Teaching Responsible Data Science
Teaching Responsible Data Science
复制标题
教授负责任的数据科学
DOI:
10.1145/3531072.3535318
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发表时间:
2022
期刊:
影响因子:
--
通讯作者:
Stoyanovich, Julia
中科院分区:
文献类型:
--
作者:
Stoyanovich, Julia
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.
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DOI:
10.4230/lipics.itcs.2018.33
发表时间:
2018
期刊:
ArXiv
影响因子:
--
作者:
J. Kleinberg;Manish Raghavan
通讯作者:
Manish Raghavan
DOI:
--
发表时间:
2019
期刊:
A Quarterly bulletin of the Computer Society of the IEEE Technical Committee on Data Engineering
影响因子:
--
作者:
Stoyanovich, Julia;Howe, Bill
通讯作者:
Howe, Bill
DOI:
--
发表时间:
2020
期刊:
Bulletin of the Technical Committee on Data Engineering
影响因子:
--
作者:
Schelter, Sebastian;Stoyanovich, Julia
通讯作者:
Stoyanovich, Julia
DOI:
--
发表时间:
2021
期刊:
2nd Symposium on Foundations of Responsible Computing (FORC
影响因子:
--
作者:
Yang, Ke;Loftus, Joshua R.;Stoyanovich, Julia
通讯作者:
Stoyanovich, Julia
影响因子:
22.7
作者:
Sweeney, Latanya
通讯作者:
Sweeney, Latanya