Machine Learning Ethics
Courses
- Summer Institutes for Computational Social Science
- People + AI
- Google AI ML fairness lectures
- Law for Computer Scientists
- Berkeley course on Social Movements and Social Media
- Syllabus • Human-AI Interaction • Fall 2022 • CMSC 848C - UMD by Hal Daume
Books
- PATTERNS, PREDICTIONS, AND ACTIONS: A story about machine learning - Moritz Hardt and Benjamin Recht
- Trust and Artificial Intelligence by Brian Stanton, Theodore Jensen
- How Humans Judge Machines
- Fairness and machine learning Limitations and Opportunities Solon Barocas, Moritz Hardt, Arvind Narayanan
- Trustworthy Machine Learning by Kush R. Varshney
Tools
Links
- Awesome list
- Ethics courses syllabus
- Ironies of Automation
- Ethics checklist for data science
- Artificial Intelligence and Human Rights
- ML gone wrong, a beginners explanation of AI ethics
- Content moderation reading list by Social Media Collective lab
- ML Fairness overview
- Tutorial Series: Limits of Social Data
- Tutorial
- Using Big Data to Solve Economic and Social Problems
- CS269 - Special Topic in AI: Fairness, Accountability, and Transparency in Natural Language Processing
- Challenges of incorporating algorithmic fairness into practice
- Tech Ethics Curriculum