Assistant Professor of Electrical Engineering and Computer Science
3 Learning Experiences
Realizing AI for Social Impact
3-Course Series
12 hours
4 hours per course (approx.)
About Realizing AI for Social Impact
"Realizing AI for Social Impact" explores how AI can contribute to social impact, examining applications across various fields like public health and conservation. Learners will explore multiple AI techniques, from machine learning to reinforcement learning, while addressing the challenges of rapidly evolving technologies. The series emphasizes practical and ethical considerations of deploying AI, especially working with communities in resource-constrained environments.
Skills You'll Gain
- Data Literacy
- Data Management
- Data Quality
- Artificial Intelligence
- Data Ethics
- Social Justice
- Community Advocacy
Course content developed by U-M faculty and managed by the university. Faculty titles and affiliations are updated periodically.
Beginner Level
Interest in deploying AI systems for social impact is key. Some familiarity with machine learning concepts may be helpful, but is not required.
3 Courses in this series
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Free U-M Access CourseDefining AI for Social Impact
Learn how AI can be useful and what its ethical limits are in social impact work.
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Free U-M Access CoursePractical AI for Social Impact
Understand how to handle data, avoid bias, and use AI ethically in your community.
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Free U-M Access CourseParticipatory AI for Social Impact
Design AI solutions with users, not just for users.
