Machine Learning Ethics
Courses
- Summer Institutes for Computational Social Science - https://compsocialscience.github.io/summer-institute/teaching-learning-materials
- People + AI - https://pair.withgoogle.com/
- Google AI ML fairness lectures - https://developers.google.com/machine-learning/crash-course/fairness/video-lecture
- Law for Computer Scientists - https://lawforcomputerscientists.pubpub.org/
- Berkeley course on Social Movements and Social Media - https://docs.google.com/document/d/1BFvpSxBOZoKayRUayCZfyUaolj6FEwH7muc5bfYWkRA/edit
- Syllabus • Human-AI Interaction • Fall 2022 • CMSC 848C - UMD by Hal Daume - https://docs.google.com/document/d/1n2GQ5A5cZoucyFkptpr27Nje58L4M9SjA8mE0h83ucg/edit#
Books
- PATTERNS, PREDICTIONS, AND ACTIONS: A story about machine learning - Moritz Hardt and Benjamin Recht - https://mlstory.org/index.html
- Trust and Artificial Intelligence by Brian Stanton, Theodore Jensen - https://www.nist.gov/publications/trust-and-artificial-intelligence
- How Humans Judge Machines - https://www.judgingmachines.com/
- Fairness and machine learning Limitations and Opportunities Solon Barocas, Moritz Hardt, Arvind Narayanan - https://fairmlbook.org/index.html
- Trustworthy Machine Learning by Kush R. Varshney - http://www.trustworthymachinelearning.com/
Tools
- The Bias and Fairness Audit Toolkit - https://github.com/dssg/aequitas
Links
- Awesome list - https://github.com/marikyu7/awesome-artificial-intelligence-ethics
- Ethics courses syllabus - https://medium.com/@cfiesler/tech-ethics-curricula-a-collection-of-syllabi-3eedfb76be18
- Ironies of Automation - http://www.bainbrdg.demon.co.uk/Papers/Ironies.html
- Ethics checklist for data science - http://deon.drivendata.org/
- Artificial Intelligence and Human Rights - https://ai-hr.cyber.harvard.edu/
- ML gone wrong, a beginners explanation of AI ethics - https://machinesgonewrong.com
- Content moderation reading list by Social Media Collective lab - https://socialmediacollective.org/content-moderation-reading-list/
- ML Fairness overview - https://developers.google.com/machine-learning/fairness-overview
- Tutorial Series: Limits of Social Data - http://www.aolteanu.com/SocialDataLimitsTutorial/index.html
- Tutorial - https://github.com/Jindong-Explainable-AI/Bias_in_Machine_Learning
- Using Big Data to Solve Economic and Social Problems - https://opportunityinsights.org/course/
- CS269 - Special Topic in AI: Fairness, Accountability, and Transparency in Natural Language Processing - https://uclanlp.github.io/CS269-Winter2020/index.html
- Challenges of incorporating algorithmic fairness into practice - https://algorithmicbiasinpractice.wordpress.com/slides/
- Tech Ethics Curriculum - https://docs.google.com/spreadsheets/d/1jWIrA8jHz5fYAW4h9CkUD8gKS5V98PDJDymRf8d9vKI/edit#gid=0
Datasets
- Compass Recidivism - https://www.propublica.org/datastore/dataset/compas-recidivism-risk-score-data-and-analysis