As Generative Artificial Intelligence (GenAI) technologies continue to advance rapidly, the issue of governance and regulation has emerged as a critical challenge. The development and implementation of governance approaches for GenAI have not kept pace with the technology itself, leading to discrepancies and a lack of consistent provisions across different regions globally.
In order to address this challenge, the authors of this paper have proposed a Harmonized GenAI Framework, or “H-GenAIGF,” which aims to provide a collective view of different governance approaches from six key regions: the European Union (EU), United States (US), China (CN), Canada (CA), United Kingdom (UK), and Singapore (SG). By analyzing the governance approaches of these regions, the authors have identified four key constituents, fifteen processes, twenty-five sub-processes, and nine principles that contribute to the effective governance of GenAI.
Furthermore, the paper includes a comparative analysis of these governance approaches, aiming to identify commonalities and distinctions between regions in terms of process coverage. The results of this analysis reveal that risk-based approaches tend to provide the most comprehensive coverage of processes, followed by mixed approaches. On the other hand, other approaches fall short, covering less than half of the processes identified.
An important finding from this research is that only one process aligns across all governance approaches from the different regions. This highlights the lack of consistent and executable provisions for GenAI governance. To support this finding, the authors also conducted a case study on ChatGPT, a popular AI model, and found a deficiency in process coverage. This further emphasizes the need for harmonization of governance approaches to ensure alignment and effectiveness in GenAI governance.
In conclusion, this paper provides valuable insights into the current state of GenAI governance globally. The proposed Harmonized GenAI Framework offers a comprehensive perspective by identifying key constituents, processes, sub-processes, and principles. The comparative analysis highlights the discrepancies and convergences between regions, emphasizing the need for consistent and executable provisions. Moving forward, it is crucial for global governance to keep pace with GenAI technologies, addressing the identified limitations and fostering safe and trustworthy adoption of this powerful technology.