Algorithmic Regulation and Personalized Law最新文献

Algorithmic Regulation and (Im)Perfect Enforcement in the Personalized Economy 个性化经济中的算法监管与(Im)完美执行

Algorithmic Regulation and Personalized Law Pub Date : 2019-03-01 DOI: 10.2139/ssrn.3503823

C. Busch

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引用次数: 1

The Death of Rules and Standards 规则和标准的消亡

Algorithmic Regulation and Personalized Law Pub Date : 2015-11-20 DOI: 10.2139/SSRN.2693826

A. Casey, Anthony Niblett

{"title":"The Death of Rules and Standards","authors":"A. Casey, Anthony Niblett","doi":"10.2139/SSRN.2693826","DOIUrl":"https://doi.org/10.2139/SSRN.2693826","url":null,"abstract":"Scholars have examined the lawmakers’ choice between rules and standards for decades. This paper, however, explores the possibility of a new form of law that renders that choice unnecessary. Advances in technology (such as big data and artificial intelligence) will give rise to this new form – the micro-directive – which will provide the benefits of both rules and standards without the costs of either. Lawmakers will be able to use predictive and communication technologies to enact complex legislative goals that are translated by machines into a vast catalog of simple commands for all possible scenarios. When an individual citizen faces a legal choice, the machine will select from the catalog and communicate to that individual the precise context-specific command (the micro-directive) necessary for compliance. In this way, law will be able to adapt to a wide array of situations and direct precise citizen behavior without further legislative or judicial action. A micro-directive, like a rule, provides a clear instruction to a citizen on how to comply with the law. But, like a standard, a micro-directive is tailored to and adapts to each and every context. While predictive technologies such as big data have already introduced a trend toward personalized default rules, in this paper we suggest that this is only a small part of a larger trend toward context-specific laws that can adapt to any situation. As that trend continues, the fundamental cost trade-off between rules and standards will disappear, changing the way society structures and thinks about law.","PeriodicalId":246000,"journal":{"name":"Algorithmic Regulation and Personalized Law","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2015-11-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130684163","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 45

Personalizing Default Rules and Disclosure with Big Data 使用大数据个性化默认规则和披露

Algorithmic Regulation and Personalized Law Pub Date : 2013-02-13 DOI: 10.2139/SSRN.2217064

A. Porat, L. Strahilevitz

{"title":"Personalizing Default Rules and Disclosure with Big Data","authors":"A. Porat, L. Strahilevitz","doi":"10.2139/SSRN.2217064","DOIUrl":"https://doi.org/10.2139/SSRN.2217064","url":null,"abstract":"This paper provides the first comprehensive account of personalized default rules and personalized disclosure in the law. Under a personalized approach to default rules, individuals are assigned default terms in contracts or wills that are tailored to their own personalities, characteristics, and past behaviors. Similarly, disclosures by firms or the state can be tailored so that only information likely to be relevant to an individual is disclosed, and information likely to be irrelevant to her is omitted. The paper explains how the rise of Big Data makes the effective personalization of default rules and disclosure far easier than it would have been during earlier eras. The paper then shows how personalization might improve existing approaches to the law of consumer contracts, medical malpratice, inheritance, landlord-tenant relations, and labor law.The paper makes several contributions to the literature. First, it shows how data mining can be used to identify particular personality traits in individuals, and these traits may in turn predict preferences for particular packages of legal rights. Second, it proposes a regime whereby a subset of the population (“guinea pigs”) is given a lot of information about various contractual terms and plenty of time to evaluate their desirability, with the choices of particular guinea pigs becoming the default choices for those members of the general public who have similar personalities, demographic characterics, and patterns of observed behavior. Third, we assess a lengthy list of drawbacks to the personalization of default rules and disclosure, including cross-susidization, strategic behavior, uncertainty, stereotyping, privacy, and institutional competence concerns. Finally, we explain that the most trenchant critiques of the disclosure strategy for addressing social ills are really criticisms of impersonal disclosure. Personalized disclosure not only offers the potential to cure the ills associated with impersonal disclosure strategies, but it can also ameliorate many of the problems associated with the use of personalized default rules.","PeriodicalId":246000,"journal":{"name":"Algorithmic Regulation and Personalized Law","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2013-02-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131081920","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 48

Personalized Law and the Behavioral Sciences 个性化法律与行为科学

Algorithmic Regulation and Personalized Law Pub Date : 1900-01-01 DOI: 10.5040/9781509931767.ch-012

引用次数: 0

Personalization of Tort Law? 侵权法的人格化?

Algorithmic Regulation and Personalized Law Pub Date : 1900-01-01 DOI: 10.5040/9781509931767.ch-011

引用次数: 0

Granular Norms and the Concept of Law: A Critique 细粒规范与法律概念:批判

Algorithmic Regulation and Personalized Law Pub Date : 1900-01-01 DOI: 10.5040/9781509931767.ch-005

引用次数: 0

De- or Re-typification through Big Data Analytics? The Case of Consumer Law 通过大数据分析去类型化还是重新类型化?消费者法案例

Algorithmic Regulation and Personalized Law Pub Date : 1900-01-01 DOI: 10.5040/9781509931767.ch-009

引用次数: 0

“Granularization” and Cross-Subsidies: Liberal, Neoliberal and Socialist Perspectives “颗粒化”和交叉补贴:自由主义、新自由主义和社会主义观点

Algorithmic Regulation and Personalized Law Pub Date : 1900-01-01 DOI: 10.5040/9781509931767.ch-007

引用次数: 0

‘Granular Legal Norms’ in the Financial Services Trade 金融服务贸易中的“细粒度法律规范”

Algorithmic Regulation and Personalized Law Pub Date : 1900-01-01 DOI: 10.5040/9781509931767.ch-008

引用次数: 1

“Smart Contract”, “Granular Norms” and Non-Discrimination “智能合约”、“颗粒规范”和非歧视

Algorithmic Regulation and Personalized Law Pub Date : 1900-01-01 DOI: 10.5040/9781509931767.ch-013

引用次数: 0