Critical Thinking in Data Science
APCOMP 221
Subject & Catalog Number
Course Information
Description
This course examines the wide-ranging impact data science has on the world and how to think critically about issues of fairness, privacy, ethics, and bias while building algorithms and predictive models that get deployed in the form of products, policy and scientific research. Topics will include algorithmic accountability and discriminatory algorithms, black box algorithms, data privacy and security, ethical frameworks; and experimental and product design. We will work through case studies in a variety of contexts including media, tech and sharing economy platforms; medicine and public health; data science for social good, and politics. We will look at the underlying machine learning algorithms, statistical models, code and data. Threads of history, philosophy, business models and strategy; and regulatory and policy issues will be woven throughout the course.
Course Notes
This does not count as a technical or disciplinary course for SEAS PhD students, nor for SEAS masters-degree students outside of CSE and Data Science.
Recommended Prep
CS 1090A, Introduction to Data Science or equivalent by instructor approval.
Available for Harvard Cross Registration
