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RESEARCH

Goal

The AI behind Virtual Humans Exhibit aims to communicate to the public about the capabilities and impact of artificial intelligence (AI) through AI technologies used in Virtual Humans. AI has and will continue to profoundly impact society in the US and around the globe. It is important to prepare the nation’s youth and the future workforce with fundamental knowledge of AI. Informal settings, such as museums, offer great opportunities in helping youth and the general public learn about AI. Virtual Humans provide an ideal vehicle to illustrate many fields of AI, as AI is arguably the science of building intelligence that thinks and acts like humans. The exhibit supports collaborative learning experiences for visitor dyads (e.g. parent/child, siblings; peers) to explore what AI is, what AI is capable of, and what impact it will have on their lives. Overall, the project addresses the urgent need of helping the nation’s youth learn the fundamentals of AI. 

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The project investigates three research questions: (1) How can a museum exhibit be designed to engage visitor dyads (e.g., parent and child) in collaborative learning about AI? (2) How can complex AI concepts underlying the Virtual Human be communicated in a way that is understandable by the general public? And (3) How does the Virtual Human exhibit increase knowledge and reduce misconceptions about AI? The project leverages existing conversational Virtual Human technology developed through decades of collaborative research in AI, including machine vision, natural language processing, automated reasoning, character animation, and machine learning. The exhibit is designed following evidence-based research in Computer Supported Collaborative Learning. The project produces an interactive exhibit with a Virtual Human installed at the Lawrence Hall of Science and aimed to be distributed to additional museums, communities, and other informal learning settings.

Publications

Greenwald, E., Cavero, D., Grindstaff, K., Krakowski, A., Hurt, T., & Wang, N. (2024, In press) Building Blocks ForUnderstanding Artificial Intelligence: Designing Interactive Ai Learning Experiences For Young Children And Their FamiliesIn A Museum Setting. In Proceedings of EDULEARN24.

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Cavero, D., Greenwald, E., Grindstaff, K., Krakowski, A., Hurt, T., & Wang, N. (2024) How does AI “think?”: A Strategy to Help Youth Unpack the “Intelligence” in Artificial Intelligence. To Appear in Science and Children.

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Greenwald, E., Krakowski, A., Hurt, T., Grindstaff, K., & Wang, N. (2024, June). It's like I'm the AI: Youth SensemakingAbout AI through Metacognitive Embodiment. In Proceedings of the 23rd Annual ACM Interaction Design and Children Conference (pp. 789-793)

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Greenwald, E., Krakowski, A., Hurt, T., & Wang, N. (2023). Detect-Interpret-Respond: A Framework to Ground theDesign of Student Inquiry into AI Systems. Proceedings of the AIED Workshop on K-12 AI Education in K-12.

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Wang, N., Hurt, T., Krakowski, A., Greenwald, E., Masur, O., Fu, B., & Merchant, C. (2023). Toward a Virtual Human Exhibit for Public AI Education, In Proceedings of the International Conference on Computers in Education.

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