IYAD RAHWAN MIT Media Lab, 75 Amherst St., Cambridge MA 02139, USA, Irahwan[-At-]Mit.Edu This Version: April 8, 2017

Total Page:16

File Type:pdf, Size:1020Kb

IYAD RAHWAN MIT Media Lab, 75 Amherst St., Cambridge MA 02139, USA, Irahwan[-At-]Mit.Edu This Version: April 8, 2017 IYAD RAHWAN MIT Media Lab, 75 Amherst St., Cambridge MA 02139, USA, irahwan[-at-]mit.edu This version: April 8, 2017 AT A GLANCE Web Personal page: www.mit.edu/~irahwan Scholar profile: http://scholar.google.com/citations?user=yKCX2IUAAAAJ Personal Born: 1978, Citizenship: Australia, Syria Degree Ph.D. University of Melbourne, Australia, 2005 Position (Sept 2015 {) Associate Professor, The Media Lab, MIT, USA Impact h-index = 34, Citations = 4,020+ (Google Scholar) as of 3/2017 Selected J.-F. Bonnefon, A. Shariff, I. Rahwan (2016). The Social Dilemma of Autonomous Papers Vehicles. Science. 352(6293):1573-1576. I. Rahwan, et al (2014). Analytical reasoning task reveals limits of social learning in networks. J. Royal Society Interface. 11(93). A. Rutherford, M. Cebrian , S. Dsouza, E. Moro, A. Pentland, I. Rahwan (2013). Limits of Social Mobilization. PNAS, 110(16) pp 6281-6286 A. Mani, I. Rahwan, A. Pentland (2013). Inducing Peer Pressure to Promote Cooper- ation. Scientific Reports. 3(1735) I. Rahwan, et al (2013). Global Manhunt Pushes the Limits of Social Mobilization. IEEE Computer, 46(4) 68-75. G. Pickard, W. Pan, I. Rahwan, M. Cebrian, R. Crane, A. Madan, A. Pentland (2011). Time-Critical Social Mobilization. Science. 334(6055) 509-512. I. Rahwan, et al (2010). Behavioural Experiments for Assessing the Abstract Argu- mentation Semantics of Reinstatement. Cognitive Science. 34(8) 1483-1502 I. Rahwan et al (2007). Laying the Foundations for a World Wide Argument Web. Artificial Intelligence, 171(10-15) 897-921 Selected New York Times (2016) Should Your Driverless Car Hit a Pedestrian to Save Your Media Life? Wall Street Journal (2016) With Driverless Cars, a Safety Dilemma Arises Washington Post (2015) What if your self-driving car decides one death is better than two { and that one is you? MIT Technology Review (Best of 2015): Why Self-Driving Cars Must Be Pro- grammed to Kill Nature News/Scientific American (2013) Crowdsourcing in manhunts can work NBC News (2013) Facebook passes research test for quick responses, collaboration The Economist (2012) Six degrees of mobilization MSNBC (2011) How MIT team won balloon search-and-rescue challenge Iyad Rahwan Page 2 PRINCIPAL FIELDS OF INTEREST Computational Social Science; Social Networks; Data Science; Crowdsourcing; Cognitive Science; Behavioral Economics; Game Theory; Argumentation; Social Learning; Artificial Intelligence. EDUCATION University of Melbourne, Australia, PhD, Information Systems (Artificial Intelligence) 2005 Advisor: Prof. Liz Sonenberg Thesis title: Interest-based Negotiation in Multi-Agent Systems Swinburne University, Melbourne, Australia, Masters in Information Technology, 2000 UAE University, UAE, B.Sc. in Computer Science (honours), GPA 3.9/4, 1999 ACADEMIC POSITIONS Associate Professor of Media Arts & Science, The Media Lab 09/2015{ Massachusetts Institute of Technology, Cambridge MA, USA Other MIT appointments: { AT&T Career Development Professor 07/2015{06{2018 { Affiliate Faculty, Institute for Data, Systems & Society (IDSS) 07/2016{06/2018 Associate Professor, Computing & Information Science 