Iyad Rahwan

TL;DR: Even though participants approve of autonomous vehicles that might sacrifice passengers to save others, respondents would prefer not to ride in such vehicles, and regulating for utilitarian algorithms may paradoxically increase casualties by postponing the adoption of a safer technology.

TL;DR: The Moral Machine, an online experimental platform designed to explore the moral dilemmas faced by autonomous vehicles, gathered 40 million decisions in ten languages from millions of people in 233 countries and territories to shed light on similarities and variations in ethical preferences among different populations.

TL;DR: This article provides a conceptual framework through which the core elements and features required by agents engaged in argumentation-based negotiation, as well as the environment that hosts these agents are outlined, and surveys and evaluates existing proposed techniques in the literature.

TL;DR: This paper shows that by extending the distant supervision to a more diverse set of noisy labels, the models can learn richer representations and obtain state-of-the-art performance on 8 benchmark datasets within emotion, sentiment and sarcasm detection using a single pretrained model.

TL;DR: This book presents an overview of key concepts in argumentation theory and of formal models of argumentation in AI, beginning with a review of the foundational issues in argueation and formal argument modeling, and moving to more specialized topics, such as algorithmic issues, argumentations in multi-agent systems, and strategic aspects of argumentations.