@inproceedings{a548f34599214d6fb2fc985cc506f47d,
title = "Key concepts for a data science ethics curriculum",
abstract = "Data science is a new field that integrates aspects of computer science, statistics and information management. As a new field, ethical issues a data scientist may encounter have received little attention to date, and ethics training within a data science curriculum has received even less attention. To address this gap, this article explores the different codes of conduct and ethics frameworks related to data science. We compare this analysis with the results of a systematic literature review focusing on ethics in data science. Our analysis identified twelve key ethics areas that should be included within a data science ethics curriculum. Our research notes that none of the existing codes or frameworks covers all of the identified themes. Data science educators and program coordinators can use our results as a way to identify key ethical concepts that can be introduced within a data science program.",
keywords = "Big data, Computing education, Data science, Ethics",
author = "Saltz, {Jeffrey S.} and Dewar, {Neil I.} and Robert Heckman",
note = "Publisher Copyright: {\textcopyright} 2018 Copyright is held by the owner/author(s).; 49th ACM Technical Symposium on Computer Science Education, SIGCSE 2018 ; Conference date: 21-02-2018 Through 24-02-2018",
year = "2018",
month = feb,
day = "21",
doi = "10.1145/3159450.3159483",
language = "English (US)",
series = "SIGCSE 2018 - Proceedings of the 49th ACM Technical Symposium on Computer Science Education",
publisher = "Association for Computing Machinery, Inc",
pages = "952--957",
booktitle = "SIGCSE 2018 - Proceedings of the 49th ACM Technical Symposium on Computer Science Education",
}