Theorizing the regulation of generative AI: lessons learned from Italy's ban on ChatGPT

被引:0
作者
Gualdi, Francesco [1 ]
Cordella, Antonio [1 ]
机构
[1] London Sch Econ & Polit Sci, London, England
来源
PROCEEDINGS OF THE 57TH ANNUAL HAWAII INTERNATIONAL CONFERENCE ON SYSTEM SCIENCES | 2024年
关键词
generative AI; ChatGPT; regulation; law; ethics; data policy; ARTIFICIAL-INTELLIGENCE;
D O I
暂无
中图分类号
TP [自动化技术、计算机技术];
学科分类号
0812 ;
摘要
Existing literature has predominantly concentrated on the legal and ethical aspects of government initiatives to regulate AI, often relegating the technological dimension to the periphery. However, the emergence and widespread use of generative AI models present new challenges for public regulators. Generative AI operates on distinctive technological properties which require a comprehensive understanding by regulators prior to the enactment of pertinent legislation. This paper focuses on the recent case of the Italian ban on ChatGPT to illustrate the public regulators' failure in acknowledging the unique characteristics intrinsic to generative AI, culminating in a flawed regulatory endeavour. By drawing on the findings of an exploratory case study, this paper contributes to the theoretical understanding of AI regulation, highlighting the discordance between the dynamism and fluidity of generative AI and the rigidity of regulatory frameworks. The paper contends that until this tension is effectively addressed, public regulatory interventions are likely to underachieve their intended objectives.
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页码:2023 / 2032
页数:10
相关论文
共 42 条
[1]   Talking AI into Being: The Narratives and Imaginaries of National AI Strategies and Their Performative Politics [J].
Bareis, Jascha ;
Katzenbach, Christian .
SCIENCE TECHNOLOGY & HUMAN VALUES, 2022, 47 (05) :855-881
[2]   Big Data's Disparate Impact [J].
Barocas, Solon ;
Selbst, Andrew D. .
CALIFORNIA LAW REVIEW, 2016, 104 (03) :671-732
[3]  
Baxter P., 2012, QUAL REP, V13, P544
[4]   On the Dangers of Stochastic Parrots: Can Language Models Be Too Big? [J].
Bender, Emily M. ;
Gebru, Timnit ;
McMillan-Major, Angelina ;
Shmitchell, Shmargaret .
PROCEEDINGS OF THE 2021 ACM CONFERENCE ON FAIRNESS, ACCOUNTABILITY, AND TRANSPARENCY, FACCT 2021, 2021, :610-623
[5]  
Black Julia, 2019, European Journal of Law and Technology, V10, P67
[6]   Statistical modeling: The two cultures [J].
Breiman, L .
STATISTICAL SCIENCE, 2001, 16 (03) :199-215
[7]  
Bringas Colmenarejo A., 2022, P 2022 AAAI ACM C ET
[8]   Governing artificial intelligence: ethical, legal and technical opportunities and challenges Introduction [J].
Cath, Corinne .
PHILOSOPHICAL TRANSACTIONS OF THE ROYAL SOCIETY A-MATHEMATICAL PHYSICAL AND ENGINEERING SCIENCES, 2018, 376 (2133)
[9]   Artificial Intelligence and the 'Good Society': the US, EU, and UK approach [J].
Cath, Corinne ;
Wachter, Sandra ;
Mittelstadt, Brent ;
Taddeo, Mariarosaria ;
Floridi, Luciano .
SCIENCE AND ENGINEERING ETHICS, 2018, 24 (02) :505-528
[10]   Artificial Intelligence Regulation: a framework for governance [J].
de Almeida, Patricia Gomes Rego ;
dos Santos, Carlos Denner ;
Farias, Josivania Silva .
ETHICS AND INFORMATION TECHNOLOGY, 2021, 23 (03) :505-525