Russell, Stuart (University of California, Berkeley) | Dietterich, Tom (Oregon State University) | Horvitz, Eric (Microsoft) | Selman, Bart (Cornell University) | Rossi, Francesca (University of Padova) | Hassabis, Demis (DeepMind) | Legg, Shane (DeepMind) | Suleyman, Mustafa (DeepMind) | George, Dileep (Vicarious) | Phoenix, Scott (Vicarious)
The adoption of probabilistic and decision-theoretic representations and statistical learning methods has led to a large degree of integration and cross-fertilization among AI, machine learning, statistics, control theory, neuroscience, and other fields. The progress in AI research makes it timely to focus research not only on making AI more capable, but also on maximizing the societal benefit of AI. We recommend expanded research aimed at ensuring that increasingly capable AI systems are robust and beneficial: our AI systems must do what we want them to do. In summary, we believe that research on how to make AI systems robust and beneficial is both important and timely, and that there are concrete research directions that can be pursued today.
Azevedo, Roger (McGill University) | Biswas, Gautam (Vanderbilt University) | Bohus, Dan (Microsoft Research) | Carmichael, Ted (University of North Carolina at Charlotte) | Finlayson, Mark (Massachusetts Institute of Technology) | Hadzikadic, Mirsad (University of North Carolina at Charlotte) | Havasi, Catherine (Massachusetts Institute of Technology) | Horvitz, Eric (Microsoft Research) | Kanda, Takayuki (ATR Intelligent Robotics and Communications Laboratories) | Koyejo, Oluwasanmi (University of Texas at Austin) | Lawless, William (Paine College) | Lenat, Doug (Cycorp) | Meneguzzi, Felipe (Carnegie Mellon University) | Mutlu, Bilge (University of Wisconsin, Madison) | Oh, Jean (Carnegie Mellon University) | Pirrone, Roberto (University of Palermo) | Raux, Antoine (Honda Research Institute USA) | Sofge, Donald (Naval Research Laboratory) | Sukthankar, Gita (University of Central Florida) | Durme, Benjamin Van (Johns Hopkins University)
The Association for the Advancement of Artificial Intelligence was pleased to present the 2010 Fall Symposium Series, held Thursday through Saturday, November 11-13, at the Westin Arlington Gateway in Arlington, Virginia. The titles of the eight symposia are as follows: (1) Cognitive and Metacognitive Educational Systems; (2) Commonsense Knowledge; (3) Complex Adaptive Systems: Resilience, Robustness, and Evolvability; (4) Computational Models of Narrative; (5) Dialog with Robots; (6) Manifold Learning and Its Applications; (7) Proactive Assistant Agents; and (8) Quantum Informatics for Cognitive, Social, and Semantic Processes. The highlights of each symposium are presented in this report.
The Association for the Advancement of Artificial Intelligence (AAAI) held its 1996 Fall Symposia Series on 9 to 11 November in Cambridge, Massachusetts. This article contains summaries of the seven symposia that were conducted: (1) Configuration; (2) Developing Assistive Technology for People with Disabilities; (3) Embodied Cognition and Action; (4) Flexible Computation: Results, Issues, and Opportunities; (5) Knowledge Representation Systems Based on Natural Language; (6) Learning Complex Behaviors in Adaptive Intelligent Systems; and (7) Plan Execution: Problems and Issues.