Consultation Paper on AI Regulation: Emerging Approaches Across the World
August 2024
Digital
Digital
Since 2016, over thirty countries have passed laws explicitly mentioning AI, and in 2024, the discussion about AI bills in legislative bodies has increased globally. This policy brief aims to inform legislators about the different regulatory approaches to artificial intelligence (AI) being considered worldwide by legislative bodies.
The brief explains nine emerging regulatory approaches, each illustrated with specific cases worldwide. The order in which the nine AI regulatory approaches are presented is deliberately structured to guide readers from less interventionist, light-touch regulatory measures to more coercive, demanding approaches. These regulatory approaches are not mutually exclusive and AI bills often combine two or more approaches:
Principles-Based Approach: Offer stakeholders a set of fundamental propositions (principles) that provide guidance for developing and using AI systems through ethical, responsible, human-centric, and human-rights-abiding processes.
Standards-Based Approach: Delegate (totally or partially) the state’s regulatory powers to organisations that produce technical standards that will guide the interpretation and implementation of mandatory rules.
Agile and Experimentalist Approach: Generate flexible regulatory schemes, such as regulatory sandboxes and other testbeds, that allow organisations to test new business models, methods, infrastructure, and tools under more flexible regulatory conditions and with the oversight and accompaniment of public authorities.
Facilitating and Enabling Approach: Facilitate and enable an environment that encourages all stakeholders involved in the AI lifecycle to develop and use responsible, ethical, and human rights-compliant AI systems.
Adapting Existing Laws Approach: Amend sector-specific rules (e.g., health, finance, education, justice) and transversal rules (e.g., criminal codes, public procurement, data protection laws, labor laws) to make incremental improvements to the existing regulatory framework.
Access to Information and Transparency Mandates Approach: Require the deployment of transparency instruments that enable the public to access basic information about AI systems.
Risk-Based Approach: Establish obligations and requirements in accordance with an assessment of the risks associated with the deployment and use of certain AI tools in specific contexts.
Rights-Based Approach: Establish obligations or requirements to protect individuals' rights and freedoms
Liability Approach: Assign responsibility and sanctions to problematic uses of AI systems.
The policy brief suggests parliamentarians how they can address three key questions before adopting AI regulations:
Why regulate? Determine whether regulation is needed to address public problems, fundamental and collective rights, or desirable futures.
**When to regulate? **Reach a consensus on why regulation is needed, map available regulatory instruments, compare them with other policy instruments, and assess the feasibility of adopting the former.
How to regulate? Identify a combination of AI regulatory approaches that are tailored to specific contexts.
Contents:
Executive Summary
Introduction
Global Landscape of AI Regulation
Emerging AI Regulatory Approaches
Key Considerations For Parliamentarians
Conclusions
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Consultation Paper on AI Regulation: Emerging Approaches Across the World
August 2024
Digital
Digital
Since 2016, over thirty countries have passed laws explicitly mentioning AI, and in 2024, the discussion about AI bills in legislative bodies has increased globally. This policy brief aims to inform legislators about the different regulatory approaches to artificial intelligence (AI) being considered worldwide by legislative bodies.
The brief explains nine emerging regulatory approaches, each illustrated with specific cases worldwide. The order in which the nine AI regulatory approaches are presented is deliberately structured to guide readers from less interventionist, light-touch regulatory measures to more coercive, demanding approaches. These regulatory approaches are not mutually exclusive and AI bills often combine two or more approaches:
Principles-Based Approach: Offer stakeholders a set of fundamental propositions (principles) that provide guidance for developing and using AI systems through ethical, responsible, human-centric, and human-rights-abiding processes.
Standards-Based Approach: Delegate (totally or partially) the state’s regulatory powers to organisations that produce technical standards that will guide the interpretation and implementation of mandatory rules.
Agile and Experimentalist Approach: Generate flexible regulatory schemes, such as regulatory sandboxes and other testbeds, that allow organisations to test new business models, methods, infrastructure, and tools under more flexible regulatory conditions and with the oversight and accompaniment of public authorities.
Facilitating and Enabling Approach: Facilitate and enable an environment that encourages all stakeholders involved in the AI lifecycle to develop and use responsible, ethical, and human rights-compliant AI systems.
Adapting Existing Laws Approach: Amend sector-specific rules (e.g., health, finance, education, justice) and transversal rules (e.g., criminal codes, public procurement, data protection laws, labor laws) to make incremental improvements to the existing regulatory framework.
Access to Information and Transparency Mandates Approach: Require the deployment of transparency instruments that enable the public to access basic information about AI systems.
Risk-Based Approach: Establish obligations and requirements in accordance with an assessment of the risks associated with the deployment and use of certain AI tools in specific contexts.
Rights-Based Approach: Establish obligations or requirements to protect individuals' rights and freedoms
Liability Approach: Assign responsibility and sanctions to problematic uses of AI systems.
The policy brief suggests parliamentarians how they can address three key questions before adopting AI regulations:
Why regulate? Determine whether regulation is needed to address public problems, fundamental and collective rights, or desirable futures.
**When to regulate? **Reach a consensus on why regulation is needed, map available regulatory instruments, compare them with other policy instruments, and assess the feasibility of adopting the former.
How to regulate? Identify a combination of AI regulatory approaches that are tailored to specific contexts.
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