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AI Watch: Global regulatory tracker

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Keeping track of AI regulatory developments around the world.

The global dash to regulate AI

Artificial intelligence (AI) has made enormous strides in recent years and has increasingly moved into the public consciousness.

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Our take on the interconnected global trends that are shaping the business climate for our clients.

Increases in computational power, coupled with advances in machine learning, have fueled the rapid rise of AI. This has brought enormous opportunities, as new AI applications have given rise to new ways of doing business. It has also brought potential risks, from unintended impacts on individuals (e.g., AI errors harming an individual's credit score or public reputation) to the risk of misuse of AI by malicious third parties (e.g., by manipulating AI systems to produce inaccurate or misleading output, or by using AI to create deepfakes).

Governments and regulatory bodies around the world have had to act quickly to try to ensure that their regulatory frameworks do not become obsolete. In addition, international organizations such as the G7, the UN, the Council of Europe and the OECD have responded to this technological shift by issuing their own AI frameworks. But they are all scrambling to stay abreast of technological developments, and already there are signs that emerging efforts to regulate AI will struggle to keep pace. In an effort to introduce some degree of international consensus, the UK government organized the first global AI Safety Summit in November 2023, with the aim of encouraging the safe and responsible development of AI around the world. 

Most jurisdictions have sought to strike a balance between encouraging AI innovation and investment, while at the same time attempting to create rules to protect against possible harms. However, jurisdictions around the world have taken substantially different approaches to achieving these goals, which has in turn increased the risk that businesses face from a fragmented and inconsistent AI regulatory environment. Nevertheless, certain trends are becoming clearer at this stage:

  1. "AI" means different things in different jurisdictions: One of the foundational challenges that any international business faces when designing an AI regulatory compliance strategy is figuring out what constitutes "AI." Unfortunately, the definition of AI varies from one jurisdiction to the next. For example, the EU AI Act adopts a definition of "AI systems" that is based on (but is not identical to) the OECD's definition, and which leaves room for substantial doubt due to its uncertain wording. Canada has proposed a similar, though more concise, definition. Various US states have proposed their own definitions, which differ from one another. And many jurisdictions (e.g., the UK, Israel, China, and Japan) do not currently provide a comprehensive definition of AI. Because several of the proposed AI regulations have extraterritorial effect (meaning more than one AI regulation may apply simultaneously), international businesses may be forced to adopt a "highest common denominator" approach to identifying AI based on the strictest applicable standard.
  2. Emerging AI regulations come in different forms: The various emerging AI regulations have no consistent legal form – some are statutes, some are executive orders, some are expansions of existing regulatory frameworks, and so on. The EU AI Act is a "Regulation" (which means that most of it will apply directly in all EU Member States, without the need for national implementation in most cases). The UK has taken a different approach, declining to legislate at this early stage in the development of AI, and instead choosing to task existing UK regulators with the responsibility of interpreting and applying five AI principles in their respective spheres. In the US, there is a mix of White House Executive Orders, federal and state initiatives, and actions by existing regulatory agencies, such as the Federal Trade Commission. As a result, the types of compliance obligations that international businesses face are likely to be materially different from one jurisdiction to the next. Many other jurisdictions have yet to decide whether they will issue sector-specific or generally applicable rules and have yet to decide between creating new regulators or expanding the roles of existing regulators, making it challenging for businesses to anticipate what form their AI regulatory relationships will take in the long term.
  3. Emerging AI regulations have different conceptual approaches: The next difficulty is the lack of a consistent conceptual approach among emerging AI regulations around the world – some are legally binding while others are not, some are sector-specific while others apply across all sectors, some will be enforced by regulators while others are merely guidelines or recommendations, and so on. As noted above, the UK approach is to use existing regulators to implement five AI principles, but with no new explicit legal obligations. This has the advantage of meaning that businesses will deal with AI regulators with whom they are already familiar but has the disadvantage that different UK regulators may interpret these principles differently in their respective spheres. The EU AI Act is cross-sectoral and creates new regulatory and enforcement powers for existing bodies, including the European Commission, and also creates entirely new bodies such as the AI Board and the AI Office, while leaving EU Member States to appoint their own AI regulators tasked with enforcing the EU AI Act. In the US, the Federal Trade Commission, Equal Employment Opportunity Commission, Consumer Financial Protection Bureau, and Department of Justice issued a joint statement clarifying that their existing authority covers AI, while various state regulators are also likely to have competence to regulate AI. International organizations including the OECD, the UN, and the G7 have issued AI principles, but these impose no legal obligations on businesses. In principle, these initiatives encourage consistency across members of each organization, but in practice this does not seem to have worked.
  4. Flexibility is a double-edged sword: In an effort to create AI regulations that can adapt to technological advances that have not yet been anticipated, many jurisdictions have sought to include substantial flexibility in those regulations, either by using deliberately high-level wording and policies, or by allowing for future interpretation and application by courts and regulators. This has the obvious advantage of prolonging the lifespan of such regulations by allowing them to be adapted to future technologies. However, it also creates the disadvantage of uncertainty because it leaves businesses uncertain of how their compliance obligations will be interpreted in the future. This is likely to mean that it is harder for businesses to know whether their planned implementations of AI will be lawful in the medium-to-long term and may make it harder to attract long-term AI investment in those jurisdictions.
  5. The overlap between AI regulation and other areas of law is complex: A substantial number of laws that are not directly focused on AI nevertheless apply to AI by association within their respective spheres, meaning that any use of AI will often trigger compliance issues and legal challenges even where there is not (yet) any enforceable AI-specific law. These areas of overlap include: IP (e.g., IP infringement issues with respect to AI model training data, and questions about copyright and patentability of AI-assisted inventions); antitrust; data protection (which adds restrictions to processing of personal data, and in some cases imposes special compliance obligations for processing carried out by automated means, including by AI); M&A (where AI innovation is driving dealmaking in many markets); financial regulation (where financial regulatory requirements may limit the ways in which AI can lawfully be deployed); litigation; digital infrastructure; securities; global trade; foreign direct investment; mining & metals; and so on. This overlap will mean that many businesses need to understand not just AI regulations in general, but also any rules that affect the use of AI in the context of the relevant sector or business activity.

