Toward Machines with Emotional Intelligence
Speaker: Rosalind W. Picard , MIT Media Lab
Date: April 16 2004
Time: 1:30PM to 2:30PM
Location: Stata Center, building 32, Gates tower, 5th floor
Contact: David Huynh, email@example.com
Relevant URL: http://www.media.mit.edu/~picard
Please note that the talk has been moved to the 5th floor lounge, Gates tower, Stata Center.
Over 70 studies on human-machine interaction in the last decade have pointed to an intriguing phenomenon: People tend to interact with machines in a way that is similar to how they interact with each other, even when the machine is not a robot, agent, or other kind of obviously social actor. This finding holds even when the users are intelligent computer science students who know that machines don't have feelings and don't care how you interact with them. Given that human-human interaction is a frequent guide to human-computer interaction, it thus becomes interesting to ask if there are principled sets of skills that are particularly important for human-human interaction, which machines do not yet have. The skills of "emotional intelligence" have been argued to be among the most important for people, even more important than mathematical and verbal intelligences. Emotional intelligence includes the ability to recognize emotion -- to see if you're irritated or annoyed someone, pleased or displeased them, bored or interested them. It includes the ability to know when to show emotion (or not), and how you should respond to another's emotions, as well as many other skills. Fifty years of artificial intelligence has essentially missed emotional intelligence.
In this talk, I'll describe how we're giving computers some of these new skills, specifically the ability to recognize and respond appropriately to human emotion. I'll show examples of systems that try to assess interest, frustration, stress, and a range of other states that occur when interacting with computers. These systems involve new kinds of sensing for desktop, wearable, and other environmental interfaces, as well as the development of new pattern recognition and machine learning algorithms for making inferences about the multimodal data.
Current applications include human learning, usability feedback, health behavior change, and human-robot interaction.
Rosalind W. Picard earned a Bachelors in Electrical Engineering with highest honors from the Georgia Institute of Technology in 1984, and was named a National Science Foundation Graduate Fellow. She worked as a Member of the Technical Staff at AT&T Bell Laboratories from 1984-1987, where she contributed to the design of the DSP16 and developed new adaptive image compression algorithms and hardware. Picard earned the Masters and Doctorate, both in Electrical Engineering and Computer Science, from MIT in 1986 and 1991, espectively. In 1991 she joined the MIT Media Laboratory as an Assistant Professor, in 1992 was appointed to the NEC Development Chair in Computers and Communications, in 1995 was promoted to Associate Professor. and in 1998 was awarded tenure. The author of over 100 peer-reviewed articles in pattern recognition, image processing and computer vision, human and machine learning, and human-computer interaction, Picard is known internationally for research developing early content-based video and image retrieval systems and for pioneering research in affective computing. She is co-recipient with Tom Minka of a "best paper" prize (1998) for their work on interactive machine learning with multiple models and with Kort and Reilly (2001) for their theory on modeling affect in human learning. She has served as Associate Editor of IEEE Trans. on Pattern Analysis and Machine Intelligence, and is currently serving on the editorial board of User Modeling as well as on the Advisory Board of NSF's CISE Division. Her award-winning book, Affective Computing, constructs a framework for giving machines skills of emotional intelligence.
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