Regulating generative AI: the limits of technology-neutral regulatory frameworks. Insights from Italy's intervention on ChatGPT

Cordella, Antonio ORCID: 0000-0002-4468-7807 and Gualdi, Francesco (2024) Regulating generative AI: the limits of technology-neutral regulatory frameworks. Insights from Italy's intervention on ChatGPT. Government Information Quarterly, 41 (4). ISSN 0740-624X

Text (1-s2.0-S0740624X24000741-main) - Published Version Available under License Creative Commons Attribution. Download (1MB)

• Scopus publication
• https://linkinghub.elsevier.com/retrieve...

Abstract

Existing literature has predominantly concentrated on the legal, ethical, governance, political, and socioeconomic aspects of AI regulation, often relegating the technological dimension to the periphery, reflecting the design, use, and development of AI regulatory frameworks that are technology-neutral. The emergence and widespread use of generative AI models present new challenges for public regulators aiming at implementing effective regulatory interventions. Generative AI operates on distinctive technological properties that require a comprehensive understanding prior to the deployment of pertinent regulation. This paper focuses on the recent case of the suspension of ChatGPT in Italy to explore the impact the specific technological fabric of generative AI has on the effectiveness of technology-neutral regulation. By drawing on the findings of an exploratory case study, this paper contributes to the understanding of the tensions between the specific technological features of generative AI and the effectiveness of a technology-neutral regulatory framework. The paper offers relevant implications to practice arguing that until this tension is effectively addressed, public regulatory interventions are likely to underachieve their intended objectives.

Item Type:	Article
Additional Information:	© 2024 The Author(s)
Divisions:	Management
Subjects:	T Technology Q Science > QA Mathematics > QA75 Electronic computers. Computer science J Political Science
Date Deposited:	26 Nov 2024 10:21
Last Modified:	02 Dec 2024 17:03
URI:	http://eprints.lse.ac.uk/id/eprint/126172

Actions (login required)

View Item