Can You Teach Creative Thinking with GenAI? with Leonard Boussioux | #13

What if the real skill of working with AI isn't knowing what it can do—but knowing when you need to lead? In this episode of What If?, Leslie Grandy sits down with Leonard Boussioux, assistant professor at the University of Washington's Foster School of Business and adjunct assistant professor at the UW Allen School of Computer Science and Engineering, to explore how humans can collaborate with AI to solve complex problems, build new ideas, and expand creative capacity. Leo's work sits at the intersection of operations, machine learning, artificial intelligence, and creative problem solving. His research investigates how humans and AI can work together more effectively—and why simply adding AI to the process doesn't automatically produce better or more original outcomes.  Together, Leslie and Leo explore: Why AI can make people more creative—but may also reduce diversity of ideas if everyone gets the same "excellent" suggestions The difference between human-in-the-loop and AI-in-the-loop thinking Why there is no single formula for when humans should lead and when AI should take more of the exploratory role How students can build confidence, agency, and creative capacity by using AI to bring their own ideas to life Why "vibe coding" is more than a technical skill—it's a way to learn orchestration, judgment, and problem framing How AI-native students may enter the workforce with skills and expectations that leaders are not yet prepared to recognize Why organizations need AI champions, safe access to the best tools, and cultures that encourage knowledge sharing How education must evolve to teach not just AI literacy, but ethics, lifelong learning, metacognition, and leadership Leo also shares how he designs his classroom as a kind of adventure—one where students don't just learn tools, but discover what they are capable of building. By asking students to create real products from their own ideas, he helps them move from anxiety about AI to a sense of creative agency. But the conversation also surfaces a critical warning: AI often recombines what it already knows. It may give you good ideas, but it may give everyone else the same good ideas, too. That means the human role is not disappearing. It is becoming more important. Because the future of human-AI collaboration won't be defined by who can generate the most ideas. It will be defined by who can push beyond the obvious, recognize what matters, and steer the system toward something more original, useful, and human. Reflection question: When you work with AI, are you letting it lead you toward the probable—or are you pushing it toward what only you can imagine?