C. I. Gutierrez, G. Marchant, Alec Carden, Kaylee Hoffner, Alexander Kearl
{"title":"Preliminary Results of a Global Database on Soft Law Mechanisms for the Governance of Artificial Intelligence","authors":"C. I. Gutierrez, G. Marchant, Alec Carden, Kaylee Hoffner, Alexander Kearl","doi":"10.1109/AI4G50087.2020.9311078","DOIUrl":null,"url":null,"abstract":"Soft law mechanisms create substantive expectations that are not directly enforceable by government. All kinds of organizations apply soft law to regulate the development or use of methods and applications of artificial intelligence (AI), yet limited scholarship is devoted to studying the prevalence of these tools. This article describes the methodology and preliminary results of a project that compiled a global database of AI soft law mechanisms. It provides information on the type of organizations that create them, differences in how they are enforced, their origin and jurisdiction, influence, and the themes of their text. As both developers and users of these mechanisms, stakeholders (private sector, governments, and civil society) need information about their option space on how to govern AI. The objective of this work is to make available an analysis and library of information that facilitates the development of effective soft law mechanisms. In addition, it offers readers unique insights into the role of these mechanisms in managing AI's outcomes.","PeriodicalId":286271,"journal":{"name":"2020 IEEE / ITU International Conference on Artificial Intelligence for Good (AI4G)","volume":"38 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2020-09-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"2","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2020 IEEE / ITU International Conference on Artificial Intelligence for Good (AI4G)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/AI4G50087.2020.9311078","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 2
Abstract
Soft law mechanisms create substantive expectations that are not directly enforceable by government. All kinds of organizations apply soft law to regulate the development or use of methods and applications of artificial intelligence (AI), yet limited scholarship is devoted to studying the prevalence of these tools. This article describes the methodology and preliminary results of a project that compiled a global database of AI soft law mechanisms. It provides information on the type of organizations that create them, differences in how they are enforced, their origin and jurisdiction, influence, and the themes of their text. As both developers and users of these mechanisms, stakeholders (private sector, governments, and civil society) need information about their option space on how to govern AI. The objective of this work is to make available an analysis and library of information that facilitates the development of effective soft law mechanisms. In addition, it offers readers unique insights into the role of these mechanisms in managing AI's outcomes.