Businesses in almost all sectors need to keep a close eye on these developments to ensure that they are aware of the AI regulations and forthcoming trends, in order to identify new opportunities and new potential business risks. But even at this early stage, the inconsistent approaches each jurisdiction has taken to the core questions of how to regulate AI is clear. As a result, it appears that international businesses may face substantially different AI regulatory compliance challenges in different parts of the world. To that end, this AI Tracker is designed to provide businesses with an understanding of the state of play of AI regulations in the core markets in which they operate. It provides analysis of the approach that each jurisdiction has taken to AI regulation and provides helpful commentary on the likely direction of travel.

Because global AI regulations remain in a constant state of flux, this AI Tracker will develop over time, adding updates and new jurisdictions when appropriate. Stay tuned, as we continue to provide insights to help businesses navigate these ever-evolving issues.

Articles

African Union

The African Union's Continental AI Strategy sets the stage for a unified approach to AI governance across the continent.

Africa Union

Australia

Voluntary AI Ethics Principles guide responsible AI development in Australia, with potential reforms under consideration.

Australia

Brazil

The enactment of Brazil's proposed AI Regulation remains uncertain with compliance requirements pending review.

Sao Paulo

Canada

AIDA expected to regulate AI at the federal level in Canada but provincial legislatures have yet to be introduced.

Canada

China

The Interim AI Measures is China's first specific, administrative regulation on the management of generative AI services.

China

Council of Europe

The Council of Europe is developing a new Convention on AI to safeguard human rights, democracy, and the rule of law in the digital space covering governance, accountability and risk assessment.

European Union

Czech Republic

The successful implementation of the EU AI Act into national law is the primary focus for the Czech Republic, with its National AI Strategy being the main policy document.

Czech Republic

European Union

The EU introduces the pioneering EU AI Act, aiming to become a global hub for human-centric, trustworthy AI.

 

European Union

France

France actively participates in international efforts and proposes sector-specific laws.

Paris

G7

The G7's AI regulations mandate Member States' compliance with international human rights law and relevant international frameworks.

G7 flags

Germany

Germany evaluates AI-specific legislation needs and actively engages in international initiatives.

