Responsible Data Science

Catalog description

/ NUTR 1520 An introduction to the issues of ethics and responsibility in data science. Topics include Value Sensitive Design (a theoretical framework for technology design incorporating human values), ethical considerations at each stage of the data science lifecycle - data collection, data preprocessing, modeling, testing and validation, and deployment - and the resulting responsibility of the data science practitioner, issues related to algorithmic fairness, transparency and interpretability of models and systems, and data privacy and protection. Cross-listed With CEMA 2050 - Responsible Data Science (3)