1/2012{08/2015 Masdar Institute of Science & Technology, Abu Dhabi, UAE Assistant Professor, Computing & Information Science 2/2010{12/2011 Masdar Institute of Science & Technology, Abu Dhabi, UAE Honorary Fellow, School of Informatics, University of Edinburgh 02/2005{present Visiting Scholar, Media Lab (with Alex `Sandy' Pentland) 04/2010{10/2010 Massachusetts Institute of Technology (MIT), Cambridge MA 06/2011{08/2011 Research Affiliate, Technology & Development Program 10/2010{12/2011 Massachusetts Institute of Technology (MIT) Lecturer / Senior Lecturer, Informatics, British University in Dubai 11/2004{2/2010 HONORS & AWARDS Finalist, Telecom Italia Big Data Challenge, top 10 out of 652 teams 03/2014 Winner, \Tag Challenge", sponsored by US Department of State 04/2012 Best Technical Paper Award 9th International Conference on Electronic Commerce (ICEC), Minneapolis, MN 08/2007 European Master of Informatics Scholar, University of Edinburgh 08/2006{2008 European Commissions Erasmus Mundus Programme UAE Crown Prince Sheikh Khalifa Al-Nahyan academic excellence award 04/2000 SELECTED MEDIA COVERAGE Science Magazine. Computers learn to cooperate better than humans 2017 Washington Post. The big moral dilemma facing self-driving cars 2017 FiveThirtyEight. This Machine Was Built To Give You Nightmares 2016 Boston Globe. MIT's `Nightmare Machine' transforms photos into creepy images 2016 The Atlantic. The Nightmare Machine 2016 Financial Times. Driverless cars and MIT's test of the crowdsourcing morality 2016 New York Times. Should Your Driverless Car Hit a Pedestrian to Save Your Life? 2016 Wall Street Journal. With Driverless Cars, a Safety Dilemma Arises 2016 Iyad Rahwan Page 3 Time Magazine. New Study Reveals We're Utterly Conflicted About Driverless Cars 2016 The Guardian. Will your driverless car be willing to kill you to save the lives of others? 2016 Le Monde. Le dilemme macabre des voitures autonomes 2016 El Pais. >Comprar´ıasun coche que elegir´amatarte para salvar otras vidas? 2016 Der Spiegel. Was soll Ihr Auto jetzt tun? 2016 La Repubblica. Guida autonoma, chi vive e chi muore? Il dilemma del MIT diventa un quiz 2016 Washington Post. What if your self-driving car decides one death is better than two - and that one is you? 2015 BBC World Service. Should self-drive cars kill their passengers to save pedestrians? 2015 MIT Tech. Review. Best of 2015: Why Self-Driving Cars Must Be Programmed to Kill 2015 Daily Mail. Is Twitter making you stupid? 2014 Nature News/Scientific American. Crowdsourcing in manhunts can work 2013 New Scientist. Nowhere to hide: The next manhunt will be crowdsourced 2013 ABC. Social media has limited mobilisation power 2013 NBC News. Facebook passes research test for quick responses, collaboration 2013 MIT Tech. Review. `12 Hours of separation' connect individuals on social networks 2013 The Economist. Six degrees of mobilization 2012 Popular Science. How to track down international jewel thieves via Facebook 2012 MSNBC. How MIT team won balloon search-and-rescue challenge 2011 Popular Mechanics. What DARPA's scavenger hunt taught us about mobilizing people fast 2011 PUBLICATIONS In Submission / Preprints 1. I. Rahwan. Society-in-the-loop: Programming the algorithmic social contract. 2. M. R. Frank, L. Sun, M. Cebrian, H. Youn, I. Rahwan. Small Cities Face Greater Impact from Automation. 3. J.