Artificial intelligence or AI is a label that can cover a huge range of activities related to machines undertaking tasks with or without human intervention.
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 focus on existing tech giants such as Google, Meta, Alibaba, and Baidu, as well as 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 these technologies.
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 figures in shaping the development and governance of AI in the global landscape.
Regulation efforts began to accelerate in 2021 when the EU proposed an initial framework called the AI Act. These rules aim to set obligations for providers and users, based on various risks associated with different technologies.
As the EU AI Act was pending, China moved forward with proposing its own regulations. In Chinese media, policymakers have discussed a desire to be first movers and offer global leadership in both 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 framework will be made up of these policies and others yet to come. This 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.
Beijing’s AI regulation may have been a wake-up call to Washington.
In April, influential lawmaker Chuck Schumer said his country should “not permit China to lead on innovation or write the rules of the road” for AI.
Last month, the White House issued an executive order 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.
Regulations worldwide reflect a race against foreign influence. At the geopolitical scale, the US competes with China economically and militarily. The EU emphasizes establishing its own digital sovereignty and striving for independence from Washington.
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 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 regulations, and the White House executive order show shared interests between the nations involved.
Together, they set the stage for last week’s Bletchley Declaration in which 28 nations including the US, the 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 its development and innovation.
Numbers like these, and talk of perceived benefits from tech companies, national governments, and consultancy firms, tend to dominate media coverage. Critical voices are often sidelined.
Beyond economic benefits, nations also look to AI systems for defense, cybersecurity, and military applications.
At the UK’s AI summit, international tensions were apparent. While China agreed with the Bletchley Declaration made on the first day, it was excluded from public events 24 hours later.
One point of disagreement is Beijing’s social credit system, which operates with little transparency. The EU’s AI Act regards social scoring systems of this sort as creating unacceptable risks.
Washington perceives China’s investments in AI as a threat to US national and economic security, particularly in terms of cyberattacks and disinformation campaigns.
These tensions are likely to hinder global collaboration on binding AI regulations.
Existing rules 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 that present different risks and may deserve different treatments.
Many rules lack clear definitions for risk, safety, transparency, fairness, and non-discrimination, posing challenges to 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 AI regulation and development.
Yet 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 governance are emerging with oversight from groups such as the UN’s AI advisory board and the US’s National Institute of Standards and Technology.
The existing AI governance frameworks from the UK, the US, 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 at The University of Melbourne. Ausma Bernot is a postdoctoral research fellow at the Australian Graduate School of Policing and Security at Charles Sturt University
The views and opinions expressed in this article are those of the author and do not necessarily reflect the official policy of China Factor.