An overview of AI policies in the UK, Europe and US

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15 Mar 2024

Artificial intelligence (AI) has emerged as a pivotal technology, reshaping various aspects of life and work across the globe. Its rapid growth and potential for transformative impact have necessitated the development of comprehensive AI strategies and policies, particularly in leading tech nations like the United Kingdom, Europe and the United States.

National AI strategies and initiatives in the U.K., Europe and U.S.

U.K. AI strategy

The U.K.’s National AI Strategy is aimed at harnessing AI to enhance resilience, productivity, growth and innovation. The U.K. is focused on becoming a global AI superpower, with the government supporting this goal through initiatives like the near-1-billion-British-pound AI Sector Deal. The strategy’s approach is comprehensive, including the development of skills in the AI sector and fostering a pro-innovation regulatory environment.
In 2023, the U.K. government introduced a new approach to AI regulation, emphasizing principles such as safety, transparency and fairness. This principle-based framework is designed to be adaptable and future-proof, avoiding heavy-handed legislation that could stifle innovation. Instead of a single centralized AI regulator, existing regulators like the Health and Safety Executive and the Information Commissioner’s Office will apply these principles within their domains.

EU Artificial Intelligence Act

In Europe, the European Union proposed the Artificial Intelligence Act, which represents a comprehensive legal framework for AI, focusing on ethical and safe AI development and usage. The Act categorizes AI systems based on risk and emphasizes the protection of citizens’ safety and fundamental rights. It aims to provide clear legal guidelines for businesses and foster innovation while ensuring compliance with ethical standards. This act is significant in creating a standardized approach to AI regulation within the European Union.

U.S. National AI Initiative

In the U.S., the National AI Initiative continues to emphasize promoting AI research and development and enhancing collaboration among federal agencies, the private sector, academia and international allies.
The initiative focuses on preparing the workforce for an AI-driven economy and leading in the development of AI technical standards globally. It also stresses developing reliable, robust and trustworthy AI systems, underscoring the importance of AI in the nation’s strategic interests.

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Ethics, privacy and AI regulation in the U.K., Europe and the U.S.

Ethics, privacy and AI regulation in the U.K.

In the U.K., AI ethics are shaped by the Data Ethics Framework and The Alan Turing Institute’s guidelines, emphasizing ethical permissibility, fairness, public trust, “SUM Values” (safe, unbiased and manageable), and “FAST Track Principles” (fair, accountable, sustainable and transparent). Data privacy is governed by principles similar to those in the General Data Protection Regulation (GDPR) and the 2022 Data Protection and Digital Information Bill, reducing compliance burdens on businesses.
The U.K.’s AI regulation is pro-innovation, less centralized and guided by six core principles across various sectors, aligning with the National AI Strategy and AI Action Plan to balance innovation and public trust.

Ethics, privacy and AI regulation in the EU

The EU AI Act ensures AI systems within the EU are safe, transparent, traceable, non-discriminatory and environmentally friendly, with an emphasis on human oversight. It strives for a uniform AI definition and integrates closely with the EU’s data protection ethos, akin to GDPR.
The act classifies AI systems by risk levels, ranging from high risk (like those used in critical sectors or impacting fundamental rights) to unacceptable risk, where harmful AI applications, such as social scoring, are banned. High-risk systems are subject to stringent assessments and fundamental rights impact assessments.

Ethics, privacy and AI regulation in the U.S.

In the U.S., AI regulation focuses on safety and security, with an executive order from President Joe Biden in 2022 mandating safety test disclosures for AI systems that could impact national security or public welfare. Legislative efforts to integrate AI into various sectors have led to amendments in laws like the Federal Aviation Administration (FAA) Reauthorization Act and the Advancing American AI Act.
The American Data Privacy and Protection Act addresses AI system definitions and requirements. The regulatory framework is evolving, with agencies like the National Institute of Standards and Technology (NIST) setting AI standards and the Federal Trade Commission (FTC) overseeing generative AI’s impact in sectors like finance and health.

AI research, development and global competitiveness of the U.K., Europe and U.S.

