Publication Type
Conference Proceeding Article
Version
acceptedVersion
Publication Date
10-2024
Abstract
As Generative Artificial Intelligence (GenAI) technologies evolve at an unprecedented rate, global governance approaches struggle to keep pace with the technology, highlighting a critical issue in the governance adaptation of significant challenges. Depicting the nuances of nascent and diverse governance approaches based on risks, rules, outcomes, principles, or a mix across different regions around the globe is fundamental to discern discrepancies and convergences and to shed light on specific limitations that need to be addressed, thereby facilitating the safe and trustworthy adoption of GenAI. In response to the need and the evolving nature of GenAI, this paper seeks to provide a collective view of different governance approaches around the world. Our research introduces a Harmonized GenAI Framework, "H-GenAIGF," based on the current governance approaches of six regions: European Union (EU), United States (US), China (CN), Canada (CA), United Kingdom (UK), and Singapore (SG). We have identified four constituents, fifteen processes, twenty-five sub-processes, and nine principles that aid the governance of GenAI, thus providing a comprehensive perspective on the current state of GenAI governance. In addition, we present a comparative analysis to facilitate the identification of common ground and distinctions based on the coverage of the processes by each region. The results show that risk-based approaches allow for better coverage of the processes, followed by mixed approaches. Other approaches lag behind, covering less than 50% of the processes. Most prominently, the analysis demonstrates that among the regions, only one process aligns across all approaches, highlighting the lack of consistent and executable provisions. Moreover, our case study on ChatGPT reveals process coverage deficiency, showing that harmonization of approaches is necessary to find alignment for GenAI governance.
Keywords
Generative artificial intelligence governance, GenAI governance
Discipline
Artificial Intelligence and Robotics | Information Security
Research Areas
Data Science and Engineering; Intelligent Systems and Optimization
Areas of Excellence
Digital transformation
Publication
Proceedings of the AAAI/ACM Conference on AI, Ethics, and Society 7th AIES 2024 : San Jose, CA, USA, October 21-23
Volume
7
First Page
917
Last Page
931
ISBN
9781577358923
Identifier
10.48550/arXiv.2408.16771
Publisher
AAAI Press
City or Country
USA
Citation
JOSE LUIS LUNA CAMPOVERDE; TAN, Ivan; XIE, Xiaofei; and JIANG, Lingxiao.
Navigating governance paradigms: A cross-regional comparative study of generative AI governance processes & principle. (2024). Proceedings of the AAAI/ACM Conference on AI, Ethics, and Society 7th AIES 2024 : San Jose, CA, USA, October 21-23. 7, 917-931.
Available at: https://ink.library.smu.edu.sg/sis_research/9536
Creative Commons License
This work is licensed under a Creative Commons Attribution-NonCommercial-No Derivative Works 4.0 International License.
Additional URL
https://doi.org/10.48550/arXiv.2408.16771