-F. Bonnefon, A. Shariff, I. Rahwan. Psychological obstacles to the adoption of self-driving cars. 4. A. Alabdulkareem, M. R. Frank, L. Sun, B. AlShebli, C. Hidalgo, I. Rahwan. Skill Polarization and Economic Inequality. 5. E. Awad, M. Kleiman-Weiner, S. Dsouza, J.-F. Bonnefon, A. Shariff, J. B. Tenenbaum, I. Rahwan. Moral responsibility across levels of vehicle automation. 6. M. R. Frank, N. Obradovich, L. Sun, S. Dsouza, P.J. Chang, W. L. Woon, B. L. LeVeck, I. Rahwan. Cooperative reciprocity is widespread in international relations. 7. A. Rutherford, M. Cebrian, I. Rahwan., Y. Lupu, B. LeVeck, M. Garcia-Herranz. Inferring Mechanisms for Global Constitutional Progress. 8. J. W. Crandall, M. Oudah, F. Ishowo-Oloko, S. Abdallah, J.-F. Bonnefon, M. Cebrian, A. Shariff, M. A. Goodrich, I. Rahwan. Cooperating with Machines. arXiv:1703.06207 Editorials in Major Newspapers & Magazines 1. A. Shariff, I. Rahwan, J.-F. Bonnefon (2016). Whose Life Should Your Car Save?. New York Times (Gray Matter) 2. M. Cebrian, I. Rahwan, A. Pentland (2017). Beyond Viral: Generating Sustainable Value From Social Media. Sloan Management Review Iyad Rahwan Page 4 Journal Articles 1. E. Awad, J.-F. Bonnefon, M. Caminada, T. Malone, I. Rahwan (2017). Experimental As- sessment of Aggregation Principles in Argumentation-enabled Collective Intelligence. ACM Transactions on Internet Technology. (in press) 2. E. Awad, M. Caminada, G. Pigozzi, M. Podlaszewski, I. Rahwan. Pareto Optimality and Strategy Proofness in Group Argument Evaluation. Journal of Logic and Computation. (in press) 3. E. Awad, R. Booth, F. Tohm´e,I. Rahwan (2017). Judgment Aggregation in Multi-Agent Argumentation. Journal of Logic and Compuation. 27(1): 227-259. 4. A. Hiassat, A. Diabat, I. Rahwan (2017). A genetic algorithm approach for location-inventory- routing problem with perishable products. Journal of Manufacturing Systems. 42:93{103. 5. I. Rahwan (2017). Towards Scalable Governance: Sensemaking and Cooperation in the Age of Social Media. Philosophy & Technology. (in press) 6. J.-F. Bonnefon, A. Shariff, I. Rahwan (2016). The Social Dilemma of Autonomous Vehicles. Science. 352(6293):1573-1576. { Press: New York Times, Wall Street Journal, Washington Post, CNN, Scientific Ameri- can, Time, The Guardian, Wired, LA Times, IEEE Spectrum, Forbes, New York Maga- zine, BBC Radio, The Independent, Popular Science, etc.. { Media impact (measured by Altmetrics as of Jan 2017): { In top-100 most discussed scientific articles in 2016 (ranked 33rd out of 2.7 million); { 10th most covered Science article to-date (out of 37,064); { 123rd most covered research output ever by the media to-date (out of 6.9 million). 7. H. Chen, I. Rahwan, M. Cebrian (2016). Bandit Strategies in Social Search: the case of the DARPA Red Balloon Challenge. EPJ Data Science. 5:20 8. M. Cebrian, I. Rahwan, A. Pentland (2016). Beyond Viral. Communications of the ACM. 59(4):36-39. 9. A. Alshamsi, F. Pianesi, B. Lepri, A. Pentland, I. Rahwan (2016). Network Diversity and Affect Dynamics: The Role of Personality Traits. PLOS ONE. 11(4): e0152358. 10. 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. 11. 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. 12. 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(13):1{27. 13. I. Rahwan, D. Krasnoshtan, A. Shariff, and J. F. Bonnefon (2014). Analytical reasoning task reveals limits of social learning in networks.