Germany

India

National frameworks inform India’s approach to AI regulation, with sector-specific initiatives in finance and health sectors.

India

Israel

Israel promotes responsible AI innovation through policy and sector-specific guidelines to address core issues and ethical principles.

Israel

Italy

Italy engages in political discussions for future laws.

Milan

Japan

Japan adopts a soft law approach to AI governance but lawmakers advance proposal for a hard law approach for certain harms.

Tokyo

Kenya

Kenya's National AI Strategy and Code of Practice expected to set foundation of AI regulation once finalized.

Kenya
Kenya

Nigeria

Nigeria's draft National AI Policy underway and will pave the way for a comprehensive national AI strategy.

Nigeria
Nigeria

Norway

Position paper informs Norwegian approach to AI, with sector-specific legislative amendments to regulate developments in AI.

Norway

OECD

The OECD's AI recommendations encourage Member States to uphold principles of trustworthy AI.

country flags

Saudi Arabia

Saudi Arabia is yet to enact AI Regulations, relying on guidelines to establish practice standards and general principles.

Riyadh_Hero_1600x600 Saudi Arabia

Singapore

Singapore's AI frameworks guide AI ethical and governance principles, with existing sector-specific regulations addressing AI risks.

Singapore

South Africa

South Africa is yet to announce any AI regulation proposals but is in the process of obtaining inputs for a draft National AI plan.

Johannesburg

South Korea

South Korea's AI Act to act as a consolidated body of law governing AI once approved by the National Assembly.

Korea

Spain

Spain creates Europe's first AI supervisory agency and actively participates in EU AI Act negotiations.

Madrid

Switzerland

Switzerland's National AI Strategy sets out guidelines for the use of AI, and aims to finalize an AI regulatory proposal in 2025.

Switzerland

Taiwan

Draft laws and guidelines are under consideration in Taiwan, with sector-specific initiatives already in place.

Taiwan city

Turkey

Turkey has published multiple guidelines on the use of AI in various sectors, with a bill for AI regulation now in the legislative process.

Türkiye

United Arab Emirates

Mainland UAE has published an array of decrees and guidelines regarding regulation of AI, while the ADGM and DIFC free zones each rely on amendments to existing data protection laws to regulate AI.

UAE

United Kingdom

The UK prioritizes a flexible framework over comprehensive regulation and emphasizes sector-specific laws.

London hero image

United Nations

The UN's new draft resolution on AI encourages Member States to implement national regulatory and governance approaches for a global consensus on safe, secure and trustworthy AI systems.

United Nations

United States

The US relies on existing federal laws and guidelines to regulate AI but aims to introduce AI legislation and a federal regulation authority.

New York city photo

Contacts

Tim Hickman
Partner
London
Erin Hanson
Partner
New York
Dr. Sylvia Lorenz
Partner
Berlin
London hero image

AI Watch: Global regulatory tracker - United Kingdom

The UK prioritizes a flexible framework over comprehensive regulation and emphasizes sector-specific laws.

Insight
|
12 min read

Laws/Regulations directly regulating AI (the “AI Regulations”)

The UK government's AI Regulation White Paper1 of August 3, 2023 (the "White Paper") and its written response of February 6, 2024 to the feedback it received as part of its consultation on the White Paper (the "Response")2 both indicate that the UK does not intend to enact horizontal AI regulation in the near future. Instead, the White Paper and the Response support a "principles-based framework" for existing sector-specific regulators to interpret and apply to the development and use of AI within their domains.3

The UK considers that a non-statutory approach to the application of the framework offers "critical adaptability" that keeps pace with rapid and uncertain advances in AI technology.4 However, the UK may choose to introduce a statutory duty on regulators to have "due regard" to the application of the principles after reviewing the initial period of their non-statutory implementation.5

The UK Government's Office for Artificial Intelligence, which was set up to oversee the implementation of the UK's National AI Strategy, will perform various central functions to support the framework's implementation. Such support functions include (among other things): (i) monitoring and evaluating the overall efficacy of the regulatory framework; (ii) assessing and monitoring risks across the economy arising from AI; and (iii) promoting interoperability with international regulatory frameworks.6

However, on July 17, 2024, the King’s Speech7 proposed a set of binding measures on AI, which deviates from the previous agile and non-binding approach. Specifically, the government plans to establish "appropriate legislation to place requirements on those working to develop the most powerful [AI] models".8 The Digital Information and Smart Data Bill was also announced, which will be accompanied by reforms to data-related laws, to support the safe development and deployment of new technologies (which may include AI).9 It is not yet clear exactly how this will be implemented.

