提高自动化决策系统的问责制:对加拿大临时居民签证移民流中引入的自动化决策系统进行评估

Lucia Nalbandian
{"title":"提高自动化决策系统的问责制:对加拿大临时居民签证移民流中引入的自动化决策系统进行评估","authors":"Lucia Nalbandian","doi":"10.1016/j.jrt.2021.100023","DOIUrl":null,"url":null,"abstract":"<div><p>States are increasingly turning to automated decision-making systems to increase efficiency in program and service delivery. While automation offers several desirable benefits, great care must be given to establishing and increasing the accountability of automated decision-making systems in the public sector. This paper focuses on accountability in automated decision-making systems in migration management. A key issue is what the impact of automated decision-making is on accountability in migration management? This paper seeks to explore this question by evaluating the accountability mechanisms established by the Canadian government in the use of automated decision-making systems to triage Temporary Resident Visa immigration applications. This paper begins with an explanation of the interaction between public administration and digital governance, with a particular focus on the human decision-making component of public administration and a review of accountability in the public sector. What follows is an explanation of how decision-making in Canada's Temporary Resident Visa Application stream traditionally occurs. A brief review of the Canadian Algorithmic Impact Assessment Tool introduces a thorough explanation of the Canadian government's Temporary Resident Visa (TRV) eApps Advanced Analytics Pilot to showcase changes between the traditional human decision-making process and the more recent experiment engaging automated decision-making in this particular immigration stream. The paper concludes by posing a question on what accountability amounts to for the Canadian government and whether the accountability measures introduced in Canada's TRV Pilot are sufficient.</p></div>","PeriodicalId":73937,"journal":{"name":"Journal of responsible technology","volume":null,"pages":null},"PeriodicalIF":0.0000,"publicationDate":"2022-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.sciencedirect.com/science/article/pii/S2666659621000160/pdfft?md5=e526f7abf3ed60ab11a78339e2b562a5&pid=1-s2.0-S2666659621000160-main.pdf","citationCount":"3","resultStr":"{\"title\":\"Increasing the accountability of automated decision-making systems: An assessment of the automated decision-making system introduced in Canada's temporary resident visa immigration stream\",\"authors\":\"Lucia Nalbandian\",\"doi\":\"10.1016/j.jrt.2021.100023\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<div><p>States are increasingly turning to automated decision-making systems to increase efficiency in program and service delivery. While automation offers several desirable benefits, great care must be given to establishing and increasing the accountability of automated decision-making systems in the public sector. This paper focuses on accountability in automated decision-making systems in migration management. A key issue is what the impact of automated decision-making is on accountability in migration management? This paper seeks to explore this question by evaluating the accountability mechanisms established by the Canadian government in the use of automated decision-making systems to triage Temporary Resident Visa immigration applications. This paper begins with an explanation of the interaction between public administration and digital governance, with a particular focus on the human decision-making component of public administration and a review of accountability in the public sector. What follows is an explanation of how decision-making in Canada's Temporary Resident Visa Application stream traditionally occurs. A brief review of the Canadian Algorithmic Impact Assessment Tool introduces a thorough explanation of the Canadian government's Temporary Resident Visa (TRV) eApps Advanced Analytics Pilot to showcase changes between the traditional human decision-making process and the more recent experiment engaging automated decision-making in this particular immigration stream. The paper concludes by posing a question on what accountability amounts to for the Canadian government and whether the accountability measures introduced in Canada's TRV Pilot are sufficient.</p></div>\",\"PeriodicalId\":73937,\"journal\":{\"name\":\"Journal of responsible technology\",\"volume\":null,\"pages\":null},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2022-07-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"https://www.sciencedirect.com/science/article/pii/S2666659621000160/pdfft?md5=e526f7abf3ed60ab11a78339e2b562a5&pid=1-s2.0-S2666659621000160-main.pdf\",\"citationCount\":\"3\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Journal of responsible technology\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://www.sciencedirect.com/science/article/pii/S2666659621000160\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Journal of responsible technology","FirstCategoryId":"1085","ListUrlMain":"https://www.sciencedirect.com/science/article/pii/S2666659621000160","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 3

