The United States, European Union, and the United Kingdom are adopting notably distinct approaches to tackling these challenges. While the EU advances with its EU AI Act and the US pursues a more market-driven strategy supported by executive orders, the UK’s regulatory framework remains comparatively unclear.
The status of AI regulation in the US, EU and UK
The EU has taken a seemingly proactive stance on AI regulation, with an act that aims to classify AI applications into four risk categories: unacceptable, high, limited, and minimal risk. This risk-based framework draws parallels to the EU’s General Data Protection Regulation (GDPR), but appears to regard AI as a mere data management problem. The EU AI Act, with its primary focus on governance and classification, falls short in addressing the full complexity of AI and fails to account for the rapid pace of its transformative potential. With stringent rules, especially for high-risk AI applications in areas such as law enforcement, recruitment and healthcare, the Act could stifle innovation by imposing high compliance costs.
The United States, in contrast, has taken a more sector-specific and less prescriptive approach to AI regulation. Key developments include President Biden’s 2023 AI Executive Order, which prioritises safety, fairness, and transparency in high-risk AI systems, alongside the Safe and Secure Innovation for Frontier Artificial Intelligence Models Act. The former notably outshined the Bletchley Park Declaration, which was little more than a weak attempt to create the illusion that the UK is taking meaningful action and has any clear understanding of AI regulation. The US initiatives aim to ensure AI safety while maintaining a climate that fosters innovation. Perhaps unsurprisingly, sector-specific regulations are emerging in areas like healthcare and financial services, but on the whole the US still lacks a comprehensive, unified regulatory framework for AI.
In the UK the situation is less clear. While the government has published its National AI Strategy, outlining a vision for AI leadership over the next decade, a comprehensive regulatory framework remains elusive. This regulatory uncertainty, compounded by the government’s recent decision to cut £1.3 billion in tech and AI funding, is creating significant challenges for businesses. Without clear guidance, British firms risk falling behind their EU and US counterparts, who benefit from more structured frameworks. Moreover, the withdrawal of funding poses a serious risk of intensifying an already concerning brain drain, as leading talent in the field may be compelled to pursue opportunities in regions with more robust investment and clearer regulatory frameworks. Without sufficient financial backing and a stable regulatory environment, countries stand to lose their most innovative minds to nations that offer stronger support for AI development, further widening the gap in global technological competitiveness. This shift could have long-term consequences, weakening the capacity for domestic innovation and stifling the growth of emerging AI ecosystems.
AI regulation elsewhere
Beyond the US, EU and UK, other countries similarly attempt to navigate the complex realm of AI regulation. Asia presents a complex regulatory landscape, with countries like China, Japan, and South Korea leading AI development while also adopting divergent approaches. China has implemented strict regulations that align with state control and security, including rules governing AI algorithms and the use of deep synthesis technologies like deepfakes. In contrast, Japan’s AI Strategy focuses on ethical AI development, aligning AI progress with human values and societal welfare. South Korea’s National AI Strategy combines innovation with ethical guidelines, highlighting sectors like healthcare and smart cities.
Canada is similarly proactive, with the introduction of the Artificial Intelligence and Data Act (AIDA) as part of its Digital Charter Implementation Act. AIDA focuses on transparency, accountability, and risk assessment, especially for high-impact AI systems. It is this framework that positions Canada as the current leader in ethical AI, balancing innovation with safeguards for privacy and fairness.
Meanwhile, Australia and several African nations are taking a lighter approach to regulations. Australia’s voluntary AI Ethics Framework guides responsible AI use without imposing strict regulations, while countries like Rwanda and Kenya are developing policies aimed at boosting AI innovation while addressing challenges like data privacy and algorithmic bias.
One hope for ethical and legal guidelines is the soon to be introduced international standard, developed by the International Organisations for Standardisation (ISO) and the International Electrotechnical Commission (IEC). As yet there are no regulatory bodies able to certify the ISO/IEC 42001 which will cover a range of standards related to AI, including:
- ISO/IEC 22989 (AI Concepts and Terminology): Providing a unified framework and definitions for AI-related terms.
- ISO/IEC 23053 (Framework for AI System Lifecycle Processes): Describing guidelines for managing the lifecycle of AI systems, from development to deployment and maintenance.
These could set the standard to ensure that AI systems are safe, transparent and reliable, helping to ensure trust and accountability in all AI technologies.
Applying neuroscience to AI regulation
As countries and businesses grapple with how to regulate AI, perhaps the key to a more effective regulatory framework lies in drawing parallels between AI and the human brain.
In the human brain, the prefrontal cortex plays a critical role in balancing signals from different regions, ensuring responsible decision-making and inhibiting inappropriate responses. AI systems could benefit from similar multi-layered control mechanisms. Rather than relying solely on risk classification, AI regulations should focus on embedding dynamic oversight within the AI systems themselves, akin to the brain’s regulatory functions.
AI models should come equipped with built-in mechanisms to monitor and address bias, fairness, and safety, enabling them to adapt continuously as new data and societal norms evolve. This approach, often referred to as “self-regulation,” would allow AI systems to not just adhere to ethical standards but also to adjust dynamically to shifting contexts. Think of it like the brain adjusting behaviour in response to new information: the AI would learn, recalibrate, and refine its actions to ensure that it remains aligned with principles of fairness and integrity over time.