On July 26, 2024, the Department for Science, Innovation and Technology commissioned an "AI Action Plan"10 to leverage AI for economic growth and improved public services. The plan will evaluate the UK's infrastructure needs, attract top AI talent, and promote AI adoption across the public and private sectors. Evidence will be gathered from academics, businesses, and civil society to create a comprehensive strategy for AI sector growth and integration. Recommendations are expected in Q4 2024, and an "AI Opportunities Unit" will be established to implement these recommendations.

Status of the AI Regulations 

In February 2024, the UK government wrote to a number of regulators whose work is impacted by AI, asking them to publish an update outlining their strategic approach to AI.11 The regulators' subsequent responses contained (among other things) plans on regulating AI, actions they have already taken, and expressed their support and adherence to the White Paper’s five principles (see section titled "Key compliance requirements" below for more details). Most notably:

  • The Financial Conduct Authority's (FCA) AI update outlines the FCA’s plans for the next 12 months, including collaboration with other Digital Regulation Cooperation Forum (DRCF) member regulators to deliver the pilot AI and Digital Hub, and running its own Digital Sandbox and Regulatory Sandbox12
  • The Information Commissioner Office’s (ICO) strategic approach establishes specific areas of focus in relation to AI and data protection, which include foundation models, high-risk AI applications (e.g., emotion recognition technology), facial recognition technology, and biometrics13
  • The Office of Communication's (Ofcom) strategic approach to AI 2024/25 sets out Ofcom's plan of work in relation to four policy areas: online safety, broadcasting, telecoms, and cross-cutting issues that affect the other three policy areas. The strategy also highlights three key risks and Ofcom's work to date in addressing them, including, synthetic media, personalization, security and resilience14
  • The Competition and Markets Authority (CMA) AI strategic update reviews foundation models to understand the opportunities and risks for competition and consumer protection15

On September 5, 2024, the Council of Europe’s Framework Convention16 on AI was signed by Andorra, Georgia, Iceland, Norway, the Republic of Moldova, San Marino, the United Kingdom17, Israel, the United States, and the European Union. The treaty will enter into force on the first day of the month following three months after five signatories, including at least three Council of Europe Member States, have ratified it. Countries from all over the world will be eligible to join and commit to its provisions.

Other laws affecting AI

There are several domestic laws that will affect the development or use of AI, including but not limited to:

  • Data protection laws
  • Intellectual property laws
  • Human rights laws (particularly, anti-discrimination laws such as the Equality Act 2010 and the Human Rights Act 1998)
  • Consumer and competition laws
  • The proposed Digital Information and Smart Data Bill

Definition of “AI”

The White Paper describes "AI," "AI systems" and/or "AI technologies" as "products and services that are ‘adaptable' and ‘autonomous'" but stops short of providing an exhaustive definition.18

  • With reference to the adaptivity of AI, the White Paper emphasizes that AI systems often develop the ability to perform new forms of inference not directly envisioned by their human programmers 
  • With reference to the autonomy of AI, the White Paper acknowledges that AI systems can make decisions without the express intent or ongoing control of a human

Territorial scope 

The proposed regulatory framework applies to the whole of the UK and states that the UK will continue to consider the impacts of devolution as the AI regulatory framework further develops.19

The White Paper also notes that, as the UK is not currently proposing the introduction of new statutory requirements, the current principles-based AI framework will not change the territorial application of existing legislation applicable to AI (including, for example, data protection legislation). The Response notes that as the UK's approach develops, the government will continue to assess the territorial reach of its AI regulatory framework.20

Sectoral scope

As noted above, sector-specific regulators will be interpreting and applying the UK's overall principles-based AI framework to the development or use of AI within their respective domains. To date, limited sector-specific guidance has been published. We expect regulators will continue to publish updates outlining their respective strategic approach to AI in the near term.