摘要

各州越来越多地转向自动化决策系统,以提高项目和服务提供的效率。虽然自动化提供了一些令人满意的好处,但必须非常注意在公共部门建立和增加自动化决策系统的责任制。本文的重点是在移民管理自动化决策系统的问责制。一个关键问题是自动化决策对迁移管理中的问责制的影响是什么?本文试图通过评估加拿大政府在使用自动决策系统来分类临时居民签证移民申请时建立的问责机制来探讨这个问题。本文首先解释了公共行政与数字治理之间的相互作用,特别关注公共行政的人力决策部分和对公共部门问责制的审查。以下是对加拿大临时居留签证申请流程的传统决策过程的解释。对加拿大算法影响评估工具的简要回顾介绍了加拿大政府临时居留签证(TRV) eApps高级分析试点的全面解释,以展示传统的人工决策过程与最近在这一特定移民流中进行自动化决策的实验之间的变化。本文最后提出了一个问题,即问责制对加拿大政府来说意味着什么,以及加拿大TRV试点中引入的问责制措施是否足够。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
查看原文
分享 分享
微信好友 朋友圈 QQ好友 复制链接
本刊更多论文
Increasing the accountability of automated decision-making systems: An assessment of the automated decision-making system introduced in Canada's temporary resident visa immigration stream

States are increasingly turning to automated decision-making systems to increase efficiency in program and service delivery. While automation offers several desirable benefits, great care must be given to establishing and increasing the accountability of automated decision-making systems in the public sector. This paper focuses on accountability in automated decision-making systems in migration management. A key issue is what the impact of automated decision-making is on accountability in migration management? This paper seeks to explore this question by evaluating the accountability mechanisms established by the Canadian government in the use of automated decision-making systems to triage Temporary Resident Visa immigration applications. This paper begins with an explanation of the interaction between public administration and digital governance, with a particular focus on the human decision-making component of public administration and a review of accountability in the public sector. What follows is an explanation of how decision-making in Canada's Temporary Resident Visa Application stream traditionally occurs. A brief review of the Canadian Algorithmic Impact Assessment Tool introduces a thorough explanation of the Canadian government's Temporary Resident Visa (TRV) eApps Advanced Analytics Pilot to showcase changes between the traditional human decision-making process and the more recent experiment engaging automated decision-making in this particular immigration stream. The paper concludes by posing a question on what accountability amounts to for the Canadian government and whether the accountability measures introduced in Canada's TRV Pilot are sufficient.

求助全文
通过发布文献求助,成功后即可免费获取论文全文。 去求助
来源期刊
Journal of responsible technology
Journal of responsible technology Information Systems, Artificial Intelligence, Human-Computer Interaction
CiteScore
3.60
自引率
0.00%
发文量
0
审稿时长
168 days
期刊最新文献
Start doing the right thing: Indicators for socially responsible start-ups and investors Virtual Social Labs – Requirements and Challenges for Effective Team Collaboration A call to action: Designing a more transparent online world for children and young people Embedding responsible innovation into R&D practices: A case study of socially assistive robot development
×
引用
GB/T 7714-2015
复制
MLA
复制
APA
复制
导出至
BibTeX EndNote RefMan NoteFirst NoteExpress
×
×
提示
您的信息不完整,为了账户安全,请先补充。
现在去补充
×
提示
您因"违规操作"
具体请查看互助需知
我知道了
×
提示
现在去查看 取消
×
提示
确定
0
微信
客服QQ
Book学术公众号 扫码关注我们
反馈
×
意见反馈
请填写您的意见或建议
请填写您的手机或邮箱
已复制链接
已复制链接
快去分享给好友吧!
我知道了
×
扫码分享
扫码分享
Book学术官方微信
Book学术文献互助
Book学术文献互助群
群 号:481959085
Book学术
文献互助 智能选刊 最新文献 互助须知 联系我们:info@booksci.cn
Book学术提供免费学术资源搜索服务,方便国内外学者检索中英文文献。致力于提供最便捷和优质的服务体验。
Copyright © 2023 Book学术 All rights reserved.
ghs 京公网安备 11010802042870号 京ICP备2023020795号-1