Course Detail
Course Components:
Enrollment Information
Enrollment Requirement:
Prerequisites: 'C-' or better in (BCOR 3040 OR MKTG 3000 OR MKTG 3010 OR MKTG 3011) AND (Intermediate or Full Major or Minor status in the School of Business)
Algorithms are used ubiquitously in business decisions in finance, marketing, operations, human resources, and other areas. While algorithms are efficient, they are not always equitable. This course examines the development of fair algorithms. Students will understand the integration of machine learning algorithms in business decisions; sources that influence their fairness; tools to evaluate fairness (in data collection, pre-processing, in-processing, and post-processing stages); fairness metrics for various business decisions; and the use of explainable and interpretable algorithms for business decisions that require transparency. The pros and cons of using glass-box versus black-box algorithms will be covered along with technical, business, social, legal, and ethical ramifications.