Recommended publications
  • Descriptive AI Ethics: Collecting and Understanding the Public Opinion
    Descriptive AI Ethics: Collecting and Understanding the Public Opinion GABRIEL LIMA, School of Computing, KAIST and Data Science Group, IBS, Republic of Korea MEEYOUNG CHA, Data Science Group, IBS and School of Computing, KAIST, Republic of Korea There is a growing need for data-driven research efforts on how the public perceives the ethical, moral, and legal issues of autonomous AI systems. The current debate on the responsibility gap posed by these systems is one such example. This work proposes a mixed AI ethics model that allows normative and descriptive research to complement each other, by aiding scholarly discussion with data gathered from the public. We discuss its implications on bridging the gap between optimistic and pessimistic views towards AI systems’ deployment. 1 INTRODUCTION In light of the significant changes artificial intelligence (AI) systems bring to society, many scholars discuss whether and how their influence can be positive and negative [21]. As we start to encounter AI systems in various morally and legally salient environments, some have begun to explore how the current responsibility ascription practices might be adapted to meet such new technologies [19, 33]. A critical viewpoint today is that autonomous and self-learning AI systems pose a so-called responsibility gap [27]. These systems’ autonomy challenges human control over them [13], while their adaptability leads to unpredictability. Hence, it might infeasible to trace back responsibility to a specific entity if these systems cause any harm. Considering responsibility practices as the adoption of certain attitudes towards an agent [40], scholarly work has also posed the question of whether AI systems are appropriate subjects of such practices [15, 29, 37] — e.g., they might “have a body to kick,” yet they “have no soul to damn” [4].
    [Show full text]
  • The Anti-Social System Properties: Bitcoin Network Data Analysis Israa Alqassem, Iyad Rahwan, and Davor Svetinovic , Senior Member, IEEE
    IEEE TRANSACTIONS ON SYSTEMS, MAN, AND CYBERNETICS: SYSTEMS, VOL. 50, NO. 1, JANUARY 2020 21 The Anti-Social System Properties: Bitcoin Network Data Analysis Israa Alqassem, Iyad Rahwan, and Davor Svetinovic , Senior Member, IEEE Abstract—Bitcoin is a cryptocurrency and a decentralized public and private keys [2]. The process of creating new coins semi-anonymous peer-to-peer payment system in which the trans- in the system is called mining. The mining process is computa- actions are verified by network nodes and recorded in a public tionally expensive. Any node connected to the Bitcoin network massively replicated ledger called the blockchain. Bitcoin is cur- rently considered as one of the most disruptive technologies. can participate in Bitcoin mining either as a part of a group Bitcoin represents a paradox of opposing forces. On one hand, it of miners (called mining pool) or individually. In pooled min- is fundamentally social, allowing people to transact in a peer-to- ing, the generated coins are shared based on each member’s peer manner to create and exchange value. On the other hand, contributed computational power. Bitcoin’s core design philosophy and user base contain strong Many commentators liken Bitcoin’s present state to the early anti-social elements and constraints, emphasizing anonymity, pri- vacy, and subversion of traditional centralized financial systems. days of the Internet, and suggest that its technology will tran- We believe that the success of Bitcoin, and the financial ecosystem scend financial transactions to encompass all kinds of new built around it, will likely rely on achieving an optimal balance social transactions.
    [Show full text]
  • 'Iran Regime Killed 106 to Quell Protest'
    TWITTER SPORTS @newsofbahrain OP-ED 8 America, China should listen to Henry Kissinger and manage their difficulties INSTAGRAM Shaikh Khalid hails /nobmedia 20 ‘successful’ 2019 BRAVE LINKEDIN WEDNESDAY newsofbahrain NOVEMBER 2019 International Combat Week 210 FILS WHATSAPP ISSUE NO. 8301 HH Shaikh Khalid yesterday 38444692 expressed his pride in the FACEBOOK resounding success enjoyed /nobmedia by the BRAVE International MAIL Combat Week in the Kingdom [email protected] thanking sponsors and heads WEBSITE of the organising committee for newsofbahrain.com their enormous support. P15 Gwyneth Paltrow, Kate Hudson, Zoe Saldana soak in Dubai spirit 14 CELEBS WORLD 5 Taliban frees US, Australian hostages A unique Children's Plan TALEEM PROFESSIONAL EDUCATION PLAN OF LIC INTERNATIONAL IN BAHRAIN FOR 30 YEARS APPLY. TERMS AND CONDITIONS Licensed as a conventional retail bank by the CBB Troops to Saudi Washington, DC S President Donald UTrump has informed Congress that the first group A glittering showcase of American troops have been sent to Saudi Arabia to deter Iran’s threat, with Jewellery Arabia 2019 Exhibition begins in great style the rest of the 3,000 soldiers to arrive within weeks. Mr Trump announced the troop The five-day movement in letters sent to • the House of Representatives exhibition, runs until and the Senate on Tuesday. Saturday and showcases The troops will stay there wide collections of for as long as they are able to luxurious jewellery and deter Iranian threats, he said. The news was in response high-end watches, in to pre-dawn attacks on two addition to precious major Saudi oil facilities on stones and gems, and September 14, which tempo- luxury accessories.
