Guidance for generative AI in education and research
A human-centered foundation for privacy, inclusion, agency, and educational use. Read the sections on risks and policy considerations.
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Research & Assessment Librarian · Zahnow Library
Kyle Bylin is a Research and Assessment Librarian at Saginaw Valley State University's Zahnow Library and a creative technologist who uses AI to turn research into clear insights. He began his career as a technology journalist and analyst, serving as the editor at Hypebot and writing for Billboard and The Hollywood Reporter. He spent nearly a decade as a UX researcher at companies including Live Nation Labs, SoundHound, Bushel, and Ellucian. He holds an MS in Information from the University of Michigan and a BA in Music Business from Berklee College of Music.
Sit down with Kyle for a one-on-one conversation or a live demo. Bring a question, a class project, or just your curiosity — no experience needed.
Explore AI foundations, practical examples, and learning events.
AI FLUENCYDevelop AI fluency and a thoughtful approach to working with assistants.
PRACTICAL SKILLSExplore courses and resources for bringing AI into your work.
LEARNING PATHSBuild technical understanding with structured AI learning paths.
GO DEEPERFind deeper courses and certificates. Access and pricing vary.
PROMPTING FRAMEWORKRead Leo S. Lo’s original article on reflective, effective prompting.
Course availability, fees, and certificates are set by each provider. These links do not imply university endorsement.
Frameworks, official guidance, and research that ground the course activities. The imagination, taste, and agency perspective used throughout this guide remains a teaching lens, not a settled scientific claim.
A human-centered foundation for privacy, inclusion, agency, and educational use. Read the sections on risks and policy considerations.
The source of Concise, Logical, Explicit, Adaptive, and Reflective prompting. Full-text access may require the library.
Explore delegation, description, discernment, and diligence. This complements—not replaces—the imagination, taste, and agency lens used throughout this guide.
Use the discussions of confabulation, information integrity, privacy, and harmful bias to inspect a real output.
Explore empathize, define, ideate, prototype, and test. Use the resource collection to find design exercises and process guides.
Part 1 addresses digital replicas; Part 2 addresses copyrightability. Rights depend on human authorship and the details of the work, not simply the tool used.
Connect AI-assisted inquiry with authority, information creation, scholarship as conversation, and searching as strategic exploration.
Read the skills outlook. These are employer expectations and forecasts—not promises about your career or a prediction that every task will be automated.
Public YouTube selections used in the curriculum. These are complementary perspectives, not endorsements of every claim. Video metadata was checked through YouTube; captions, playback in all locations, and embedding permissions remain publisher-dependent.
Watch for delegation, description, discernment, and diligence. Compare this framework with imagination, taste, and agency.
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Optional technical deep dive. Focus on how training and generation help explain why plausible answers can be wrong.
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Identify each CLEAR habit. Apply the framework to your initial prompt and to what you change after seeing the result.
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Practice leaving the original page to investigate its source. Apply the same habit to links suggested by an AI assistant.
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Use the vocabulary of balance, emphasis, line, and composition to explain why one visual direction serves your audience better.
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Consider how context and interpretation shape judgment. Do not mistake a polished surface for meaningful creative work.
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A historical explainer, not a current capability benchmark. Watch for how synthetic likenesses challenge consent and trust.
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Apply online source-checking habits to the origin and context of media before sharing it.
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Look for how understanding people shapes framing, ideation, prototyping, and testing. Use the cycle on your own small project.
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Connect the five steps with the five-step building loop. Notice where user testing can change the problem itself.
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Optional extended educator discussion. Identify ways library-led inquiry keeps human reasoning and source verification visible.
Open on YouTubeLoading the player connects to YouTube. Playback and captions depend on the publisher; use the accompanying readings if unavailable.