Compliance roles 

There are two key compliance roles that will be impacted by the UK's AI regulatory framework:

  • First, regulators will need to: (i) have due regard for the framework and its principles when they introduce sector-specific regulation; and (ii) issue sector-specific guidance on how the cross-sectoral principles apply within their remit. Having due regard for the fact that the principles may eventually become a "statutory duty on regulators"21
  • Second, AI actors across the life cycle of AI systems (including the design, research, training, development, deployment, integration, operation, maintenance, sale, use and governance phases) will have to comply with any sector-specific regulation introduced by the relevant regulators

Core issues that the AI Regulations seek to address

The White Paper identifies a range of high-level risks that the principles-based AI framework seeks to mitigate with proportionate interventions.22 These include:

  • Risks to human rights (e.g., Generative AI may be used to create deepfake video content, potentially damaging the reputation, relationships and dignity of the subject) 
  • Risks to safety (e.g., an AI system based on LLM technology may recommend a dangerous activity that it has found on the internet, without understanding or communicating the context of the website where the activity was described, potentially leading to physical harm)
  • Risks to fairness (e.g., an AI tool assessing creditworthiness of loan applicants that is trained on incomplete or inaccurate data may result in the offer of loans to individuals on inappropriate terms)
  • Risks to privacy and agency (e.g., connected devices in a household may continuously gather data —including conversations—and may potentially create a near-complete portrait of an individual's home life. Privacy risks will compound if more parties can access such data)
  • Risks to societal well-being (e.g., disinformation generated and propagated by AI could undermine access to reliable information and trust in democratic institutions and processes)
  • Risks to security (e.g., AI tools may be used to automate, accelerate and magnify the impact of highly targeted cyber-attacks, increasing the severity of the threat from malicious actors)

Risk categorization

The White Paper states that the UK's AI regulatory framework will adopt a context-specific approach instead of categorizing AI systems according to risk. Thus, the UK has decided to not assign rules or risk levels across sectors or technologies.23 The White Paper also notes that it would be neither proportionate nor effective to classify all applications of AI in critical infrastructure as high risk, as some uses of AI in relation to critical infrastructure (e.g., the identification of superficial scratches on machinery) can be relatively low risk.24 Essentially, the UK's context-specific approach to risk categorization is expected to allow regulators to respond to the risks posed by AI systems in a proportionate manner.25

The Response highlights the UK's continued commitment to a context-based approach "that avoids unnecessary blanket rules that apply to all AI technologies, regardless of how they are used", noting that such an approach is the "best way" to ensure an agile approach that stands the test of time.26

Key compliance requirements 

The White Paper establishes five cross-sectoral principles for existing regulators to interpret and apply within their respective domains:

Principle 1: Regulators should ensure that AI systems function in a robust, secure, and safe way throughout the AI life cycle, and that risks are continually identified, assessed and managed. 

To implement this principle, regulators will need to consider: 

  • Providing guidance as to what good cybersecurity and privacy practices look like
  • Referring to a risk management framework that AI life cycle actors should apply 
  • The role of available technical standards to clarify regulatory guidance and support the implementation of risk treatment measures

Principle 2: Regulators should ensure that AI systems are appropriately transparent and explainable. To implement this principle, regulators will need to consider:

  • Setting expectations for AI life cycle actors to provide information relating to: (a) the nature and purpose of the AI system in question; (b) the data being used; (c) the training data used; (d) the logic and process used; and (e) accountability for the AI system and any specific outcomes 
  • Setting "explainability" requirements, particularly for higher-risk systems, to ensure appropriate balance between information needs for regulatory enforcement and technical trade-offs with system robustness 
  • The role of available technical standards to clarify regulatory guidance and support the implementation of risk treatment measures

Principle 3: Regulators should ensure that AI systems are fair (i.e., they do not undermine the legal rights of individuals or organizations, discriminate unfairly against individuals, or create unfair market outcomes).