    [Show full text]
  • Iyad Rahwan Course Through Various Cultural and Institutional Innovations, Humans Became the Description Most Successful Cooperative Species on Earth
    Course Syllabus Program and Media Arts and Sciences Course Code MAS.S63 Course Title Cooperation Machines Credit Hours 12 Instructor Iyad Rahwan Course Through various cultural and institutional innovations, humans became the Description most successful cooperative species on earth. This course explores models and mechanisms of cooperation from a variety of disciplines: from behavioral economics and political science, to mathematical biology and artificial intelligence. Emphasis will be on: (1) the use of mathematical and computational techniques, from evolutionary game theory, to model cooperation mechanisms in nature and society; (2) the use of experiments and data analytics to understand cooperation phenomena using real behavioral data. We will then linK the phenomenon of cooperation to design features of social media and artificial intelligence systems. First, students obtain proficiency in the mathematical and computational modeling of cooperation and supporting mechanisms (around 25% of the course). Students will then read recent papers published in this area and present them in class, with topics rotating in each offering. Students will also be required to complete a major project, which involves substantial use of mathematical modeling combined with computational simulation or data analysis (e.g. from simulation or lab experiments), and writing up the results in a short article. Enrollment Enrollment in this course will be limited to 15 students, to facilitate seminar- style discussion of papers. Preference will be given to students with a strong technical bacKground. Pre-requisites Students are assumed to have a strong foundation in introductory statistics and probability, computer programming, and mathematical modeling. This will be required to read the papers at a sufficiently technical level.
    [Show full text]
  • Machine Behaviour ­Iyad Rahwan1,2,3,34*, Manuel Cebrian1,34, Nick Obradovich1,34, Josh Bongard4, Jean-François Bonnefon5, Cynthia Breazeal1, Jacob W
    REVIEW https://doi.org/10.1038/s41586-019-1138-y Machine behaviour Iyad Rahwan1,2,3,34*, Manuel Cebrian1,34, Nick Obradovich1,34, Josh Bongard4, Jean-François Bonnefon5, Cynthia Breazeal1, Jacob W. Crandall6, Nicholas A. Christakis7,8,9,10, Iain D. Couzin11,12,13, Matthew O. Jackson14,15,16, Nicholas R. Jennings17,18, Ece Kamar19, Isabel M. Kloumann20, Hugo Larochelle21, David Lazer22,23,24, Richard McElreath25,26, Alan Mislove27, David C. Parkes28,29, Alex ‘Sandy’ Pentland1, Margaret E. Roberts30, Azim Shariff31, Joshua B. Tenenbaum32 & Michael Wellman33 Machines powered by artificial intelligence increasingly mediate our social, cultural, economic and political interactions. Understanding the behaviour of artificial intelligence systems is essential to our ability to control their actions, reap their benefits and minimize their harms. Here we argue that this necessitates a broad scientific research agenda to study machine behaviour that incorporates and expands upon the discipline of computer science and includes insights from across the sciences. We first outline a set of questions that are fundamental to this emerging field and then explore the technical, legal and institutional constraints on the study of machine behaviour. n his landmark 1969 book Sciences of the Artificial1, which individuals to target in advertising campaigns Nobel Laureate Herbert Simon wrote: “Natural on social media. I science is knowledge about natural objects and These AI agents have the potential to augment phenomena. We ask whether there cannot also be human welfare and well-being in many ways. Indeed, ‘artificial’ science—knowledge about artificial objects that is typically the vision of their creators. But a and phenomena.” In line with Simon’s vision, we describe the emergence broader consideration of the behaviour of AI agents is now critical.
