{"title":"Towards experimental standardization for AI governance in the EU","authors":"Kostina Prifti , Eduard Fosch-Villaronga","doi":"10.1016/j.clsr.2024.105959","DOIUrl":null,"url":null,"abstract":"<div><p>The EU has adopted a hybrid governance approach to address the challenges posed by Artificial Intelligence (AI), emphasizing the role of harmonized European standards (HES). Despite advantages in expertise and flexibility, HES processes face legitimacy problems and struggle with epistemic gaps in the context of AI. This article addresses the problems that characterize HES processes by outlining the conceptual need, theoretical basis, and practical application of <em>experimental standardization</em>, which is defined as an <em>ex-ante</em> evaluation method that can be used to test standards for their effects and effectiveness. Experimental standardization is based on theoretical and practical developments in experimental governance, legislation, and innovation. Aligned with ideas and frameworks like Science for Policy and evidence-based policymaking, it enables co-creation between science and policymaking. We apply the proposed concept in the context of HES processes, where we submit that experimental standardization contributes to increasing throughput and output legitimacy, addressing epistemic gaps, and generating new regulatory knowledge.</p></div>","PeriodicalId":51516,"journal":{"name":"Computer Law & Security Review","volume":null,"pages":null},"PeriodicalIF":3.3000,"publicationDate":"2024-03-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.sciencedirect.com/science/article/pii/S0267364924000268/pdfft?md5=cb322c13cb72a1a4bc7b89c543300ffb&pid=1-s2.0-S0267364924000268-main.pdf","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Computer Law & Security Review","FirstCategoryId":"90","ListUrlMain":"https://www.sciencedirect.com/science/article/pii/S0267364924000268","RegionNum":3,"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: 0
Abstract
The EU has adopted a hybrid governance approach to address the challenges posed by Artificial Intelligence (AI), emphasizing the role of harmonized European standards (HES). Despite advantages in expertise and flexibility, HES processes face legitimacy problems and struggle with epistemic gaps in the context of AI. This article addresses the problems that characterize HES processes by outlining the conceptual need, theoretical basis, and practical application of experimental standardization, which is defined as an ex-ante evaluation method that can be used to test standards for their effects and effectiveness. Experimental standardization is based on theoretical and practical developments in experimental governance, legislation, and innovation. Aligned with ideas and frameworks like Science for Policy and evidence-based policymaking, it enables co-creation between science and policymaking. We apply the proposed concept in the context of HES processes, where we submit that experimental standardization contributes to increasing throughput and output legitimacy, addressing epistemic gaps, and generating new regulatory knowledge.
期刊介绍:
CLSR publishes refereed academic and practitioner papers on topics such as Web 2.0, IT security, Identity management, ID cards, RFID, interference with privacy, Internet law, telecoms regulation, online broadcasting, intellectual property, software law, e-commerce, outsourcing, data protection, EU policy, freedom of information, computer security and many other topics. In addition it provides a regular update on European Union developments, national news from more than 20 jurisdictions in both Europe and the Pacific Rim. It is looking for papers within the subject area that display good quality legal analysis and new lines of legal thought or policy development that go beyond mere description of the subject area, however accurate that may be.