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Webinar Resources: Learning to Imagine in the Age of AI
Webinar Description
AI is changing how people learn, create, and solve problems—not by narrowing human thinking, but by expanding what individuals can imagine and attempt. Through stories and practical examples, this exploration highlights how people across roles, organizations, and communities are using accessible, “my-sized” AI tools to rethink learning, approach complex challenges, and experiment with new ideas. By lowering barriers tied to expertise, scale, and resources, AI is enabling more inclusive creativity and problem-solving, helping individuals and teams envision possibilities that were previously out of reach.
Resource Sharing
Name of resource
Description
ASU Partnership with advanced AI platforms to foster innovation challenges amongst faculty, staff, students, and researchers.
Use of AI at ASU,
Principled Innovation at ASU,
Edge AI, and
CreateAI platform
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Questions from the audience
Question
Response
AI, Critical Thinking & Cognitive Development: Does reliance on AI risk weakening foundational cognitive skills such as deep focus, memory, synthesis, imagination, and critical thinking? Is there scientific evidence that AI-assisted writing or learning negatively affects critical thinking? How can educators balance AI enabling learning without replacing learning, especially when students are becoming highly dependent on AI?
Open
University-Wide Policy & Governance: Should universities develop institution-wide AI policies, and what should those policies include in order to balance innovation, academic integrity, responsible use, and risk management?
Open
Practical Use in Education (Course Design & Platforms): Is it appropriate to use AI to create instructional design and course content, and is AI-generated content acceptable in platforms such as Open edX?
Open
Equity, Bias & Educational Inequality: How can educators balance AI’s transformative potential for personalized learning with the risks of reinforcing bias, diminishing critical thinking, and increasing educational inequities?
Open
Reliability, Accuracy & Trust in AI: Given that AI systems are not error-free and sometimes provide incorrect answers, how can educators responsibly rely on AI in academic contexts?
Open
Responsible Use, Deepfakes & Distortion of Reality: How should generative AI be used responsibly given risks such as deepfakes, misinformation, distortion of reality, and harmful outputs (e.g., inappropriate image generation)? What accountability should AI developers have, and how should universities respond?
Open
Recommended Tools & Access (Free vs Paid): Which AI tools are recommended for educational purposes (course preparation, research, content creation), and are advanced AI versions accessible or affordable for educators in low-resource contexts?
Open
Infrastructure & Capacity in Developing Countries: Do developing countries (e.g., Ethiopia, Eritrea, Somalia) have sufficient infrastructure, resources, and datasets to create or meaningfully implement AI systems?
Open
Professional / Specialized Applications (Health Example): Can generative AI be responsibly used for specialized professional applications such as predicting drug adverse effects in clinical contexts, and what safeguards are necessary?
Open
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