Dr. Joanna J. Bryson

Joanna J. Bryson, Ph.D. is Reader, Department of Computer Science, University of Bath, England. She is an Associate Editor for Adaptive Behavior and on the Editorial Boards of the International Journal of Synthetic Emotions (IJSE) and the Journal of Mind Theory.
 
Joanna’s principle scientific passion is understanding human behavior, human culture, and natural intelligence more broadly. Her main methodology for doing this is designing intelligent systems to model and test scientific theories. By building theories into cognitive systems — working AI models — we can learn more about a theory’s implications than by unassisted human reasoning. Once we understand a theory’s implications and predictions, we can compare these to data we collect from the system we are trying to explain.
 
In her opinion the unintentional and non-linguistic aspects of human intelligence are not taken sufficiently into account when we think about human behavior. The more we understand both the universals and the variation we see in natural intelligence, the more we will understand the “hardware” human behavior and human culture run on.
 
Designing AI models of natural intelligence requires AI as well as  good scientific method for utilizing it. Joanna’s research includes a great deal of work on systems AI. She applies this work into a variety of domains besides science, including cognitive robotics, computer game characters, and intelligent environments / “smart homes”.  Since 1998 she has been publishing and maintaining a web page on the ethical role of AI in Society.
 
Her papers include Crude, Cheesy, Second-Rate Consciousness, Structuring Intelligence: The Role of Hierarchy, Modularity and Learning in Generating Intelligent Behavior, Cultural Ratcheting Results Primarily from Semantic Compression, Why Robot Nannies Probably Won’t Do Much Psychological Damage, Robots Should Be Slaves, Simplifying the Design of Human-Like Behaviour: Emotions as Durative Dynamic State for Action Selection, Building Persons is a Choice, Age-Related Inhibition and Learning Effects: Evidence from Transitive Performance, and Representations Underlying Social Learning and Cultural Evolution.
 
Joanna earned her B.A. in Behavioral Science at the University of Chicago in 1986, her M.Sc. in Artificial Intelligence at the University of Edinburgh in 1992 with the dissertation The Subsumption Strategy Development of a Music Modelling System, her M.Phil. in Psychology at the University of Edinburgh in 2000 with the dissertation The Study of Sequential and Hierarchical Organization of Behavior via Artificial Mechanisms of Action Selection, and her Ph.D. in Computer Science at MIT in 2001 with the dissertation Intelligence by Design: Principles of Modularity and Coordination for Engineering Complex Adaptive Agents.