{"title":"关键数据伦理教学法:三种(非竞争性)方法","authors":"Luis Felipe R Murillo, Caitlin Wylie, Phil Bourne","doi":"10.1177/20539517231203666","DOIUrl":null,"url":null,"abstract":"In a moment of heightened ethical questioning concerning data-intensive analytics, “data ethics” has become a site of dispute over its very definition in teaching, research, and practice. In this paper, we contextualize this dispute based on the experience of teaching data ethics. We describe how the field of computer ethics has historically informed the training of computer experts and how, in recent years, the scholarship on science and technology studies has created opportunities for transforming the way we teach with the inclusion of critical scholarship on relational ethics and sociotechnical systems. The emergent literature on “critical data ethics” has created a space for interdisciplinary collaboration that integrates technical and social science research to examine digital systems in their design, implementation, and use through a hands-on approach. As a contribution to the recent efforts to reimagine and transform the field of data science, we conclude with a discussion of the approach we devised to bridge technology/society divides and engage students with questions of social justice, accountability, and openness in their data practices.","PeriodicalId":47834,"journal":{"name":"Big Data & Society","volume":"340 1","pages":"0"},"PeriodicalIF":6.5000,"publicationDate":"2023-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Critical data ethics pedagogies: Three (non-rival) approaches\",\"authors\":\"Luis Felipe R Murillo, Caitlin Wylie, Phil Bourne\",\"doi\":\"10.1177/20539517231203666\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"In a moment of heightened ethical questioning concerning data-intensive analytics, “data ethics” has become a site of dispute over its very definition in teaching, research, and practice. In this paper, we contextualize this dispute based on the experience of teaching data ethics. We describe how the field of computer ethics has historically informed the training of computer experts and how, in recent years, the scholarship on science and technology studies has created opportunities for transforming the way we teach with the inclusion of critical scholarship on relational ethics and sociotechnical systems. The emergent literature on “critical data ethics” has created a space for interdisciplinary collaboration that integrates technical and social science research to examine digital systems in their design, implementation, and use through a hands-on approach. As a contribution to the recent efforts to reimagine and transform the field of data science, we conclude with a discussion of the approach we devised to bridge technology/society divides and engage students with questions of social justice, accountability, and openness in their data practices.\",\"PeriodicalId\":47834,\"journal\":{\"name\":\"Big Data & Society\",\"volume\":\"340 1\",\"pages\":\"0\"},\"PeriodicalIF\":6.5000,\"publicationDate\":\"2023-07-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Big Data & Society\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1177/20539517231203666\",\"RegionNum\":1,\"RegionCategory\":\"社会学\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q1\",\"JCRName\":\"SOCIAL SCIENCES, INTERDISCIPLINARY\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Big Data & Society","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1177/20539517231203666","RegionNum":1,"RegionCategory":"社会学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"SOCIAL SCIENCES, INTERDISCIPLINARY","Score":null,"Total":0}
Critical data ethics pedagogies: Three (non-rival) approaches
In a moment of heightened ethical questioning concerning data-intensive analytics, “data ethics” has become a site of dispute over its very definition in teaching, research, and practice. In this paper, we contextualize this dispute based on the experience of teaching data ethics. We describe how the field of computer ethics has historically informed the training of computer experts and how, in recent years, the scholarship on science and technology studies has created opportunities for transforming the way we teach with the inclusion of critical scholarship on relational ethics and sociotechnical systems. The emergent literature on “critical data ethics” has created a space for interdisciplinary collaboration that integrates technical and social science research to examine digital systems in their design, implementation, and use through a hands-on approach. As a contribution to the recent efforts to reimagine and transform the field of data science, we conclude with a discussion of the approach we devised to bridge technology/society divides and engage students with questions of social justice, accountability, and openness in their data practices.
期刊介绍:
Big Data & Society (BD&S) is an open access, peer-reviewed scholarly journal that publishes interdisciplinary work principally in the social sciences, humanities, and computing and their intersections with the arts and natural sciences. The journal focuses on the implications of Big Data for societies and aims to connect debates about Big Data practices and their effects on various sectors such as academia, social life, industry, business, and government.
BD&S considers Big Data as an emerging field of practices, not solely defined by but generative of unique data qualities such as high volume, granularity, data linking, and mining. The journal pays attention to digital content generated both online and offline, encompassing social media, search engines, closed networks (e.g., commercial or government transactions), and open networks like digital archives, open government, and crowdsourced data. Rather than providing a fixed definition of Big Data, BD&S encourages interdisciplinary inquiries, debates, and studies on various topics and themes related to Big Data practices.
BD&S seeks contributions that analyze Big Data practices, involve empirical engagements and experiments with innovative methods, and reflect on the consequences of these practices for the representation, realization, and governance of societies. As a digital-only journal, BD&S's platform can accommodate multimedia formats such as complex images, dynamic visualizations, videos, and audio content. The contents of the journal encompass peer-reviewed research articles, colloquia, bookcasts, think pieces, state-of-the-art methods, and work by early career researchers.