    [Show full text]
  • Ziv G. Epstein Cambridge, MA 02139
    [email protected] 75 Amherst St www.zive.info Ziv G. Epstein Cambridge, MA 02139 Code Statistical & Numerical Analysis Digital Media & Design Python Java React d3.js MATLAB R STATA LATEX Arduino Image Processing Illustrator Web EDUCATION Massachusetts Institute of Technology, Cambridge, MA September 2019 - Present PhD Candidate in Media Arts and Sciences at the MIT Media Lab's Human Dynamics group. Massachusetts Institute of Technology, Cambridge, MA Graduated May 2019 Masters in Media Arts and Sciences at the MIT Media Lab's Scalable Cooperation group. • Thesis: Untangling the Knotty Web of AI, advised by Iyad Rahwan Pomona College, Claremont, CA Graduated May 2017 Cum laude with Computer Science and Mathematics double major, Media Studies minor. GPA 3.88/4.00 • Thesis in Mathematics: Data Representation as Low Rank Matrix Factorization, advised by Blake Hunter • Thesis in Media Studies: The Mediasphere: Intermediation with Digital Planetaria, advised by Kim-Trang Tran Aquincum Institute of Technology, Budapest, Hungary Fall 2015 EXPERIENCE Facebook, Inc., New York, NY May 2019 - August 2019 Intern in Core Data Science on the Facebook and Society team • Conducted causal inference and trained machine learning models at Facebook scale as part of a independent research project to detect and understand the proliferation of misinformation. Massachusetts Institute of Technology, Cambridge, MA June 2015 - August 2016 Researcher and software developer for Laboratory for Social Machines at MIT Media Lab • Designed and implemented web scraper, back-end database and visualization interface as a functional component of LSM's JMAP/Electome project to navigate, quantify, aggregate and understand online journalism and in particular the 2016 Presidential Election.
    [Show full text]
  • Program Guide
    The First AAAI/ACM Conference on AI, Ethics, and Society February 1 – 3, 2018 Hilton New Orleans Riverside New Orleans, Louisiana, 70130 USA Program Guide Organized by AAAI, ACM, and ACM SIGAI Sponsored by Berkeley Existential Risk Initiative, DeepMind Ethics & Society, Future of Life Institute, IBM Research AI, Pricewaterhouse Coopers, Tulane University AIES 2018 Conference Overview Thursday, February Friday, Saturday, 1st February 2nd February 3rd Tulane University Hilton Riverside Hilton Riverside 8:30-9:00 Opening 9:00-10:00 Invited talk, AI: Invited talk, AI Iyad Rahwan and jobs: and Edmond Richard Awad, MIT Freeman, Harvard 10:00-10:15 Coffee Break Coffee Break 10:15-11:15 AI session 1 AI session 3 11:15-12:15 AI session 2 AI session 4 12:15-2:00 Lunch Break Lunch Break 2:00-3:00 AI and law AI and session 1 philosophy session 1 3:00-4:00 AI and law AI and session 2 philosophy session 2 4:00-4:30 Coffee break Coffee Break 4:30-5:30 Invited talk, AI Invited talk, AI and law: and philosophy: Carol Rose, Patrick Lin, ACLU Cal Poly 5:30-6:30 6:00 – Panel 2: Invited talk: Panel 1: Prioritizing The Venerable What will Artificial Ethical Tenzin Intelligence bring? Considerations Priyadarshi, in AI: Who MIT Sets the Standards? 7:00 Reception Conference Closing reception Acknowledgments AAAI and ACM acknowledges and thanks the following individuals for their generous contributions of time and energy in the successful creation and planning of AIES 2018: Program Chairs: AI and jobs: Jason Furman (Harvard University) AI and law: Gary Marchant
    [Show full text]
  • Law's Halo and the Moral Machine
    LAW’S HALO AND THE MORAL MACHINE Bert I. Huang * How will we assess the morality of decisions made by artificial intelligence—and will our judgments be swayed by what the law says? Focusing on a moral dilemma in which a driverless car chooses to sacrifice its passenger to save more people, this study offers evidence that our moral intuitions can be influenced by the presence of the law. INTRODUCTION As a tree suddenly collapses into the road just ahead of your driver- less car, your trusty artificial intelligence pilot Charlie swerves to avoid the danger. But now the car is heading straight toward two bicyclists on the side of the road, and there’s no way to stop completely before hitting them. The only other option is to swerve again, crashing the car hard into a deep ditch, risking terrible injury to the passenger—you. Maybe you think you’ve heard this one. But the question here isn’t what Charlie should do. Charlie already knows what it will do. Rather, the question for us humans is this: If Charlie chooses to sacrifice you, throw- ing your car into the ditch to save the bicyclists from harm, how will we judge that decision?1 Is it morally permissible, or even morally required, because it saves more people?2 Or is it morally prohibited, because Charlie’s job is to protect its own passengers?3 * Michael I. Sovern Professor of Law and Vice Dean for Intellectual Life, Columbia Law School. I wish to thank Benjamin Minhao Chen, Jeanne Fromer, Jeffrey Gordon, Scott Hemphill, Benjamin Liebman, Frank Pasquale, and the editors of this journal for their helpful comments on earlier drafts.
