Gary Klein, Ph.D Keynote Speaker
- Pioneered the Naturalistic Decision Making movement (1989)
- Developed the RPD, Data/Frame & Triple Path models
- Authored 6 books and 3 co-edited volumes; 150k+ copies sold
Gary Klein, Ph.D's Biography
Gary Klein, Ph.D., is a cognitive psychologist whose pioneering work has reshaped the understanding of decision-making in high-pressure environments. As a founder of the Naturalistic Decision Making movement in 1989, he introduced the Recognition-Primed Decision (RPD) model, which has been extensively tested and replicated across various domains. His contributions also include the Data/Frame model of sensemaking and the Triple Path model of insight, all grounded in advanced cognitive interviewing methods developed by his team.
Beyond theoretical models, Gary has created practical tools that have been widely adopted. The Pre-Mortem method aids organizations in identifying potential risks before they materialize, while the ShadowBox method enhances cognitive skills through scenario-based training. He also led the development of the Artificial Intelligence Quotient (AIQ) toolkit, aimed at improving the usability of AI and machine learning systems. His six authored books and three co-edited volumes have collectively sold over 150,000 copies, reflecting the broad impact of his work.
In his keynote presentations, Gary offers a compelling blend of research insights and practical applications, empowering audiences to navigate complexity, foster innovation, and make informed decisions under pressure. Drawing from decades of experience collaborating with organizations such as NASA, the U.S. Marine Corps, and Fortune 500 companies, he equips leaders and teams with strategies to thrive in dynamic environments.
Gary Klein, Ph.D's Speaking Topics
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How to gain more insights
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How to make decisions under time pressure and uncertainty
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Tools for harnessing the power of Artificial Intelligence systems
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The Pre-mortem method for risk assessment
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Cognitive coaching
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The Grey Tsunami — capturing the expertise of highly experienced knowledge workers before they retire
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