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Professional

Track: Emerging Analytics

Data is Dirty: What AI Algorithms Actually Do and Why We Need Explainable Artificial Intelligence

Wednesday, April 14, 10-10:40am EDT

Modern black-box artificial intelligence algorithms are computationally powerful yet fallible in unpredictable ways. We argue that Explainable Artificial Intelligence (XAI) frameworksare required to not only understand ‘why’ AIs make their decisions, but to also integrate with human operators so these explanations provide the right quantity and quality of information to each operator. In essence, we need to account the expertise and goals of the user in order for these algorithms gain widespread adoptance in mission-critical environments. In this talk, we will present a survey of introspection techniques as well as a set of requirements for robust XAI systems. We describe a use-case for cognitive models to act as a bridge between humans and AIs that meet most of these requirements.

Robert Thomson image

Robert Thomson

Robert Thomson

Associate Professor in Engineering Psychology at the United States Military Academy

Dr. Robert Thomson is an Associate Professor in Engineering Psychology at the United States Military Academy and the Cyber and Cognitive Sciences Fellow at the Army Cyber Institute. Dr. Thomson has 10 years of post-graduate experience and over 40 invited and refereed academic publications in the domains of computational modeling, intelligence analysis, cybersecurity, and artificial intelligence.