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Pat Pataranutaporn, Ph.D. is a technologist and a researcher at the Massachusetts Institute of Technology (MIT) where he explores Human-AI interaction, Cyborg Psychology, synthetic virtual humans, and synthetic biology. Specifically, he focuses on the intersections between biological and digital systems. He finished his Ph.D. from the Fluid Interfaces research group at the MIT Media Lab and was a KBTG Fellow, working in collaboration with teams at NASA, NTT DATA, IBM, KBTG, UCSB, Stanford, and Harvard on advancing the future of human-computer interaction. Pat has also held a position as a researcher at the NASA SETI Frontier Development Lab.
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More about Pat Pataranutaporn's topics
Pat will present two distinct sessions during the Winter School: Session C1 and C2.
Session C1 - Cyborg Psychology: Designing Human-AI Systems that Support Human Flourishing
As Artificial Intelligence (AI) becomes increasingly integrated into our daily lives, understanding the psychological implications of human-AI interaction is crucial for developing systems that truly support human capabilities. This talk introduces "Cyborg Psychology," an interdisciplinary, human-centered approach to understanding how AI systems influence human psychological processes. Cyborg Psychology emphasizes applying insights to design and develop AI systems that support human flourishing through the cultivation of Wisdom, Wonder, and Wellbeing. For example, the "Wearable Reasoner" seeks to enhance human rationality, "Personalized Virtual Characters" aims to support learning motivation, and "Future You" is designed to encourage long-term oriented thinking and behavior. The ultimate goal is to empower the development of AI systems that foster human flourishing by nurturing intellectual growth, cultivating motivation, stimulating critical thinking, and preserving individual autonomy in decision-making
Session C2 - Research Methodologies for Investigating Human Cognitive Vulnerabilities in Cyborg Psychology
This presentation examines methodological approaches for studying cognitive vulnerabilities that emerge in human-AI interactions. Through an interdisciplinary lens combining human-computer interaction and behavioral sciences, we analyze how AI systems can inadvertently influence human psychological processes, particularly in areas of critical thinking, memory, and belief formation. Our research framework identifies key vulnerabilities in human cognition when interfacing with AI, including over-reliance, confirmation bias amplification, and reduced cognitive awareness. We present empirical approaches for investigating these phenomena and discuss implications for protective design measures in AI systems.
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