计算机视觉和机器学习用于人权视频分析:案例研究、可能性、关注和局限性

Jay D. Aronson
{"title":"计算机视觉和机器学习用于人权视频分析:案例研究、可能性、关注和局限性","authors":"Jay D. Aronson","doi":"10.1111/lsi.12353","DOIUrl":null,"url":null,"abstract":"<p>Citizen video and other publicly available footage can provide evidence of human rights violations and war crimes. The ubiquity of visual data, however, may overwhelm those faced with preserving and analyzing it. This article examines how machine learning and computer vision can be used to make sense of large volumes of video in advocacy and accountability contexts. These technologies can enhance the efficiency and effectiveness of human rights advocacy and accountability efforts, but only if human rights organizations can access the technologies themselves and learn how to use them to promote human rights. As such, computer scientists and software developers working with the human rights community must understand the context in which their products are used and act in solidarity with practitioners. By working together, practitioners and scientists can level the playing field between the human rights community and the entities that perpetrate, tolerate, or seek to cover up violations.</p>","PeriodicalId":47418,"journal":{"name":"Law and Social Inquiry-Journal of the American Bar Foundation","volume":null,"pages":null},"PeriodicalIF":1.4000,"publicationDate":"2018-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.1111/lsi.12353","citationCount":"14","resultStr":"{\"title\":\"Computer Vision and Machine Learning for Human Rights Video Analysis: Case Studies, Possibilities, Concerns, and Limitations\",\"authors\":\"Jay D. Aronson\",\"doi\":\"10.1111/lsi.12353\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<p>Citizen video and other publicly available footage can provide evidence of human rights violations and war crimes. The ubiquity of visual data, however, may overwhelm those faced with preserving and analyzing it. This article examines how machine learning and computer vision can be used to make sense of large volumes of video in advocacy and accountability contexts. These technologies can enhance the efficiency and effectiveness of human rights advocacy and accountability efforts, but only if human rights organizations can access the technologies themselves and learn how to use them to promote human rights. As such, computer scientists and software developers working with the human rights community must understand the context in which their products are used and act in solidarity with practitioners. By working together, practitioners and scientists can level the playing field between the human rights community and the entities that perpetrate, tolerate, or seek to cover up violations.</p>\",\"PeriodicalId\":47418,\"journal\":{\"name\":\"Law and Social Inquiry-Journal of the American Bar Foundation\",\"volume\":null,\"pages\":null},\"PeriodicalIF\":1.4000,\"publicationDate\":\"2018-03-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"https://sci-hub-pdf.com/10.1111/lsi.12353\",\"citationCount\":\"14\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Law and Social Inquiry-Journal of the American Bar Foundation\",\"FirstCategoryId\":\"90\",\"ListUrlMain\":\"https://onlinelibrary.wiley.com/doi/10.1111/lsi.12353\",\"RegionNum\":2,\"RegionCategory\":\"社会学\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q1\",\"JCRName\":\"LAW\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Law and Social Inquiry-Journal of the American Bar Foundation","FirstCategoryId":"90","ListUrlMain":"https://onlinelibrary.wiley.com/doi/10.1111/lsi.12353","RegionNum":2,"RegionCategory":"社会学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"LAW","Score":null,"Total":0}
引用次数: 14

摘要

公民录像和其他可公开获得的录像可以提供侵犯人权和战争罪行的证据。然而,无处不在的视觉数据可能会使那些面临保存和分析它的人不知所措。本文探讨了如何使用机器学习和计算机视觉来理解宣传和问责背景下的大量视频。这些技术可以提高人权倡导和问责工作的效率和效果,但前提是人权组织能够自己使用这些技术,并学会如何利用这些技术促进人权。因此,与人权界合作的计算机科学家和软件开发人员必须了解其产品的使用背景,并与从业人员团结一致。通过共同努力,从业者和科学家可以在人权界与实施、容忍或试图掩盖侵权行为的实体之间创造公平的竞争环境。
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
Computer Vision and Machine Learning for Human Rights Video Analysis: Case Studies, Possibilities, Concerns, and Limitations

Citizen video and other publicly available footage can provide evidence of human rights violations and war crimes. The ubiquity of visual data, however, may overwhelm those faced with preserving and analyzing it. This article examines how machine learning and computer vision can be used to make sense of large volumes of video in advocacy and accountability contexts. These technologies can enhance the efficiency and effectiveness of human rights advocacy and accountability efforts, but only if human rights organizations can access the technologies themselves and learn how to use them to promote human rights. As such, computer scientists and software developers working with the human rights community must understand the context in which their products are used and act in solidarity with practitioners. By working together, practitioners and scientists can level the playing field between the human rights community and the entities that perpetrate, tolerate, or seek to cover up violations.

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
CiteScore
2.10
自引率
0.00%
发文量
53
期刊最新文献
Mercy and the Construction of Social Control: A Four-Site Analysis of Clemency Exclusion from Within: Noncitizens and the Rise of Discriminatory Licensing Laws Legal Strategies at the Governance Precipice: Transnational Lawyers in the European Union’s Sovereign Debt Crisis (2010–2012) Aspirational Laws in Action: A Field Experiment Many Shades of Success: Bottom-up Indicators of Individual Success in Community Courts
×
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