Global Governance Imperative For The Oversight of Generative AI: Lessons From US, EU, China, And India
The ascent of Generative Artificial Intelligence (Generative AI) has raised concerns globally, prompting leaders and lawmakers to grapple with the need for effective regulation. With key players like the United States, European Union (EU), China, and India navigating this complex terrain, the call for global governance is resonating louder than ever. This article delves into the challenges faced by different nations in regulating Generative AI and underscores the imperative for unified global regulations.
Current Regulatory Landscape:
Leading figures in the AI domain, including Geoffrey Hinton and Sam Altman, acknowledge the potent capabilities of Generative AI and the necessity for careful oversight. The recent US executive order, signed by President Joe Biden, emphasises the establishment of new standards for AI safety, security, and the protection of privacy.
The EU has been actively working on comprehensive regulations for AI but faces challenges in deciding on foundational model regulations. China has already enacted specific laws addressing Generative AI, seeking a balance between control and private sector freedom. India, traditionally slower in digital lawmaking, recently passed the Digital Personal Data Privacy (DPDP) Act but lacks a comprehensive framework for regulating AI.
Challenges and Faith in Responsible AI:
Lawmakers globally place trust in the concept of “Responsible and Ethical AI,” expecting major tech companies to self-regulate and prevent the development of harmful AI models. However, this approach ignores the rapid growth of open-source movements in Generative AI, providing free tools for developers to build their models.
Crucial Aspects Overlooked:
Lawmakers face challenges in understanding the intricacies of regulating Generative AI, often relying on outdated privacy and copyright laws. They attempt to create regulations that apply within their borders for a technology that operates globally. UK Prime Minister Rishi Sunak recognises the need for a global approach and is working towards building a consensus through international alliances.
Data Collection at the Core:
The foundational models of Generative AI heavily rely on data collected through web scrapers or crawlers. The lack of specific laws regulating data scraping poses a significant challenge. Existing laws, designed for different eras and technologies, fall short in addressing the extensive personal data available on social media platforms.
Call for Global Harmony in Regulation:
To effectively regulate Generative AI, experts assert the necessity of starting with the basics, particularly focusing on data collection. Harmonised regulations across countries are deemed essential to govern all aspects of Generative AI, including data crawlers and scrapers. The responsibility for regulation lies with governments, not solely with corporations following “responsible and ethical AI” practices.
The rapid evolution of Generative AI demands a concerted global effort in regulation. Lessons from the US, EU, China, and India underscore the urgency for cohesive, harmonised regulations that address the core challenges of data collection and model training. As the UK hosted the International AI Safety Summit this year, the need for a unified approach to oversee Generative AI becomes increasingly evident on the global stage.
