贿赂机器:在革命开始时保护算法的完整性

IF 1.3 3区 社会学 Q3 BUSINESS
Philip M. Nichols
{"title":"贿赂机器:在革命开始时保护算法的完整性","authors":"Philip M. Nichols","doi":"10.1111/ablj.12151","DOIUrl":null,"url":null,"abstract":"<p>In the Industrial Revolution, machines took on the burden of physical labor; in the Big Data Revolution, machines are taking on the tasks of making decisions. Algorithms are the rules and processes that enable machines to make those decisions. Machines will make many decisions that affect general well-being. This article addresses a threat to the efficacy of those decisions: the intentional distortion or manipulation of the underlying algorithm so that machines make decisions that benefit self-interested third parties, rather than decisions that enhance public well-being. That threat has not been recognized or addressed by legal thinkers or policy makers. This article first examines the lifecycle of an algorithm, and then demonstrates the likelihood that self-interested third parties will attempt to corrupt the development and operation of algorithms. The article then argues that existing mechanisms cannot protect the integrity of algorithms. The article concludes with a discussion of policies that could protect the integrity of algorithms: transparency in both the development of and the content of algorithms that affect general well-being and holding persons who corrupt the integrity of such algorithms accountable. Just as the Industrial Revolution eventually improved the quality of life for many, so too does the Big Data Revolution offer enhancement of general well-being. That promise, however, will only be realized if policy makers take action to protect the integrity of underlying algorithms now, at the beginning of the revolution.</p>","PeriodicalId":54186,"journal":{"name":"American Business Law Journal","volume":"56 4","pages":"771-814"},"PeriodicalIF":1.3000,"publicationDate":"2019-11-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.1111/ablj.12151","citationCount":"5","resultStr":"{\"title\":\"Bribing the Machine: Protecting the Integrity of Algorithms as the Revolution Begins\",\"authors\":\"Philip M. Nichols\",\"doi\":\"10.1111/ablj.12151\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<p>In the Industrial Revolution, machines took on the burden of physical labor; in the Big Data Revolution, machines are taking on the tasks of making decisions. Algorithms are the rules and processes that enable machines to make those decisions. Machines will make many decisions that affect general well-being. This article addresses a threat to the efficacy of those decisions: the intentional distortion or manipulation of the underlying algorithm so that machines make decisions that benefit self-interested third parties, rather than decisions that enhance public well-being. That threat has not been recognized or addressed by legal thinkers or policy makers. This article first examines the lifecycle of an algorithm, and then demonstrates the likelihood that self-interested third parties will attempt to corrupt the development and operation of algorithms. The article then argues that existing mechanisms cannot protect the integrity of algorithms. The article concludes with a discussion of policies that could protect the integrity of algorithms: transparency in both the development of and the content of algorithms that affect general well-being and holding persons who corrupt the integrity of such algorithms accountable. Just as the Industrial Revolution eventually improved the quality of life for many, so too does the Big Data Revolution offer enhancement of general well-being. That promise, however, will only be realized if policy makers take action to protect the integrity of underlying algorithms now, at the beginning of the revolution.</p>\",\"PeriodicalId\":54186,\"journal\":{\"name\":\"American Business Law Journal\",\"volume\":\"56 4\",\"pages\":\"771-814\"},\"PeriodicalIF\":1.3000,\"publicationDate\":\"2019-11-21\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"https://sci-hub-pdf.com/10.1111/ablj.12151\",\"citationCount\":\"5\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"American Business Law Journal\",\"FirstCategoryId\":\"90\",\"ListUrlMain\":\"https://onlinelibrary.wiley.com/doi/10.1111/ablj.12151\",\"RegionNum\":3,\"RegionCategory\":\"社会学\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q3\",\"JCRName\":\"BUSINESS\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"American Business Law Journal","FirstCategoryId":"90","ListUrlMain":"https://onlinelibrary.wiley.com/doi/10.1111/ablj.12151","RegionNum":3,"RegionCategory":"社会学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q3","JCRName":"BUSINESS","Score":null,"Total":0}
引用次数: 5

摘要

在工业革命中,机器承担了体力劳动的负担;在大数据革命中,机器正在承担决策的任务。算法是使机器能够做出这些决定的规则和过程。机器将做出许多影响整体福祉的决定。本文解决了对这些决策有效性的威胁:故意扭曲或操纵底层算法,以便机器做出有利于自利第三方的决策,而不是提高公共福祉的决策。法律思想家或政策制定者没有认识到或解决这一威胁。本文首先考察了算法的生命周期,然后演示了自利的第三方试图破坏算法的开发和操作的可能性。然后,文章认为现有机制不能保护算法的完整性。文章最后讨论了可以保护算法完整性的政策:影响一般福祉的算法的开发和内容的透明度,以及追究破坏此类算法完整性的人的责任。正如工业革命最终改善了许多人的生活质量一样,大数据革命也提高了人们的总体幸福感。然而,只有政策制定者在革命之初就采取行动保护底层算法的完整性,这一承诺才能实现。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Bribing the Machine: Protecting the Integrity of Algorithms as the Revolution Begins

In the Industrial Revolution, machines took on the burden of physical labor; in the Big Data Revolution, machines are taking on the tasks of making decisions. Algorithms are the rules and processes that enable machines to make those decisions. Machines will make many decisions that affect general well-being. This article addresses a threat to the efficacy of those decisions: the intentional distortion or manipulation of the underlying algorithm so that machines make decisions that benefit self-interested third parties, rather than decisions that enhance public well-being. That threat has not been recognized or addressed by legal thinkers or policy makers. This article first examines the lifecycle of an algorithm, and then demonstrates the likelihood that self-interested third parties will attempt to corrupt the development and operation of algorithms. The article then argues that existing mechanisms cannot protect the integrity of algorithms. The article concludes with a discussion of policies that could protect the integrity of algorithms: transparency in both the development of and the content of algorithms that affect general well-being and holding persons who corrupt the integrity of such algorithms accountable. Just as the Industrial Revolution eventually improved the quality of life for many, so too does the Big Data Revolution offer enhancement of general well-being. That promise, however, will only be realized if policy makers take action to protect the integrity of underlying algorithms now, at the beginning of the revolution.

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
1.10
自引率
16.70%
发文量
17
期刊介绍: The ABLJ is a faculty-edited, double blind peer reviewed journal, continuously published since 1963. Our mission is to publish only top quality law review articles that make a scholarly contribution to all areas of law that impact business theory and practice. We search for those articles that articulate a novel research question and make a meaningful contribution directly relevant to scholars and practitioners of business law. The blind peer review process means legal scholars well-versed in the relevant specialty area have determined selected articles are original, thorough, important, and timely. Faculty editors assure the authors’ contribution to scholarship is evident. We aim to elevate legal scholarship and inform responsible business decisions.
×
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
确定
请完成安全验证×
copy
已复制链接
快去分享给好友吧!
我知道了
右上角分享
点击右上角分享
0
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 布克学术 All rights reserved.
京ICP备2023020795号-1
ghs 京公网安备 11010802042870号
Book学术文献互助
Book学术文献互助群
群 号:481959085
Book学术官方微信