Social and Emotional Intelligence in AI and Agents
- Mary Czerwinski; Justine Cassell; Jonathan Gratch; Daniel McDuff; Louis-Philippe Morency | Microsoft; Carnegie Mellon University; University of Southern California; Microsoft; Carnegie Mellon University
Social signals and emotions are fundamental to human interactions and influence memory, decision-making and wellbeing. As AI systems, in particular, intelligent agents, become more advanced, there is increasing interest in applications that can fulfil tasks goals, social goals and respond to emotional states. Research has shown that cognitive agents with these capabilities can increase empathy, rapport and trust with their users, amongst other things. However, designing such agents is extremely complex, as most human knowledge of emotion is implicit/tacit and defined by unwritten rules. Furthermore, these rules are culturally dependent and not universal. This session will focus on research into intelligent cognitive agents. It will cover the measurement and understanding of verbal and non-verbal cues, the computational modeling of emotion and the design of sentient virtual agents.
-
-
Evelyne Viegas
Technical Advisor - Research Explorations
-
-
Series: AIFactory – France research lecture library
-
Keynote: Model-Based Machine Learning
- Christopher Bishop
-
AI and Security
- Taesoo Kim; Dawn Song; Michael Walker
-
Transforming Machine Learning and Optimization Through Quantum Computing
- Krysta Svore; Helmut Katzgraber; Matthias Troyer; Nathan Wiebe
-
AI for Earth
- Tanya Berger-Wolf; Carla Gomes; Milind Tambe
-
Social and Emotional Intelligence in AI and Agents
- Mary Czerwinski; Justine Cassell; Jonathan Gratch; Daniel McDuff; Louis-Philippe Morency
-
Microsoft Cognitive Toolkit (CNTK) for Deep Learning
- Sayan Pathak; Cha Zhang; Yanmin Qian; Chris Basoglu
-
Machine Learning from Verbal Instruction
- Tom M. Mitchell
-
Combining Algorithms and Humans for Large-Scale Data Integration
- Vasileios Verroios
-
-
Learning Language through Interaction
- Hal Daume III