Knowledge
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1000+ Global AI Regulations - Turning AI Regulations into Opportunities: Are You Ready?

Published on
October 15, 2024
Contributor(s)
Dr. Nicolai Bohn
Founder
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The rise of Generative AI (Gen AI) offers enormous potential for transforming business processes but also introduces complex ethical, legal, and operational challenges. Its ability to autonomously generate content has raised global concerns, leading to an unprecedented surge in regulatory frameworks aimed at mitigating associated risks.

From the EU's ambitious AI Act to the UK's National AI Strategy and the US Executive Order on AI Development, countries are racing to establish guidelines for responsible AI use. The regulatory landscape is evolving rapidly, with each new update adding layers of complexity for businesses developing or deploying AI systems. Even experts find it challenging to stay current as new proposals and frameworks are continually being introduced.

We started to track global AI regulation ourselves to understand the (most recent) developments and some of the key policies to be aware of. Today, we decided to publish our list to help businesses extend their own list of legislation tracking and navigate these changes. This resource provides an overview of key regulation, broken down by jurisdiction and year, so you can stay ahead of the curve. You’ll find the full list below, with links to detailed country-level overviews.

Continent Country Year Regulation
Europe EU 2018 EU Strategy For Artificial Intelligence
2019 Ethics guidelines for trustworthy Al 2019
2020 White Paper on Artificial Intelligence: a European approach to excellence and trust
2020 Resolution on automated decision-making processes
2021 Coordinated Plan on Artificial Intelligence 2021 Review
2022 EU Al Liability Directive
2024 EU AI Act
UK 2021 National Al Strategy 2021
2021 Guidance on Al and data protection
2022 Defence Al strategy
2022 Explaining decisions made with AI
2022 National AI Strategy - AI Action Plan
2022 Policy Paper: Establishing a pro-innovation approach to regulating AI 2022
2023 CMA AI Foundation Models: Initial Report
2024 UK Artificial Intelligence (Regulation) Bill
North America US 2020 The National Al Initiative Act
2021 FTC / aiming for truth, fairness and equity in companies' use of Al
2021 Al and algorithmic fairness initiative
2023 Blueprint for an Al bill of rights
2023 NIST Al risk management framework
2023 Al Disclosure Act
2023 US Executive Order on the Safe, Secure, and Trustworthy Development and Use of Artificial Intelligence
CANADA 2017 PAN-CANADIAN AI STRATEGY
2021 Directive on use of automated decision-making by federal government
2022 Bill C-27: digital charter implementation) act to include artificial intelligence and data act (AIDA part C)
2023 Guidance on generative Al
South America ARGENTINA 2023 Recommendations for a trustworthy Artificial Intelligence
2023 Bill 2505-D-2023 for the Regulation of the development and use of Al
BRAZIL 2021 Ordinance No. 4617 of 04.06.2021
2021 National Al Strategy
2023 Bill No. 2338/2023 to regulate artificial intelligence
CHILE 2021 National Policy on Artificial Intelligence 2021-2030
2022 Guide to the Ethical F ... Science Projects
COLOMBIA 2019 National Policy for Digital Transformation and Al
2022 Bill-253-2022 for the development, use and implementation of Al
2023 Bill 59 to regulate Al
PERU 2021 Peru National Al Strategy
2023 Law promoting the use of Al for the economic and social development of Peru (No 21814) 2023
Middle East SAUDI ARABIA (KSA) 2020 National Strategy for Data and Al
2023 Al Ethics Principles version 2.0
2024 Guidelines on generative Al for Government 2024
2024 Guidelines on generative AI for general public 2024
UAE 2018 UAE National Strategy for Artificial Intelligence 2031
Asia CHINA 2022 Provisions on the Administration of Internet Information Service Algorithm Recommendations (translation)
2023 Measures for the Management of Generative Al Services (translation)
2023 Regulations on the Administration of Deep Synthesis of Internet Information Technology
2023 Information Security Technology - Al Computing Platform Security Framework
2023 Regulations on the Safety Management of Facial Recognition Technology Application
INDIA 2023 Presentation Proposal for a Digital India Act
2023 National Strategy on Robotics
2024 Complex Adaptive System Framework to Regulate Al
JAPAN 2021 Report on Al Governance in Japan Ver. 1.1
2022 Al guidelines for implementation of Al Principles ver. 1.1
2022 Al strategy
2023 ML Quality management guideline
2024 Al Operator Guidelines 2023+Al Business Guidelines
MALAYSIA 2021 National Al Roadmap 2021-2025
TURKEY 2021 National Al strategy 2021-2025
SINGAPORE 2019 National Al strategy 2019+ Strategy
2020 Al governance approach+implementation self-assessment guide
2021 Al governance testing framework MVP
2022 A.I. Verify
2024 Model AI Governance Framework for Generative AI 2024
SOUTH KOREA 2023 MIST Digital rights charter outlining principles for a global digital normative order 2023
2023 MSIT Digital technology standardisation strategy 2023
Oceania AUSTRALIA 2021 Australia's Al action plan 2021
2023 Report on Safe and Responsible use of Al 2023
2023 Rapid Response Information Report Generative AI: Language models and multimodal foundation models
2024 Guideline on Engaging with Al 2024
NEW ZEALAND 2020 Algorithm Charter 2020
United Nations 2024 Seizing the opportunities of safe, secure and trustworthy artificial intelligence systems for sustainable development

