, Manuel; Shariff, Azim; Goodrich, Michael A. (2018-01-16). "Cooperating with machines". Nature Communications. 9 (1): 233. arXiv:1703.06207. Bibcode:2018NatCo...9..233C. doi:10.1038/s41467-017-02597-8. ISSN 2041-1723. PMC 5770455. PMID 29339817.
  33. Crandall, Jacob W; Oudah, Mayada; Tennom; Ishowo-Oloko, Fatimah; Abdallah, Sherief; Bonnefon, Jean-François; Cebrian, Manuel; Shariff, Azim; Goodrich, Michael A; Rahwan, Iyad (2017). "Cooperating with Machines". Nature Communications. 9 (233): 233. arXiv:1703.06207. Bibcode:2018NatCo...9..233C. doi:10.1038/s41467-017-02597-8. PMC 5770455. PMID 29339817.
  34. "AI Can Beat Us at Poker—Now Let's See If It Can Work with Us - MIT Technology Review".
  35. Widmaier, Sarah; Dumont, Jean-Christophe (2011). "OECD Social, Employment and Migration Working Papers". Social Employment and Migration Working Papers. OECD Social, Employment and Migration Working Papers. doi:10.1787/1815199x. ISSN 1815-199X.
  36. Frey, Carl Benedikt; Osborne, Michael A. (January 2017). "The future of employment: How susceptible are jobs to computerisation?". Technological Forecasting and Social Change. 114: 254–280. CiteSeerX 10.1.1.395.416. doi:10.1016/j.techfore.2016.08.019. ISSN 0040-1625.
  37. Frank, Morgan R.; Sun, Lijun; Cebrian, Manuel; Youn, Hyejin; Rahwan, Iyad (2018-02-01). "Small cities face greater impact from automation". Journal of the Royal Society Interface. 15 (139): 20170946. doi:10.1098/rsif.2017.0946. ISSN 1742-5689. PMC 5832739. PMID 29436514.
  38. "Crowdsourcing in Manhunts Can Work - Scientific American".
  39. "Nowhere to hide: The next manhunt will be crowdsourced - New Scientist".
  40. "Six degrees of mobilisation". The Economist. September 2012.
  41. "THe Nightmare Machine".
  42. "Researchers Build 'Nightmare Machine' : The Two-Way : NPR".
  43. "Clinton, Trump, the White House too, terrifyingly transformed by MIT's 'Nightmare Machine' - The Washington Post".
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