    [Show full text]
  • Faculty Club - December 4, 2020 12:00 - 1:30 Pm, Multimedia Presentation (45 Min) with Detailed Discussion
    Faculty Club - December 4, 2020 12:00 - 1:30 pm, Multimedia presentation (45 min) with detailed discussion Prof. Iyad Rahwan, Max Planck Institute for Human Development Experiments in Machine Behavior: Cooperating with and through machines Human cooperation is fundamental to the success of our species. But emerging machine intelligence poses new chal- lenges to human cooperation. This talk explores two interrelated problems: How can we humans cooperate through machines - that is, agree among ourselves on how machines should behave? And how can we cooperate with ma- chines - that is, convince self-interested machines to cooperate with us. The talk will then propose an interdisciplinary agenda for understanding and improving our human-machine ecology. Iyad Rahwan holds a PhD in Information Systems (Artificial Intelligence) from the Uni- versity of Melbourne, Australia and is a director of the Max Planck Institute for Human Development in Berlin, where he founded and directs the Center for Humans & Machi- nes. He is an honorary professor of Electrical Engineering and Computer Science at the Technical University of Berlin. From 2015 until 2020, he was an Associate Professor of Media Arts & Sciences at the Massachusetts Institute of Technology (MIT). Rahwan‘s work lies at the intersection of computer science and human behavior, with a focus on collective intelligence, large-scale cooperation, and the societal impact of Artificial Intelligence and social media. Through a series of projects, he also exposed tens of millions of people worldwide to new implications of AI, such as bias in machine learning, human-AI creativity and the ability of AI to induce fear and empathy in humans at scale.
    [Show full text]
  • Tuesday 10/29/19 the Moral Machine Experiment Iyad Rahwan's
    Tuesday 10/29/19 The Moral Machine Experiment Iyad Rahwan’s Ted Talk · Talk centered around technology and society, and self-driving cars - social aspects of technology · Moral decision making · Bentham line of thought: minimize death count · Dilemma: do you take action to minimize the death count? Or do not take action and let the situation play out · Social dilemma: if everyone thinks, “I won't follow the rules, but I hope everyone else will”, then no one will follow the rules o This is why collecting user data on ethical preferences is important ​ · Asimov’s laws of robotics o A robot may not injure a human being or allow a human being to come to harm. ​ o A robot must obey the orders given to it by human beings except if they were to ​ conflict with the first law. o A robot must protect its own existence - may not allow itself to come to harm ​ Moral Machine Experiment · Collected data based off culture clusters o Western, eastern, southern ​ o Eastern cares more about people following the law, less about sparing the young, ​ don’t follow Bentham model o Should be taken into account by regulators so the laws that are formed are ​ modeled based on the preferences of that country · Collected data from various regions and made charts to show probabilities of choosing one side over another in a situation where an ethical decision is made, in context of autonomous vehicle accidents Moral Machine Experiment (continued) · Study, gathered 40 million decisions in 10 different languages from many people spanning across 233 countries o Moral preferences among those who participated in the study: prioritize young lives, ​ valuing humans over animals o Spared most often were babies in strollers, pregnant women, and children ​ o Final results also showed ethics varying between different cultures ​ • Let the car take its course.