AI research and development is progressing rapidly, marked by breakthroughs in machine learning, data analytics and computational power, with deep learning and natural language processing as key trends. The U.K.’s AI strategy emphasizes foundational models and innovative sandbox trials, while the U.S. National AI Research Institutes program champions cross-sector research collaboration.
Globally, AI competitiveness is gauged by research output, investment, talent acquisition and infrastructure, with the U.S. and key European countries, such as the U.K. and Germany, leading, supported by robust tech ecosystems and governmental backing.
Funding for AI innovation is crucial, with the U.S. increasing federal funding and venture capital investment and Europe and the U.K. offering substantial support through programs like Horizon 2020, Horizon Europe and the AI Sector Deal, fueling a diverse range of AI applications and business development.

AI applications and cross-border collaborations

AI in public sector policy

AI’s integration into the public sector has significantly transformed service delivery, operational efficiency and the ability to address complex societal challenges. In healthcare, AI is used for disease diagnosis and treatment planning, as exemplified by initiatives like the U.K.’s NHS using AI for early cancer detection and patient care management.
In transportation, AI aids in traffic management and the regulation of autonomous vehicles, as seen in the U.S. with projects like the Department of Transportation’s research into AI for improving transportation systems.

Cross-border AI collaboration

Cross-border AI collaboration is key to leveraging diverse expertise and resources, driving innovation and addressing global challenges. An example is the collaboration between the EU and Japan on projects like AI4EU, aimed at creating a joint AI research platform.
AI4EU is an EU-funded project aimed at creating a collaborative, AI-focused ecosystem, providing resources, tools and support to facilitate and accelerate AI research and innovation across Europe.

Public-private AI partnerships

Public-private AI partnerships combine government resources and private-sector innovation to accelerate AI development. An example is the U.K.’s AI Sector Deal, which involves collaboration between the government and industry leaders to boost the country’s AI capabilities. Another example is the U.S. National AI Research Institutes program, a partnership between the National Science Foundation, government, academia and industry focusing on AI research in various domains.

AI standards and workforce development

AI standards and certification

Ensuring AI systems’ safety, reliability and interoperability is crucial, and AI standards and certifications address this need. Developed by international bodies, industry groups and regulatory agencies, these standards cover ethical considerations, data handling, algorithm transparency and security. For example, the IEEE P7000 series offers principles for ethically aligned design in AI.

AI workforce development

A skilled AI workforce is essential for leveraging AI’s full potential. Universities globally offer specialized programs in AI, machine learning and data science. Online platforms like Coursera and edX have also democratized AI education, providing accessible courses in partnership with leading institutions.
Moreover, companies like Google and Microsoft run AI training programs for their employees, and there are increasing efforts to diversify the AI workforce, promoting inclusivity in AI development.

Legal and security aspects of AI

AI and intellectual property (IP)

The intersection of AI and intellectual property law is a complex and evolving area. One key issue is the determination of IP rights for AI-generated content and inventions. Traditional IP laws are being challenged to accommodate the nuances of AI, leading to debates about whether AI systems themselves can be recognized as inventors or creators.
This debate extends to various jurisdictions, with patent offices like the European Patent Office (EPO) and the United States Patent and Trademark Office (USPTO) revising guidelines to address AI’s role in inventions. Crucial topics in these debates include:

AI as an inventor: Are AI systems entitled to the same recognition as human inventors? This calls into question conventional ideas of creativity and invention, which have long been associated with human intellectual endeavors.
Ownership of AI-created inventions: Who is entitled to the intellectual property created by an AI system? The status of the AI and whether the creator or operator of the AI should own the intellectual property are other concerns raised by this question.
Patent eligibility and requirements: According to current patent regulations, inventors must be human beings. As a result, standard patent requirements, like those about inventorship and the creative process, might not apply to ideas produced by AI systems.

AI in national security

AI’s role in national security raises significant ethical and legal concerns. Its applications in surveillance, autonomous weapons, cybersecurity and intelligence analysis enhance defense capabilities but also pose challenges related to autonomy, privacy and ethical use. The deployment of AI in surveillance has sparked privacy and civil liberties debates, particularly regarding the balance between security and individual rights.