Dasharathraj K. Shetty , R. Vijaya Arjunan , D. Cenitta , Krishnamoorthi Makkithaya , Nikhil Venkatraman Hegde , Shreepathy Ranga Bhatta B , Staissy Salu , T.R. Aishwarya , Pranav Bhat , Phani Kumar Pullela
{"title":"Analyzing AI regulation through literature and current trends","authors":"Dasharathraj K. Shetty , R. Vijaya Arjunan , D. Cenitta , Krishnamoorthi Makkithaya , Nikhil Venkatraman Hegde , Shreepathy Ranga Bhatta B , Staissy Salu , T.R. Aishwarya , Pranav Bhat , Phani Kumar Pullela","doi":"10.1016/j.joitmc.2025.100508","DOIUrl":null,"url":null,"abstract":"<div><div>Artificial intelligence (AI) technology has been rapidly evolving, necessitating that discussions on the need and design of regulatory frameworks be taken seriously. This paper reviews literature regarding AI regulations on a theoretical versus a practical level. It examines the different models of regulation – some of which are risk-based regulation and others are complete prohibition – to gauge the literature’s predictions on the scope, precise features, and direction of AI regulation. With particular reference to the EU AI Act as the primary case study, the paper analyzes the consequences of rules on innovation and the international standards’ impact on AI regulatory measures. The results show that almost all scholarly assumptions are accurate, showing how the issues are integrated at the practical level and where is it still challenging to comply and enforce. This paper advocates for continuous improvement in AI regulatory frameworks and more international interactions to ensure efficient governance for AI technologies. It contributes to ongoing debates about creating future-proof adaptable robust AI regulations which can negotiate the complexity between technological development and social protection.</div></div>","PeriodicalId":16678,"journal":{"name":"Journal of Open Innovation: Technology, Market, and Complexity","volume":"11 1","pages":"Article 100508"},"PeriodicalIF":0.0000,"publicationDate":"2025-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Journal of Open Innovation: Technology, Market, and Complexity","FirstCategoryId":"1085","ListUrlMain":"https://www.sciencedirect.com/science/article/pii/S2199853125000435","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"Economics, Econometrics and Finance","Score":null,"Total":0}
引用次数: 0
Abstract
Artificial intelligence (AI) technology has been rapidly evolving, necessitating that discussions on the need and design of regulatory frameworks be taken seriously. This paper reviews literature regarding AI regulations on a theoretical versus a practical level. It examines the different models of regulation – some of which are risk-based regulation and others are complete prohibition – to gauge the literature’s predictions on the scope, precise features, and direction of AI regulation. With particular reference to the EU AI Act as the primary case study, the paper analyzes the consequences of rules on innovation and the international standards’ impact on AI regulatory measures. The results show that almost all scholarly assumptions are accurate, showing how the issues are integrated at the practical level and where is it still challenging to comply and enforce. This paper advocates for continuous improvement in AI regulatory frameworks and more international interactions to ensure efficient governance for AI technologies. It contributes to ongoing debates about creating future-proof adaptable robust AI regulations which can negotiate the complexity between technological development and social protection.