Professor, Communication & Media and Political Science
Generative AI: Forecasting Disruption
What You'll Learn
- Explain the basics of generative AI tools
- Compare the effects of generative AI to earlier technological advances
- Identify the key accomplishments and limitations of generative AI tools
- Identify basic strategies for writing prompts for generative AI
3 Modules
3 Hours
1 hr per module (approx.)
Rating
About Generative AI: Forecasting Disruption
For centuries, society has considered revolutionary technologies like the printing press, the telegraph, and even the first computers major disruptors of work and life.
“Generative AI: Forecasting Disruption” lays the foundation for understanding our reaction to the rise of generative artificial intelligence by looking to the past. We examine a brief history of previous “revolutionary” communication technologies and how their impact can inform the way we think about advances in generative AI. You’ll then explore the nature of generative AI, how it works, and what it can do. As the course concludes, you’ll learn how to improve your results when using generative AI, and recognize what AI can – and cannot – accomplish.
This is the first course in “Navigating Disruption: Generative AI in the Workplace,” a course series on ways to respond to new advances in AI in the workplace and our lives.
Skills You'll Gain
- AI Innovation
- Decision Making
- Generative Adversarial Networks
- Generative AI Agents
- Generative Artificial Intelligence
- Generative Model Architectures
- Innovation Management
- Prompt Engineering
What You'll Earn
- Certificate of Completion:
- Certificates of completion acknowledge knowledge acquired upon completion of a non-credit course or program.
Welcome Message
Welcome to Generative AI: Forecasting Disruption, an online course and the first course in the Navigating Disruption: Generative AI in the Workplace series. This course uses historical examples of transformative technologies to frame today’s rise of generative AI. You will explore how AI works, what it enables, and where its limits lie, helping you critically assess its disruptive potential in work and everyday life.
This abbreviated syllabus description was created with the help of AI tools and reviewed by staff. The full syllabus is available to those who enroll in the course.
Course Schedule
Module 1: Getting Started
- Video: Series Overview & Course Introduction
- Reading: Course Syllabus
- Discussion Prompt: Reflect on Your Experience
- Reading: Pre-Course Survey
- Video: AI & the Printing Press
- Video: Disruptive Information and Communication Technology
- Reading: Artificial Intelligence: An Unprecedented Disruption
- Video: Why It Is Important to Understand How AI Works
Module 2: Affordances of AI
- Video: Flavors of AI
- Video: Understanding LLMs
- Reading: Previewing Predict the Next Word Activity
- Ungraded Plugin: Activity (Part 1): Predict the Next Word
- Reading: Activity (Part 2): What the Model Learned
- Discussion Prompt: Reflecting on LLMs
- Video: Generating Images with AI
- Reading: Activity: The Turing Test
- Discussion Prompt: Turing Test Reflection
- Video: Crash Course in Prompt Engineering
- Reading: Activity: How Word Choice Effects AI Outputs
- Discussion Prompt: Reflecting on Word Choice & AI Outputs
Module 3: Limitations of AI
- Video: Understanding How AI Learns
- Video: Imperfections of AI
- Reading: The CLEAR Framework
- Video: Can AI Pass the Turing Test and Does it Matter?
- Reading: End of Course Survey
Grading Policy
To pass the course and earn a certificate, learners must complete the required graded assignment with a score of 80% or higher. The graded assignment, “Prompt Evaluation & Reflection,” comprises 100% of the course grade.
Course content developed by U-M faculty and managed by the university. Faculty titles and affiliations are updated periodically.
Beginner Level
No prior experience required