Applying neuroscience insights into AI regulatory frameworks would not only ensure that systems are trustworthy and safe but also create room for innovation by avoiding overly prescriptive rules.
Opportunities for AI talent or brain drain
As the global race for AI leadership heats up, certain countries are increasingly emerging as attractive destinations for AI talent as a result of their forward-thinking approaches in regulation, investment, and innovation. France, in particular, has positioned itself as a rising star in the AI field. The French government has made substantial investments in AI development, aiming to foster homegrown talent and attract international expertise. For example, in 2018 French President Emmanuel Macron announced a €1.5 billion investment over five years, with the aim to boost AI research and development across public and private sectors, focusing on healthcare, transportation, environment, and defence. This was then followed in 2021 with a commitment to invest a further €1.5 billion to increase research funding, building AI infrastructure and encourage public-private collaborations. With its focus on research and innovation, alongside clear regulatory frameworks, cutting-edge AI startups like Mistral are rapidly gaining prominence. These advances are helping to quickly establish the country as a key player in Europe’s AI ecosystem, with substantial support for entrepreneurs and developers alike.
Similarly, countries like Germany, the Netherlands and Sweden are also stepping up, offering robust funding programmes and creating supportive environments for AI research and development. Germany’s AI strategy emphasises both innovation and ethics, particularly in industries like automotive and manufacturing, while the Netherlands’ AI sector is focused on collaboration between academia and industry. Sweden’s investments in AI, particularly through its Digitaliseringsstrategi, ensure that the country remains competitive in sectors like healthcare and green technologies, with AI playing a central role.
Germany has made a series of significant investments since 2018 ranging from its National AI Strategy with an initial investment of €3 billion through 2025, an AI Innovation Competition, allocating €100 million to support innovative AI solutions in small and medium-sized enterprises (SMEs), followed in 2020 with its GAIA-X project, a pan-European cloud infrastructure aimed at enhancing data sovereignty and fostering AI innovation.
In the Netherlands, the government launched the Strategic Action Plan for Artificial Intelligence in 2019 with the aim of strengthening the Netherlands’ AI capabilities. The plan includes an investment of €64 million in AI development, with a focus on enhancing AI in healthcare, energy, and agriculture. It encourages collaboration between government, industry, and academia to foster innovation. It then went further by creating the Netherlands AI Coalition (NL AIC), a public-private partnership that includes more than 400 organisations, committing €23.5 million in funding during its initial stages.
In a similar time frame the government in Sweden co-invested alongside industry an estimated €100 million, focusing on R&D in areas like healthcare, smart cities, and autonomous systems, with a strong emphasis on collaboration. Furthermore, Sweden’s largest individual AI research investment, the Wallenberg AI, Autonomous Systems and Software Programme (WASP), is backed by the Wallenberg Foundation and the Swedish government, with a total investment of €660 million over the coming years
Unsurprisingly, the United States remains a dominant player in the global AI landscape, largely driven by its vibrant tech sector and venture capital ecosystems. Major tech companies like Google, Microsoft and OpenAI continue to attract top talent from around the world, offering cutting-edge research opportunities and substantial resources for AI development. Google introduced its Google AI Impact Challenge, offering $25 million in grants to organisations that use AI to address social and environmental challenges and Microsoft introduced its AI for Good programme, providing $165 million to support efforts around sustainability, accessibility and humanitarian aid. Similar initiatives by Meta, IBM, Apple and Amazon, to name a few, are all promising millions of dollars of funding to support AI related programmes. There is no doubt that the US’ sector-specific regulations and funding mechanisms for AI research, especially in healthcare and defence, will continue to create an environment where AI talent can thrive.
Neuroscience - A path forward for AI regulation
As AI continues to adapt and evolve, the need for comprehensive regulation that balances innovation and safety becomes increasingly urgent. Countries like the EU, US and UK are at different stages of this journey, with varying degrees of success. The EU’s AI Act, while ambitious, may stifle innovation by imposing overly rigid rules, while the US’ sector-specific approach leaves gaps in high-risk areas. The UK, meanwhile, faces the challenge of creating a coherent framework while grappling with funding cuts and the risk of a brain drain.
In the interests of businesses both small and multi-national there will come a time where the different AI regulatory frameworks need to adapt and interact to help drive commerce and business advantage. By drawing on insights from neuroscience, future AI regulatory frameworks should incorporate adaptive, multi-layered oversight mechanisms that will help AI systems remain trustworthy and safe without stifling innovation, offering a path forward that balances the needs of businesses, governments and society.
While navigating this path is undoubtedly difficult, the promise of a well-regulated AI future, one that fosters both innovation and safety, is within reach.
Steve Elcock
Steve Elcock is a visionary entrepreneur and the founder and CEO of elementsuite, with over 25 years in HR technology. Combining neuroscience and technology, his vision to universalize HR processes is realized in elementsuite’s adaptable all-in-one solution, designed to evolve with the latest advancements.
