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Title: Teaching Responsible Data Science
Responsible Data Science (RDS) and Responsible AI (RAI) have emerged as prominent areas of research and practice. Yet, educational materials and methodologies on this important subject still lack. In this paper, I will recount my experience in developing, teaching, and refining a technical course called “Responsible Data Science”, which tackles the issues of ethics in AI, legal compliance, data quality, algorithmic fairness and diversity, transparency of data and algorithms, privacy, and data protection. I will also describe a public education course called “We are AI: Taking Control of Technology” that brings these topics of AI ethics to the general audience in a peer-learning setting. I made all course materials are publicly available online, hoping to inspire others in the community to come together to form a deeper understanding of the pedagogical needs of RDS and RAI, and to develop and share the much-needed concrete educational materials and methodologies.  more » « less
Award ID(s):
1922658 1934464 1916505
PAR ID:
10350696
Author(s) / Creator(s):
Date Published:
Journal Name:
DataEd '22: 1st International Workshop on Data Systems Education
Page Range / eLocation ID:
4 to 9
Format(s):
Medium: X
Sponsoring Org:
National Science Foundation
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