Assistant Professor of Electrical Engineering and Computer Science, College of Engineering
Participatory AI for Social Impact
What You'll Learn
- Recognize the importance of including interested and impacted communities in AI design and development
- Describe principles and methods for participatory AI
- Develop strategies for overcoming challenges when working with communities
2 Modules
4 Hours
2 hrs per module (approx.)
About Participatory AI for Social Impact
AI is rapidly proliferating across society, but negative impacts can arise when communities and stakeholders are not equally involved in the AI development process. In this course, you’ll learn to critically evaluate AI's societal impact and apply participatory design methods, preparing you to develop ethical and inclusive AI solutions for the future.
"Participatory AI for Social Impact" introduces the core philosophy of designing with rather than for users and other stakeholders. Motivated by analyzing case studies where AI for social impact did not achieve the desired goals in the real world, you will learn to identify participatory AI practices and principles and create your own participatory AI plan. We will also discuss the logistical and ethical nuances of implementing participatory AI for social impact, including working with communities. This course will provide a practical toolkit for developing ethical, inclusive AI solutions that prioritize collaboration and positive social impact.
This is the third course in the three-course series, "Realizing AI for Social Impact", where you will explore use cases and frameworks for deploying AI to achieve social impact.
Skills You'll Gain
- Artificial Intelligence
- Community Advocacy
- Data Ethics
- Data Literacy
- Data Management
- Data Quality
- Social Justice
What You'll Earn
- Certificate of Completion
- Certificates of completion acknowledge knowledge acquired upon completion of a non-credit course or program.
Course content developed by U-M faculty and managed by the university. Faculty titles and affiliations are updated periodically.
Welcome Message
Welcome to Participatory AI for Social Impact! This is the third course in a 3-part series in Realizing AI for Social Impact from the University of Michigan. In this course, we discuss ethical and participatory AI development—creating AI with people interested in and impacted by AI—for social impact. We hope this course inspires you to start trying to apply AI techniques in your context, with participation!
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: What is PAI?
- Motivation behind Participatory AI (PAI)
- Benefits of inclusive community involvement through real-world case studies
- Analyzing interactive scenarios to explore how PAI can prevent harm and foster positive social impact
Module 2: How to Apply PAI for Social Impact
- Participatory AI principles from academic surveys and successful case studies
- Applying PAI principles to real-world projects
- Identifying relevant communities
- Designing engagement strategies, including relationship-building and compensation
- Developing plans to mitigate potential challenges
Grading Policy
To pass the course and earn the certificate, learners must achieve an overall grade of 80%. Quizzes make up the entire course grade.
- Quiz: Module 1 Quiz — 50%
- Quiz: Module 2 Quiz — 50%
Beginner Level
Interest in real-world AI application, especially for social challenges. Some knowledge of ethics in AI may be useful, but not required.
