Edmond Awad is a Postdoctoral Associate at the Scalable Cooperation group, led by Iyad Rahwan at MIT Media Lab. Born and raised in Syria, Edmond received his bachelor degree (2007) from Tishreen University (Syria) in Informatics Engineering. In 2009, he moved to UAE where at Masdar Institute, he completed a master’s degree (2011) in Computing and Information Science with a research topic in Multi-agent Systems, before completing a PhD (2015) in Argumentation and Multi-agent systems. In 2015, Edmond joined the Scalable Cooperation group at MIT Media Lab. There, he co-developed Moral Machine, a website that gather human decisions on moral dilemmas faced by driverless cars. The website has been visited by over 3 million users, who contributed their judgements on 40 million dilemmas. Another website that Edmond co-created, called MyGoodness, collected judgements over 1 million charity dilemmas. Edmond’s work appeared in major academic journals, including Nature and ACM Transactions, and it has been covered in major media outlets including The Associated Press, the New York Times, Washington Post, LA Times, The Times, Der Spiegel, Le Monde and El Pais. Edmond’s research interests are in the areas of AI, Ethics, Computational Social Science and Multi-agent Systems.
Moral Machine is an online platform for gathering a human perspective on moral decisions made by autonomous vehicles (AVs). It presents users with moral dilemmas that are faced by AVs. The dilemmas are inspired by the Trolley Problem, a famous philosophical conundrum. Since its deployment in June 2016, the website has received high publicity and coverage. This has produced the largest dataset on ethics of machines ever collected: 40 million decisions in ten languages from millions of people in 233 countries and territories.
MyGoodness is an online platform created in collaboration with Peter Singer's foundation, The Life You Can Save. MyGoodness proposes dilemmas in a similar fashion to Moral Machine in the form of possible charities. The goal of MyGoodness is to quantify the effect of the different factors that may influence people to give ineffectively, and to raise awareness among the public about how people can be very ineffective when giving. Since its deployment in December 2017, MyGoodness has been visited by 80,000 users who have contributed over one million responses.
Blaming Humans and Machines
When a semi-autonomous car crashes and harms someone, how are blame and causal responsibility distributed across the human and the machine drivers? Our studies considered a variety of situations in which a car crashed causing the death of a pedestrian in an accident that could have been avoided.
Various mechanisms have been implemented to capture individuals' opinions online such as thumbs-up/down. However, in more contested domains (e.g., Wikipedia, and political discussion) these mechanisms are not sufficient since they only deal with each issue independently. In such cases, the use of arguments provides a better tool to represent the conflict on the Web. I investigated the theoretical limits of such a type of aggregation, and how to circumvent these limits.