About the Event
The field of artificial intelligence is enjoying renewed public attention today, based on its pervasive influence on a wide range of technologies, and promise for transformative effects in the near-term future. Coincident with the economic impact of AI in this century has been an increasing embrace of economic reasoning in the design and analysis of AI systems. Developments in algorithmic game theory and mechanism design are shaping how autonomous software agents interact in the networked economies, just as such agents are proliferating in key sectors like Internet advertising and financial trading. Large-scale computing infrastructure enabling much of this activity can also be harnessed in service of reasoning in a principled way about the resulting complex strategic environments.
With thousands of trials and verdicts occurring daily in courtrooms around the world, the chance of using deceptive statements and testimonies as evidence is growing. In this talk, I will address the identification of deception in real-life trial data. I will present a novel dataset consisting of videos collected from public court trials, and describe a multimodal deception detection system that relies on verbal and non-verbal clues to discriminate between truthful and deceptive statements provided by defendants and witnesses. The system achieves a classification accuracy in the range of 60-75%, which exceeds by a large margin the non-expert human performance on this task. This is joint work with Veronica Perez-Rosas, Mohamed Abouelenien, and Mihai Burzo.
Michael P. Wellman is Professor of Computer Science & Engineering at the University of Michigan. He received a PhD from the Massachusetts Institute of Technology in 1988 for his work in qualitative probabilistic reasoning and decision-theoretic planning. From 1988 to 1992, Wellman conducted research in these areas at the USAF’s Wright Laboratory. For the past 20+ years, his research has focused on computational market mechanisms and game-theoretic reasoning methods, with applications in electronic commerce, finance, and cyber-security. As Chief Market Technologist for TradingDynamics, Inc., he designed configurable auction technology for dynamic business-to-business commerce. Wellman previously served as Chair of the ACM Special Interest Group on Electronic Commerce (SIGecom), and as Executive Editor of the Journal of Artificial Intelligence Research. He is a Fellow of the Association for the Advancement of Artificial Intelligence and the Association for Computing Machinery.
Rada Mihalcea is a Professor in the Computer Science and Engineering department at the University of Michigan. Her research interests are in computational linguistics, with a focus on lexical semantics, graph-based algorithms for natural language processing, and multilingual natural language processing. She serves or has served on the editorial boards of the Journals of Computational Linguistics, Language Resources and Evaluations, Natural Language Engineering, Research in Language in Computation, IEEE Transactions on Affective Computing, and Transactions of the Association for Computational Linguistics. She was a program co-chair for the Conference of the Association for Computational Linguistics (2011) and the Conference on Empirical Methods in Natural Language Processing (2009), and a general chair for the Conference of the North American Chapter of the Association for Computational Linguistics (2015). She is the recipient of a National Science Foundation CAREER award (2008) and a Presidential Early Career Award for Scientists and Engineers (2009). In 2013, she was made an honorary citizen of her hometown of Cluj-Napoca, Romania.