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Human error analysis consists in trying to understand what
went wrong in the case of an incident. Such analysis is made even more
difficult when it comes to modern socio-technical systems, in which
human operators interact with complex systems. Accidents can occur even
with a fully operational system and rational operators. In such
situations, it can be very difficult to identify the cause of the error.
As an example, we all know how long the inqury after an airplane crash
can be. In this talk, we will show how AI and logic-based reasoning can
help inversigators in exploring the numerous scenarios that can explain
the accident. We show that human biases can be modeled and used to
filter the possible explanations. This work, at the junction between AI
and cognitive sciences, gives an example of AI use that does not try to
replace human beings, but rather serve as a tool for human enhancement.
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Nicolas Sabouret is full Professor at University Paris-Saclay, conducting his research at LISN, the interdisciplinar joint research institute for Digital Science between Université Paris-Saclay, CNRS, Inria and CentraleSupélec. He is also director of the Graduate School of Computer Science. Nicolas Sabouret is an expert in AI. His research focuses on human behaviour modeling and simulation, combining AI models with theories of human cognition and decision making from social science. His goal is to contribute to the construction of artificial agents that adopt human-like behaviours. His research is applied to various domains: multi-agent simulation of human activity to study and predict electrical consumption in households; development of conversational agents with social competencies for customer relationship, for social training or for health coaching; modeling and simulation of human factors in critical systems.