Teaching Responsible Data Science

Teaching Responsible Data Science
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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:
DataEd '22: 1st International Workshop on Data Systems Education
影响因子:
--
通讯作者:
Stoyanovich, Julia
Stoyanovich, Julia
中科院分区:
--
文献类型:
--
作者:
Stoyanovich, Julia

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负责任的数据科学(RDS)和负责任的人工智能(RAI)已经成为研究和实践的重要领域。然而,关于这一重要问题的教育材料和方法仍然缺乏。在本文中,我将讲述我在开发、教学和完善一门名为“负责任的数据科学”的技术课程方面的经验,该课程涉及人工智能中的道德问题、法律的合规性、数据质量、算法的公平性和多样性、数据和算法的透明度、隐私和数据保护。我还将介绍一门名为“我们是人工智能:控制技术”的公共教育课程,该课程将人工智能伦理的这些主题带到了同行学习的环境中。我把所有的课程材料都公开在网上,希望能激励社区中的其他人走到一起,形成对RDS和RAI的教学需求的更深入的理解,并开发和分享急需的具体教育材料和方法。
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.
存在隐性偏见时的选择问题
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
数据和模型的营养标签
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
克服机器学习管道中的技术偏见
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
因果交叉性和公平排名
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
DOI: 10.1145/2447976.2447990
发表时间: 2013-05-01
影响因子: 22.7
作者:
Sweeney, Latanya
通讯作者: Sweeney, Latanya