Tab. 1: Non-exhaustive list of global AI regulation

We recently learned that OECD.AI has been conducting a similar effort and has compiled an even more extensive list. On the OECD.AI Policy Dashboard, you can now find 'over 1000 AI policy initiatives from 69 countries, territories, and the EU.'

No global consensus

Countries around the world are approaching AI regulation in different ways and at various stages of development. Some, like the EU, have opted for comprehensive, overarching frameworks, as seen with the EU AI Act, which aims to create a uniform approach across member states. Others, such as the UK, prefer a more flexible, regulator-led model, focusing on industry-specific guidance and principles, without introducing blanket legislation.
Global consensus on a unified regulatory approach to AI seems unlikely. However, international efforts like the United Nations' draft resolution on AI, passed in March 2024, represent steps toward global cooperation. This resolution encourages nations to prioritize human rights, data protection, and risk mitigation in AI use, though it stops short of creating legally binding regulations. The goal is to foster trust and transparency while ensuring AI systems are developed responsibly on a global scale.

Reflection: How to Navigate the Complex Regulatory Landscape

With this overwhelming surge of AI regulations, organizations may respond with one of two main approaches:

1. Reactive Approach: Fear and Hesitation
One response to the sheer volume of new regulations is to become overwhelmed and adopt a reactive stance. In this scenario, companies may wait for regulatory bodies to finalize decisions before taking any action. This strategy, however, comes with serious risks. Delayed responses can lead to rushed implementation, non-compliance fines, and failure to align with industry best practices. Worse yet, the reactive approach could leave companies vulnerable to legal, reputational, and operational risks—and significantly diminish their competitiveness in a rapidly evolving market.

2. Proactive Approach: Embrace and Innovate
Alternatively, companies can choose to view this regulatory wave as an opportunity. AI governance plays a critical role in ensuring systems are safe and trustworthy. By engaging with regulations early on and embedding internal governance structures into AI development, organizations can gain a competitive edge. Proactive companies have the chance to innovate in compliance technologies, improve transparency, and bolster their ethical standing. The widespread governmental focus on AI governance signals that these frameworks are not only necessary but are becoming valuable benchmarks for industry maturity. Engaging with them early allows companies to lead the way in ethical AI deployment, all while staying compliant.

The Implementation Challenge: Navigating and Validating Gen AI Applications Against Regulatory Standard

While embracing regulation is a proactive approach, the actual implementation can be daunting. Each jurisdiction presents unique challenges, with varying compliance timelines and rules. For example, the EU AI Act has strict guidelines for high-risk AI systems, whereas the US focuses heavily on fairness, transparency, and accountability. Successfully navigating these distinctions requires in-depth knowledge of both local and global regulations to ensure legal and operational compliance.

How Rhesis AI Can Help

At Rhesis AI, we understand how difficult it can be to ensure Gen AI applications comply with constantly evolving regulations. That's why we provide Tailored Validation Test Sets that make validating AI applications easier and more efficient.

Our service offers curated, continuously updated validation sets tailored to industry-specific needs, individual regulations, including data privacy laws, algorithmic fairness, and transparency standards. By incorporating Rhesis AI's test benches, you can:

  • Automate robustness, reliability and compliance testing.
  • Ensure your AI applications are trustworthy, ethical, and secure.
  • Stay ahead of regulatory changes without sacrificing innovation.

With Rhesis AI, regulatory compliance becomes a competitive advantage, not a burden. Let us help you navigate the AI regulatory landscape and build stronger, more reliable AI systems.

Conclusion: Seize the Opportunity

While the current AI regulatory landscape may seem overwhelming, forward-thinking organizations can turn this challenge into an opportunity. By staying informed, engaging proactively with regulations, and building robust compliance strategies, companies can position themselves as leaders in AI governance. Rather than viewing AI regulations as an obstacle, businesses should see them as a path to enhancing public trust, ensuring ethical AI use, and staying at the forefront of technological advancement.

Sources:

OECD.AI (2021), powered by EC/OECD (2021), database of national AI policies, accessed on 15/10/2024, https://oecd.ai.

Sanni Kumar (2021), World Map. Licensed under CC BY 4.0.

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