Mohamed Abouelenien is an Assistant Professor in the Department of Computer and Information Science at the University of Michigan-Dearborn. He was a Postdoctoral Research Fellow in Electrical Engineering and Computer Science Department at the University of Michigan, Ann Arbor from 2014-2017. In 2013, he received his Ph.D. in Computer Science and Engineering from the University of North Texas. His areas of interest broadly cover data science topics, including applied machine learning, computer vision, and natural language processing. He has worked on a number of projects in these areas, including affective computing, deception detection, ensemble learning, video and image processing, face and action recognition, and others. His recent research involves data analytics projects as well as modeling of human behavior for different applications. Abouelenien has published extensively in international journals and conferences in IEEE, ACM, Springer, and SPIE. He also served as the chair for the ACM Workshop on Multimodal Deception Detection, a reviewer for IEEE Transactions and Elsevier journals, and a program committee member for multiple international conferences.
“Fake news” has become the central inflammatory charge in media discourse in the United States since the 2016 presidential contest. Deployed not only to damn particular stories but to delegitimize the traditional press as a whole, “fake news” presents profound—and likely increasing—challenges for both the public and private spheres today. Recognizing that no single—or simple—tactic is sufficient to address the harms of “fake news,” in this talk I will discuss a three-pronged approach—focusing on platform self-regulation, audience information literacy approaches responsive to the lessons of cognitive science, and—perhaps counterintuitively—empowerment of the press itself through expanded legal protections for newsgathering and publication. Tools to empower the professional press can help forge alliances between the conservative and liberal wings of the traditional media, thereby isolating and minimizing the impact of newly-rising alt-right media entrants. If given expanded protections, the professional press can transform the modern context of “fake news” into an opportunity to shine as watchdog and, hopefully, thereby rebuild public trust.
Rada Mihalcea is a Professor in the Computer Science and Engineering department at the University of Michigan, where she directs the Artificial Intelligence lab. 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.