Publication Title
Proceedings of the Second Teaching Machine Learning and Artificial Intelligence Workshop
Document Type
Conference Proceeding
Department or Program
Digital and Computational Studies
Publication Date
2022
Abstract
Bates College, is a small liberal arts postsecondary institution in the northeast United States. An information literacy course, Calling Bull, serves as an introductory data science class as well as a prerequisite-free quantitative literacy class. In this context, we spend a week discussing machine learning, with an emphasis on facial recognition algorithms. The emphasis is on the general algorithmic approach, critical inquiry of the process and careful interpretation of results presented in research or decision-making. This module relies on the use of open educational materials, discussion, and careful attention to issues of marginalization and algorithmic justice.
Recommended Citation
Diaz Eaton, C. (2022). Teaching Machine Learning in the Context of Critical Quantitative Information Literacy. Proceedings of the Second Teaching Machine Learning and Artificial Intelligence Workshop, in Proceedings of Machine Learning Research 170:51-56 https://proceedings.mlr.press/v170/eaton22a.html
Copyright Note
© 2021 The Author.
Comments
Original version is available from the publisher at: https://proceedings.mlr.press/v170/eaton22a.html