Artificial intelligence (“AI”) is a label that can cover a huge range of activities related to machines undertaking tasks with or without human intervention, and our understanding of AI technologies is largely shaped by where we encounter them, from facial recognition tools and chatbots to photo editing software and self-driving cars. If you think of AI you might think of tech companies – from existing giants such as Google, Meta, Alibaba, and Baidu, to new players, such as OpenAI, Anthropic and others. Less visible are the world’s governments, which are shaping the landscape of rules in which AI systems will operate.
Since 2016, tech-savvy regions and nations across Europe, Asia-Pacific and North America have been establishing regulations targeting AI technologies. (Australia is lagging behind, still currently investigating the possibility of such rules.) Currently, there are more than 1,600 AI policies and strategies globally. The European Union, China, the United States, and the United Kingdom have emerged as pivotal forces in shaping the development and governance of AI in the global landscape.
Ramping up to regulate AI
Efforts to regulate AI began to accelerate in April 2021, when the EU proposed an initial framework for regulations called the AI Act. These rules aim to set obligations for providers and users, based on various risks associated with different AI technologies. As the EU AI Act was pending, China moved forward with proposing its own AI regulations. In Chinese media, policymakers have discussed a desire to be first movers and offer global leadership in both AI development and governance.
Where the EU has taken a comprehensive approach, China has been regulating specific aspects of AI one after another. These have ranged from algorithmic recommendations, to deep synthesis or “deepfake” technology, and generative AI. China’s full framework for AI governance will be made up of these policies and others yet to come. The iterative process lets regulators build up their bureaucratic know-how and regulatory capacity, and leaves flexibility to implement new legislation in the face of emerging risks.
A “wake-up call”
China’s move to regulate AI may have been a wake-up call to the U.S., as in April, influential lawmaker Chuck Schumer said the U.S. should “not permit China to lead on innovation or write the rules of the road” for AI. Fast forward to October 30 2023, and the White House issued an executive order that focuses on safe, secure. and trustworthy AI. The order attempts to address broader issues of equity and civil rights, while also concentrating on specific applications of technology.
Alongside the dominant actors, countries with growing IT sectors, including Japan, Taiwan, Brazil, Italy, Sri Lanka, and India, have also sought to implement defensive strategies to mitigate potential risks associated with the pervasive integration of AI.
Such growing efforts at AI regulations worldwide reflect a race against foreign influence. At the geopolitical scale, the U.S. competes with China economically and militarily. The EU emphasizes establishing its own digital sovereignty and striving for independence from the US. On a domestic level, these regulations can be seen as favoring large incumbent tech companies over emerging challengers. This is because it is often expensive to comply with legislation, requiring resources smaller companies may lack.
Alphabet, Meta, and Tesla have supported calls for AI regulation. At the same time, the Alphabet-owned Google has joined Amazon in investing billions in OpenAI’s competitor Anthropic, and Tesla boss Elon Musk’s xAI has just launched its first product, a chatbot called Grok.
The EU’s AI Act, China’s AI regulations, and the White House’s executive order show shared interests among the nations involved. Together, they set the stage for last week’s “Bletchley declaration,” in which 28 countries including the U.S., UK, China, Australia, and several EU members pledged cooperation on AI safety. Countries or regions see AI as a contributor to their economic development, national security, and international leadership. Despite the recognized risks, all jurisdictions are trying to support AI development and innovation.
By 2026, worldwide spending on AI-centric systems may pass $300 billion by one estimate. By 2032, according to a Bloomberg report, the generative AI market alone may be worth $1.3 trillion. Numbers like these, and talk of perceived benefits from tech companies, national governments, and consultancy firms, tend to dominate media coverage of AI. Critical voices are often sidelined.
Beyond economic benefits, countries also look to AI systems for defense, cybersecurity, and military applications. At the UK’s AI safety summit, international tensions were apparent. While China agreed with the Bletchley declaration made on the summit’s first day, it was excluded from public events on the second day. One point of disagreement is China’s social credit system, which operates with little transparency. The EU’s AI Act regards social scoring systems of this sort as creating unacceptable risk.
The U.S. perceives China’s investments in AI as a threat to U.S. national and economic security, particularly in terms of cyberattacks and disinformation campaigns. These tensions are likely to hinder global collaboration on binding AI regulations.
The limitations of current rules
Existing AI regulations also have significant limitations. For instance, there is no clear, common set of definitions of different kinds of AI technology in current regulations across jurisdictions. Current legal definitions of AI tend to be very broad, raising concern over how practical they are. This broad scope means regulations cover a wide range of systems which present different risks and may deserve different treatments. Many regulations lack clear definitions for risk, safety, transparency, fairness, and non-discrimination, posing challenges for ensuring precise legal compliance.
We are also seeing local jurisdictions launch their own regulations within the national frameworks. These may address specific concerns and help to balance attempts to regulate and develop AI. California has introduced two bills to regulate AI in employment. Meanwhile, Shanghai has proposed a system for grading, management, and supervision of AI development at the municipal level. However, defining AI technologies narrowly, as China has done, poses a risk that companies will find ways to work around the rules.
Sets of “best practices” for AI governance are emerging from local and national jurisdictions and transnational organizations, with oversight from groups such as the UN’s AI advisory board and the U.S.’s National Institute of Standards and Technology. The existing AI governance frameworks from the UK, the U.S., the EU, and – to a limited extent – China are likely to be seen as guidance. Global collaboration will be underpinned by both ethical consensus and more importantly national and geopolitical interests.
Fan Yang is a Research fellow at Melbourne Law School and the ARC Centre of Excellence for Automated Decision-Making and Society.
Ausma Bernot is a Postdoctoral Research Fellow at the Australian Graduate School of Policing and Security at Charles Sturt University.