    [Show full text]
  • Edmond Awad MIT Media Lab [email protected] |
    Edmond Awad MIT Media Lab [email protected] | http://media.mit.edu/~awad Academic Positions Massachusetts Institute of Technology, Cambridge, MA, USA. (Jun, 2017 – present) Postdoctoral Associate Advisor: Iyad Rahwan Education Massachusetts Institute of Technology, Cambridge, MA, USA. (Sep, 2015 – May, 2017) MSc in Media Arts and Sciences. GPA: 4.9/5.0 Thesis Title: “Moral Machine: Perception of Moral Judgment Made by Machines” Committee: Iyad Rahwan (Advisor), Joshua Greene, and Joshua B. Tenenbaum. Masdar Institute (now Khalifa University), United Arab Emirates. (Sep, 2011 – Aug, 2015) PhD in Argumentation and Multi-Agent Systems. GPA: 3.8/4.0 Thesis Title: “Collective Judgement in Contested Domains: The Case of Conflicting Arguments” Committee: Iyad Rahwan (Advisor), Thomas W. Malone, Martin Caminada, and Khaled Elbassioni Masdar Institute (now Khalifa University), United Arab Emirates. (Sep, 2009 – Aug, 2011) MSc in Computing and Information Science. GPA: 4.0/4.0 Thesis Title: “Learning to Share: A Study of Multi-agent Learning in Transportation Systems” Committee: Jacob Crandall (Advisor), Iyad Rahwan, and Zeyar Aung. Tishreen University, Latakia, Syria (Sep, 2002 – Jun, 2007) BSc in Informatics Eng. (Major: Information Systems and Software Eng.). GPA: 75.78% Capstone Project: Simulation for Traffic Lights Publications & Working Papers E. Awad, S. Dsouza, R. Kim, J. Schulz, J. Henrich, A. Shariff, J.F. Bonnefon, I. Rahwan. The Moral Machine Experiment (2018). Nature. 562(7729) E. Awad*, S. Levine*, M. Kleiman-Weiner, S. Dsouza, J. B. Tenenbaum, A. Shariff, J.F. Bonnefon, I. Rahwan. Blaming humans in autonomous vehicle accidents: Shared responsibility across levels of automation (Revise & Resubmit at Nature Human Behaviour).
    [Show full text]
  • Mechanism Design for Time Critical and Cost Critical Task Execution Via Crowdsourcing
    Mechanism Design for Time Critical and Cost Critical Task Execution via Crowdsourcing Swaprava Nath1, Pankaj Dayama2, Dinesh Garg3, Y. Narahari1, and James Zou4 1 Department of Computer Science and Automation, Indian Institute of Science, Bangalore, India, {swaprava, hari}@csa.iisc.ernet.in 2 IBM India Research Lab, Bangalore, India, [email protected] 3 IBM India Research Lab, New Delhi, India, [email protected] 4 Harvard School of Engineering and Applied Sciences, Cambridge, MA, [email protected] Abstract. An exciting application of crowdsourcing is to use social net- works in complex task execution. In this paper, we address the problem of a planner who needs to incentivize agents within a network in order to seek their help in executing an atomic task as well as in recruiting other agents to execute the task. We study this mechanism design problem under two natural resource optimization settings: (1) cost critical tasks, where the planner’s goal is to minimize the total cost, and (2) time crit- ical tasks, where the goal is to minimize the total time elapsed before the task is executed. We identify a set of desirable properties that should ideally be satisfied by a crowdsourcing mechanism. In particular, sybil- proofness and collapse-proofness are two complementary properties in our desiderata. We prove that no mechanism can satisfy all the desirable properties simultaneously. This leads us naturally to explore approximate versions of the critical properties. We focus our attention on approximate sybil-proofness and our exploration leads to a parametrized family of pay- ment mechanisms which satisfy collapse-proofness.
    [Show full text]