To implement this principle, regulators will likely need to: 

  • Interpret and articulate what "fair" means with reference to their respective sectors 
  • Decide in which contexts and instances fairness is important and relevant 
  • Design, implement and enforce appropriate governance requirements for "fairness" in their respective sectors 
  • Where a decision involving the use of an AI system has a legal or similarly significant effect on an individual, consider the suitability of requiring AI system operators to provide an appropriate justification for that decision to affected third parties 
  • Ensure that AI systems comply with regulatory requirements relating to the vulnerability of individuals within specific regulatory domains 
  • Consider the role of available technical standards to clarify regulatory guidance and support the implementation of risk treatment measures

Principle 4: Regulators should ensure there are governance measures in place to allow for effective oversight of the supply and use of AI systems, with clear lines of accountability across the AI life cycle. To implement this principle, regulators will likely need to:

  • Determine who is accountable for compliance with existing regulation and the principles, and provide initial guidance on how to demonstrate accountability in relation to AI systems 
  • Provide guidance on governance mechanisms including, potentially, activities in the scope of appropriate risk management and governance processes (including reporting duties) 
  • Consider how available technical standards addressing AI governance, risk management, transparency and other issues can support responsible behavior and maintain accountability within an organization

Principle 5: Regulators should ensure that users, impacted third parties and actors in the AI life cycle are able to contest an AI decision or outcome that is harmful or creates a material risk of harm, and access suitable redress.

To implement this principle, regulators will need to consider:

  • Creating or updating guidance with relevant information on where those affected by AI harms should direct their complaint or raise a dispute 
  • Creating or updating guidance that identifies the "formal" routes of redress offered by regulators in certain scenarios 
  • Emphasizing the requirements of appropriate transparency and "explainability" in interactions for effective redress and contestability

The Response notes that values and rules associated with human rights, operational resilience, data quality, international alignment, systemic risks and wider societal impacts, sustainability and education, and literacy are largely already enshrined in existing UK laws.

Regulators

The UK does not have a central AI regulator, and the White Paper indicates that there are no existing plans to establish a central AI regulator either.27 As noted above, sector-specific regulators are expected to interpret and apply the principles-based AI framework within their respective domains. 

Enforcement powers and penalties 

Sector-specific regulators will need to ensure their regulations incorporate the principles of accountability and suitable redress with reference to the UK's principles-based AI framework.

1 See Convention text here.
2 See Government press release
here
3 See UK government press release (
here).
4 See the White Paper (
here).
5 See the Response (
here).
6 See the White Paper (
here), Section 3.2 (The proposed regulatory framework), and the Response (here), section 5 (A regulatory framework to keep pace with a rapidly advancing technology).
7 See the Response (
here), paragraph 16.
8 See the Response (
here), paragraph 109.
9 See the White Paper (
here), paragraph 14.
10 The King’s Speech sets out the new Labor government’s proposed laws and its plans for the upcoming parliamentary term.
11 See the King’s Speech
here.
12 See the King’s Speech background notes
here, page 40.
13 See all the relevant regulator updates
here.
14 See the FCA update
here.
15 See the ICO strategic approach
here.
16 See Ofcom’s strategic approach to AI 2024/25
here.
17 See the Competition and Markets Authority initial review of AI Foundation Models (
here).
18 See the White Paper (
here), Section 1.3 (A note on terminology) and Section 3.2.1 (Defining Artificial Intelligence).
19 See the White Paper (
here), Part 5 (Territorial application).
20 See the Response (
here), paragraph 78.
21 See the White Paper (
here), paragraph 25.
22 See the Response (
here), paragraph 11.
23 See the White Paper (
here), Section 3.2.2 (Regulating the use – not the technology), paragraph 45.
24 See the White Paper (
here), Section 3.2.2 (Regulating the use – not the technology), paragraph 45.
25 See the White Paper (
here), Section 3.2.2 (Regulating the use – not the technology), paragraph 46.
26 See the Response (
here), paragraph 11.
27 See the White Paper (
here), paragraph 15.

White & Case means the international legal practice comprising White & Case LLP, a New York State registered limited liability partnership, White & Case LLP, a limited liability partnership incorporated under English law and all other affiliated partnerships, companies and entities.

This article is prepared for the general information of interested persons. It is not, and does not attempt to be, comprehensive in nature. Due to the general nature of its content, it should not be regarded as legal advice.

© 2024 White & Case LLP

Daniel Mair (Trainee Solicitor, White & Case, Paris) and Jeffrey Shin (Trainee Solicitor, White & Case, London) contributed to this publication.

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