Title: How Stanford Teaches AI-Powered Creativity in Just 13 MinutesㅣJeremy Utley
Resource URL: https://www.youtube.com/watch?v=wv779vmyPVY
Publication Date: 2025-04-27
Format Type: Video
Reading Time: 13 minutes
Contributors: Jeremy Utley;
Source: EO (YouTube)
Keywords: [Generative AI Collaboration, AI-Assisted Creativity, Prompt Engineering, Human-Machine Teaming, Innovation Training]
Job Profiles: Chief Innovation Officer (CIO);Chief Digital Officer (CDO);Learning and Development Specialist;Innovation Manager;Business Consultant;
Synopsis: In this video, Stanford University's Jeremy Utley examines how non-technical professionals can collaborate with generative artificial intelligence to amplify creativity and productivity through practical methods and real-world case studies.
Takeaways: [Invite a language model to interview you by requesting it to ask successive questions until it can propose two obvious and two non-obvious AI applications for your workflows., Treat generative AI as a teammate: coach its output with feedback and mentorship instead of dismissing mediocre results as failures., Use AI to role-play and prepare for challenging conversations by having the model adopt a counterpart’s perspective and provide targeted feedback., Apply AI to tasks you dread: one park ranger turned a two-to-three-day paperwork process into a 45-minute tool that will collectively save 7,000 labor days across 430 parks., Cultivate diverse sources of inspiration—your unique experiences and inputs, combined with disciplined prompt variation, yield differential outputs from the same AI model.]
Summary: Jeremy Utley opens by recalling Winston Churchill’s bathtub-dictated speech to illustrate the timeless nature of creativity’s unguarded moments and observes that modern professionals can now command an AI assistant with equal intimacy. As an adjunct professor at Stanford University’s design school, he has shifted from authoring a leading text on idea generation to immersing himself in generative artificial intelligence, learning alongside students and corporate teams about how this technology can augment human invention. 

In his first chapter, Utley argues that users should ask an AI model to interrogate them first, requesting a sequence of questions that reveal workflows, objectives, and performance indicators. This “AI teaching itself” approach equips the system to offer two obvious and two non-obvious recommendations for integrating AI into daily responsibilities. He illustrates the point with a national park ranger who automated 2–3 days of paperwork into a 45-minute natural language tool, a solution that is projected to save 7,000 human labor days across 430 parks this year. 

Chapter two contrasts two orientations toward AI: tool versus teammate. While AI can improve speed by 25 percent, output volume by 12 percent, and quality by 40 percent, less than 10 percent of professionals realize meaningful gains because they treat the model as a passive instrument. Outperformers, by contrast, coach their AI collaborators—providing feedback on mediocre results and prompting them to ask clarifying questions. Utley demonstrates how role-playing difficult conversations with AI can refine one’s approach, building psychological profiles and rehearsing dialogue. 

In his final chapter, he revisits the definition of creativity as “doing more than the first thing you think of,” noting that generative AI makes it easier than ever to reach a “good-enough” answer. Yet achieving world-class innovation requires volume and variation in prompts, time to vet outputs, and the deliberate curation of inspirational inputs. According to Utley, creativity in the AI era demands disciplined exploration, leveraging personal experience and diverse influences to secure distinctive results. He concludes that rather than using AI, professionals must work with it as a collaborative partner to unlock unprecedented creative potential.
Content: ## Introduction

Creativity often emerges during everyday activities rather than at a desk. Winston Churchill famously dictated a speech from his bathtub, relying on an assistant to capture his words. Today, any individual with minimal resources can access a personalized AI assistant capable of understanding context, style, and intent, enabling them to dictate ideas from anywhere.

## AI’s Democratizing Potential

The proliferation of advanced language models means that even the most modest professional can engage an AI collaborator equivalent to Churchill’s private secretary. This capability allows users to focus on inspiration and ideation rather than transcription and formatting.

## Context and Expertise

The speaker is an adjunct professor of creativity and artificial intelligence at Stanford University’s design school, where he has taught executive programs for over fifteen years. Co-author of a seminal book on idea generation, he returned to the learner’s seat following the emergence of generative AI, conducting research and training teams to understand how these systems influence individual, team, and organizational problem-solving.

## Chapter 1: Let AI Ask You Questions

Instead of directing an AI with a static prompt, request the model to assume the role of an AI expert and to pose clarifying questions one at a time. By gathering detailed information about your workflows, key performance indicators, and objectives, the system can formulate two obvious and two non-obvious recommendations for integrating AI effectively into your responsibilities.

## Chapter 2: Treat AI as a Teammate

Research indicates that while AI can boost speed by 25 percent, output volume by 12 percent, and quality by 40 percent, fewer than 10 percent of professionals unlock these benefits. The difference lies in mindset: those who view AI as a tool often abandon it when results are mediocre, whereas those who regard it as a teammate provide feedback, mentorship, and even request that the AI ask them questions to refine outcomes.

A practical application involves training an AI to role-play a forthcoming difficult conversation. By prompting the model to gather intelligence on a colleague’s preferences and communication style, users can rehearse dialogue and receive feedback, thereby improving interpersonal outcomes.

## Chapter 3: Surpass “Good Enough”

A simple definition of creativity is “doing more than the first thing you think of,” which counters our natural tendency to adopt the first acceptable solution. Although generative AI readily delivers “good enough” responses, achieving world-class innovation requires volume, variation, and rigorous evaluation of model outputs. The inspiration a human brings—comprising personal experience, technique, and external influences—differentiates one user’s output from another’s.

## Conclusion

In the age of generative AI, the most effective approach is not to use AI as a mere instrument but to collaborate with it as one would with a skilled teammate. By adopting a questioning mindset, coaching the model, and cultivating diverse inputs, professionals can unlock unprecedented levels of creativity and productivity.