Data Science Ethics Lecturer, School of Information
Generative AI: Labor and the Future of Work
What You'll Learn
- Explore scenarios for the future of work
- Discuss the impact generative AI could have on labor and business
- Make informed assessments about labor involvement in generative AI technologies
2 Modules
4 Hours
2 hrs per module (approx.)
Rating
About Generative AI: Labor and the Future of Work
This course gives a broad overview of the impact that generative artificial intelligence (AI) could have on jobs and how it can be used to support everyday tasks. As the use of generative AI increases, organizations are finding new ways to augment their work, impacting the number and types of jobs we can expect in the future. In “Generative AI: Labor and the Future of Work,” you’ll explore how generative AI can support workers in all industries, as well as the labor that goes into developing and managing these systems. Explore what the “future of work” could mean for both employees and employers and how these systems can impact work quality, creativity, and the labor market. You’ll also look at how the global digital divide could impact tool adoption for different groups across the world. By analyzing the adoption and implementation of generative AI in the workplace, you will better understand how these tools could shift how we work together.
Skills You'll Gain
- AI Innovation
- Change Management
- Decision Making
- Ethical AI
- Generative Artificial Intelligence
- Human Capital
- Human Resource Management
- Responsible AI
- Strategic Thinking
What You'll Earn
- Certificate of Completion:
- Certificates of completion acknowledge knowledge acquired upon completion of a non-credit course or program.
Welcome Message
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: Introduction to the Course
- Reading: Welcome to the Course & Course Syllabus
- Discussion Prompt: Introduce Yourself
- Reading: Help Us Learn About You!
- Reading: Module Introduction
- Reading: What comes to mind when we say generative AI and future of work?
- Video: Unseen Labor in Generative AI
- Video: Data Labeling
- Video: Content Moderation & Human Feedback
- Discussion Prompt: Reflection: Labor and Data Quality Risks
Module 2: Forecasting Labor Futures: Readiness and Implications
- Reading: Module Introduction
- Video: Labor and Market Forecasts
- Video: Augment vs Reallocate vs Displace
- Video: Labor Readiness
- Video: Labor Reskilling & Deskilling
- Video: Digital Divide
- Discussion Prompt: Reflection: Future Implications of GenAI
- Reading: Supplemental Resources
- Reading: Post-course Survey
- Reading: Staying Current with Responsible Generative AI and Governance
- Reading: Continue your AI education with the AI Collection from Michigan Online
Grading Policy
Learners must complete all required assessments to pass the course. An overall score of 80% or higher is required to earn the certificate. The course grade is based on two knowledge checks worth 40% each, and two honor code assignments worth 10% each.
Course content developed by U-M faculty and managed by the university. Faculty titles and affiliations are updated periodically.
Beginner Level
No prerequisites required.
