Can We Regulate Trust?
An interactive exploration of AI trust and regulation across 47 countries worldwide.
AI Regulation Landscape Tiers
Minimal Regulatory Involvement
Governments take a largely hands-off approach, focusing on enabling innovation and growth in AI technologies with sparse direct regulation. These governments emphasize voluntary guidelines, industry self-regulation, and public-private collaboration rather than binding legal instruments.
Adaptation of Existing Laws
Instead of creating entirely new regulatory structures, governments at this level apply and modify pre-existing legal frameworks to address the specific challenges posed by AI. This approach seeks to fill regulatory gaps by leveraging well-established legal principles to ensure that AI systems are subject to the same standards as other technologies and services.
Comprehensive National AI Regulatory Framework
The most proactive governments create dedicated, AI-specific legislation or regulatory frameworks that address the unique risks, ethical questions, and societal impacts AI poses. These frameworks typically encompass a wide range of considerations, including transparency, explainability, accountability, human oversight, data governance, and protections against bias and discrimination.
The AI Trust Framework
Many elements influence public trust in AI. This conceptual framework defines 14 critical factors for fostering public trust in AI across 4 main categories: regulation, accountability, transparency, and ethical standards.
Explore the Full Report
Access the complete research findings, methodology, and analysis from our comprehensive study of AI regulation across 47 countries.
Stay Connected
Follow our work and get in touch for questions or feedback about this research.
