{"title":"计算算法时要考虑什么:关于算法问责制的系统文献综述","authors":"M. Wieringa","doi":"10.1145/3351095.3372833","DOIUrl":null,"url":null,"abstract":"As research on algorithms and their impact proliferates, so do calls for scrutiny/accountability of algorithms. A systematic review of the work that has been done in the field of 'algorithmic accountability' has so far been lacking. This contribution puts forth such a systematic review, following the PRISMA statement. 242 English articles from the period 2008 up to and including 2018 were collected and extracted from Web of Science and SCOPUS, using a recursive query design coupled with computational methods. The 242 articles were prioritized and ordered using affinity mapping, resulting in 93 'core articles' which are presented in this contribution. The recursive search strategy made it possible to look beyond the term 'algorithmic accountability'. That is, the query also included terms closely connected to the theme (e.g. ethics and AI, regulation of algorithms). This approach allows for a perspective not just from critical algorithm studies, but an interdisciplinary overview drawing on material from data studies to law, and from computer science to governance studies. To structure the material, Bovens's widely accepted definition of accountability serves as a focal point. The material is analyzed on the five points Bovens identified as integral to accountability: its arguments on (1) the actor, (2) the forum, (3) the relationship between the two, (3) the content and criteria of the account, and finally (5) the consequences which may result from the account. The review makes three contributions. First, an integration of accountability theory in the algorithmic accountability discussion. Second, a cross-sectoral overview of the that same discussion viewed in light of accountability theory which pays extra attention to accountability risks in algorithmic systems. Lastly, it provides a definition of algorithmic accountability based on accountability theory and algorithmic accountability literature.","PeriodicalId":377829,"journal":{"name":"Proceedings of the 2020 Conference on Fairness, Accountability, and Transparency","volume":"62 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2020-01-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"155","resultStr":"{\"title\":\"What to account for when accounting for algorithms: a systematic literature review on algorithmic accountability\",\"authors\":\"M. Wieringa\",\"doi\":\"10.1145/3351095.3372833\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"As research on algorithms and their impact proliferates, so do calls for scrutiny/accountability of algorithms. A systematic review of the work that has been done in the field of 'algorithmic accountability' has so far been lacking. This contribution puts forth such a systematic review, following the PRISMA statement. 242 English articles from the period 2008 up to and including 2018 were collected and extracted from Web of Science and SCOPUS, using a recursive query design coupled with computational methods. The 242 articles were prioritized and ordered using affinity mapping, resulting in 93 'core articles' which are presented in this contribution. The recursive search strategy made it possible to look beyond the term 'algorithmic accountability'. That is, the query also included terms closely connected to the theme (e.g. ethics and AI, regulation of algorithms). This approach allows for a perspective not just from critical algorithm studies, but an interdisciplinary overview drawing on material from data studies to law, and from computer science to governance studies. To structure the material, Bovens's widely accepted definition of accountability serves as a focal point. The material is analyzed on the five points Bovens identified as integral to accountability: its arguments on (1) the actor, (2) the forum, (3) the relationship between the two, (3) the content and criteria of the account, and finally (5) the consequences which may result from the account. The review makes three contributions. First, an integration of accountability theory in the algorithmic accountability discussion. Second, a cross-sectoral overview of the that same discussion viewed in light of accountability theory which pays extra attention to accountability risks in algorithmic systems. Lastly, it provides a definition of algorithmic accountability based on accountability theory and algorithmic accountability literature.\",\"PeriodicalId\":377829,\"journal\":{\"name\":\"Proceedings of the 2020 Conference on Fairness, Accountability, and Transparency\",\"volume\":\"62 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2020-01-22\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"155\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Proceedings of the 2020 Conference on Fairness, Accountability, and Transparency\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1145/3351095.3372833\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Proceedings of the 2020 Conference on Fairness, Accountability, and Transparency","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1145/3351095.3372833","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 155
摘要
随着对算法及其影响的研究激增,对算法的审查/问责制的要求也在增加。迄今为止,还缺乏对“算法问责制”领域所做工作的系统审查。这篇文章在PRISMA声明之后提出了这样一个系统的审查。采用递归查询设计与计算方法相结合的方法,从Web of Science和SCOPUS中收集并提取了2008年至2018年期间的242篇英文论文。使用关联映射对242篇文章进行了优先级排序和排序,从而产生了93篇“核心文章”。递归搜索策略使得超越“算法责任”这一术语成为可能。也就是说,查询还包括与主题密切相关的术语(例如道德和人工智能,算法监管)。这种方法不仅考虑了关键算法研究的视角,还考虑了从数据研究到法律,从计算机科学到治理研究的跨学科概述。为了构建材料,Bovens对问责制的广泛接受的定义是一个焦点。这些材料是根据博文斯认为的问责制不可或缺的五点进行分析的:它的论点是(1)行动者,(2)论坛,(3)两者之间的关系,(3)描述的内容和标准,最后(5)描述可能产生的后果。这篇综述有三点贡献。首先,将问责理论整合到算法问责讨论中。其次,根据问责制理论对同一讨论进行跨部门概述,该理论特别关注算法系统中的问责制风险。最后,基于问责理论和算法问责相关文献,给出了算法问责的定义。
What to account for when accounting for algorithms: a systematic literature review on algorithmic accountability
As research on algorithms and their impact proliferates, so do calls for scrutiny/accountability of algorithms. A systematic review of the work that has been done in the field of 'algorithmic accountability' has so far been lacking. This contribution puts forth such a systematic review, following the PRISMA statement. 242 English articles from the period 2008 up to and including 2018 were collected and extracted from Web of Science and SCOPUS, using a recursive query design coupled with computational methods. The 242 articles were prioritized and ordered using affinity mapping, resulting in 93 'core articles' which are presented in this contribution. The recursive search strategy made it possible to look beyond the term 'algorithmic accountability'. That is, the query also included terms closely connected to the theme (e.g. ethics and AI, regulation of algorithms). This approach allows for a perspective not just from critical algorithm studies, but an interdisciplinary overview drawing on material from data studies to law, and from computer science to governance studies. To structure the material, Bovens's widely accepted definition of accountability serves as a focal point. The material is analyzed on the five points Bovens identified as integral to accountability: its arguments on (1) the actor, (2) the forum, (3) the relationship between the two, (3) the content and criteria of the account, and finally (5) the consequences which may result from the account. The review makes three contributions. First, an integration of accountability theory in the algorithmic accountability discussion. Second, a cross-sectoral overview of the that same discussion viewed in light of accountability theory which pays extra attention to accountability risks in algorithmic systems. Lastly, it provides a definition of algorithmic accountability based on accountability theory and algorithmic accountability literature.