Data Science Ethics Lecturer, School of Information
Generative AI: Impact on Business and Society
What You'll Learn
- Understand the global nature of generative AI products and the diversity of its users
- Make informed business decisions regarding the impact and risks of generative AI systems
- Critically consider the different ways that generative AI impacts society
3 Modules
3 Hours
1 hr per module (approx.)
Rating
About Generative AI: Impact on Business and Society
Generative artificial intelligence (AI) systems can have a range of impacts on both business and society. In “Generative AI: Impact on Business and Society,” you’ll consider the social and technological aspects of these systems to evaluate how they may impact the way we adopt, trust, or work with these tools. This course builds on your knowledge of the benefits, challenges, and potential risks of AI as we begin integrating these tools into our organizations or communities. It includes considerations relevant to business operations, impact on consumers, as well as wider implications for citizens, public safety, and the environment. By the end of this course, you’ll be able to evaluate the global and local implications specific to generative AI systems for informed decision-making in your role.
Skills You'll Gain
- AI Innovation
- Brand Management
- Corporate Sustainability
- Decision Making
- Ethical AI
- Generative Artificial Intelligence
- Responsible AI
- Risk Management
- Systems 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
Welcome to Generative AI: Impact on Business and Society, the second course in the Responsible Generative AI series. This online course examines generative AI through a socio-technical lens, focusing on business decision-making and broader societal effects. You will explore key risks, ethical considerations, and impacts on trust, public safety, and the environment to support informed, responsible use of generative AI technologies.
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
- Video: Linguistic Diversity in GenAI
- Video: Image Diversity in GenAI
- Video: Anthropomorphic Design
- Video: Limitations of Current Disclosures
- Video: Consequences of Design
Module 2: Informed Choices — Mitigating Generative AI Risks in Business
- Reading: Module Introduction
- Reading: Priorities for Businesses Adopting Generative AI
- Video: Reputational Risks
- Video: Liability Risks
- Video: Business Continuity
- Video: Regulatory Warnings
- Video: Importance of Responsible GenAI
- Discussion Prompt: Challenges of International Development
Module 3: Generative AI’s Societal Impact: A Critical Overview
- Reading: Module Introduction
- Video: Societal Impact of Generative AI
- Video: Integrity of Information
- Video: Erosion of Trust
- Video: Environmental Impact
- Discussion Prompt: Stakeholder Impact of Generative AI
- Reading: Supplemental Resources
- Reading: Post-course Survey
- Reading: Staying Current with Responsible Generative AI and Governance
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 are required.
