Michael Hogan Ph.D.: Researcher Bridging AI, Cognition, and Human Teamwork

Michael Hogan, Ph.D., is a researcher and lecturer at the National University of Ireland, Galway, whose work straddles systems science, cognitive neuroscience, and emerging questions around artificial intelligence integration in human teams.

Hogan's research spans multiple domains. His early work examined behavioral and electrophysiological aspects of executive control, learning, and memory. He has published on physical activity's relationship to aging cognition, emotional processing in younger and older adults, and cardiovascular reactivity. More recently, his research has shifted toward applied questions: how AI systems perform in high-stakes environments, how humans trust (and sometimes over-trust) AI teammates, and what design choices shape whether students think critically with AI tools or merely defer to them.

Recent publications suggest Hogan is particularly focused on the adoption barriers and behavioral dynamics that emerge when humans and AI systems work together. One line of inquiry examines human-AI teams in emergency scenarios. Another investigates classroom dynamics—specifically, how the same AI tool produces different cognitive outcomes depending on task structure. A third explores how employees respond when AI systems outvote them in group decision-making.

Hogan is also the author of The Culture of Our Thinking in Relation to Spirituality, reflecting a broader interest in how cognition, contemplative practice, and critical thinking intersect.

His contributor profile on Psychology Today highlights posts on topics including perspective-taking and dialogue-based AI, trust failures in medical AI systems, the role of situational awareness in AI autonomy, and what productivity gains from AI-human collaboration actually reveal about teamwork effectiveness. These contributions suggest Hogan approaches AI adoption with skepticism toward hype—asking not whether AI can perform a task, but whether its integration serves human cognition and organizational outcomes.

For researchers, educators, and organizations evaluating AI implementation, Hogan's work offers a counterpoint to vendor claims: evidence-based examination of how humans actually behave with AI systems, and what that behavior reveals about trust, task design, and learning.