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This document outlines strategic guidelines regarding artificial intelligence and data management within Uruguay. It provides a framework for public sector entities to approach AI adoption and data utilization responsibly. The initiative is part of broader efforts by Agesic to foster digital transformation and innovation in government processes.

The Inter-American Guidelines on Data Governance and AI provide a comprehensive reference framework developed by the Department for Effective Public Management of the OAS. The document outlines twelve key themes ranging from cross-cutting principles and institutional strengthening to research, cybersecurity, and open data to support regional digital transformation. It aims to harmonize policies, ensure respect for human rights, and foster multi-stakeholder collaboration across the Americas.

This document outlines Singapore's International Scientific Exchange on AI Safety, detailing collaborative research, scientific exchange, and safety standards for artificial intelligence. It emphasizes international cooperation to foster safe, secure, and trustworthy AI ecosystems. The framework highlights key technical mechanisms and shared responsibilities for researchers and developers.

Google DeepMind's Frontier Safety Framework sets out protocols for identifying and mitigating severe risks from advanced AI models. It focuses on four risk domains—autonomy, biosecurity, cybersecurity, and machine learning R&D—by establishing Critical Capability Levels, early warning evaluations, and targeted security and deployment mitigations.

This International Standard establishes terminology for artificial intelligence and describes concepts in the field of AI. It is designed to be used in the development of other standards and to support communication among diverse interested parties and stakeholders. The document is applicable to all types of organizations including commercial enterprises, government agencies, and not-for-profit organizations.

This document specifies requirements for functional safety and AI systems, forming part of a standard series developed by ISO/IEC. It provides foundational guidance and technical specifications for integrating artificial intelligence into safety-critical applications. The standard addresses risk assessment, reliability, and safety measures associated with machine learning and AI components.

This document is part of a series covering functional safety and AI systems, specifically providing examples of application under ISO/IEC CD TS 22440-3. It acts as a technical specification draft developed by ISO and IEC committees focused on artificial intelligence. The standard illustrates practical functional safety contexts for AI implementations.

This document outlines Australia's national regulatory and strategic approach to managing artificial intelligence, focusing on mitigating risks, protecting rights, and establishing an AI Safety Institute. It details actions to address harms, promote responsible AI practices in businesses and government, and partner on international norms and global governance. The approach builds on existing technology-neutral legal frameworks while targeting specific emerging AI challenges.

This document is a legislative proposal or law aimed at promoting artificial intelligence and associated technologies in El Salvador. It sets out institutional frameworks and provisions to foster technological development and innovation. The text outlines the governance mechanism and regulatory structure for the advancement of AI within the country.

This document provides a strategic and normative framework for adopting ethical, inclusive, and responsible artificial intelligence across Francophone Africa. Developed through regional collaboration led by Burkina Faso and supported by NIYEL, AUDA-NEPAD, and CITADEL, the guidelines emphasize data governance, digital sovereignty, capacity building, and regional cooperation. They offer practical recommendations for policymakers, researchers, and civil society to ensure AI serves human rights and sustainable development.

This high-level guidance introduces basic concepts for businesses handling Māori data and artificial intelligence in New Zealand. It explains what Māori data and Māori data sovereignty are, outlines practical steps to protect and respect Māori data, and details core values like mana whakahaere and kaitiakitanga. The document emphasizes avoiding harm, ensuring collective benefit, and involving Māori in decision-making and AI development.

This document issues guidelines to organs of the State Administration in Chile regarding the responsible, ethical, secure, and transparent use of artificial intelligence tools. It outlines principles such as human-centric AI, transparency and explainability, privacy and data use, and staff training. Additionally, it establishes communication and monitoring mechanisms for these recommendations.

This document outlines a legislative bill related to the regulation of artificial intelligence systems in Chile, managed by the Ministry of Science, Technology, Knowledge and Innovation. It provides access to the draft bill and related project information for public review.

The UAE Ministry of Health and Prevention (MOHAP) has adopted artificial intelligence to reduce emergency department waiting times through its smart healthcare operation center, known as PaCE. The initiative utilizes predictive analytics and AI-driven monitoring to manage patient flow, bed occupancy, and hospital resources in real time. This deployment aims to enhance healthcare operational efficiency and patient outcomes across emergency facilities.

The National Artificial Intelligence Strategy Committee (NAIS) serves as a core governmental framework and body in South Korea aimed at advancing national artificial intelligence policies and strategies. The portal provides information regarding the committee's initiatives, organizational structure, and strategic directions for fostering AI innovation and governance.

This document outlines comprehensive national AI policy recommendations for Jamaica, presented to the Office of the Prime Minister by the National Artificial Intelligence Task Force. It establishes a strategic roadmap addressing innovation, workforce development, infrastructure, ethical considerations, and regulatory frameworks. The goal is to position Jamaica as a leader in ethical AI adoption while aligning with Vision 2030 and international standards.

This document presents comprehensive policy recommendations developed by Jamaica's National Artificial Intelligence Task Force to harness AI for economic growth, innovation, and societal well-being. It outlines actionable strategies across nine key pillars, including infrastructure development, workforce education, legal frameworks, and ethical AI deployment. The framework aims to position Jamaica as a regional AI innovation hub while safeguarding data privacy and human rights.

The National Artificial Intelligence Strategy of Panama provides an action-oriented blueprint for accelerating AI-enabled economic growth, productivity, workforce readiness, and investment. Structured around six core pillars, the strategy emphasizes digital infrastructure, human capital development, data governance, agile regulation, investment promotion, and sectoral AI applications. It aims to position Panama as Latin America's trusted hub for AI innovation and competitiveness.

The NIST AI RMF Playbook provides voluntary, suggested actions for achieving the outcomes laid out in the four core functions of the AI Risk Management Framework (Govern, Map, Measure, and Manage). It is designed as a flexible, living resource that organizations can adapt to their specific industry use cases and interests. The guidance is non-binding and intended to evolve alongside advancements in artificial intelligence technology.

The United States Department of State and major technology companies have launched the Partnership for Global Inclusivity on AI (PGIAI), committing over $100 million to leverage AI for sustainable development in developing countries while ensuring safety, security, and trustworthiness. The initiative focuses on three main pillars: context, compute, and capacity. Additionally, the U.S. government outlined specific funding commitments for global AI governance, human rights, education, and capacity building.

This policy sets out mandatory requirements and principles for Australian Government agencies regarding AI preparedness and operations. It mandates that agencies establish an approach to embed responsible AI practices within 12 months, implement mandatory staff training, and align with risk management standards. Additionally, it provides recommended actions concerning technical standards, procurement guidance, and capability development.

This document outlines the national strategy and policy for artificial intelligence in Buenos Aires, focusing on digital innovation and governance. It provides a strategic framework for guiding AI development and deployment within the public sector and broader society. The policy serves to structure institutional approaches to emerging technologies.

This document outlines Colombia's National Artificial Intelligence Policy, representing a milestone for the country regarding the approval and implementation of national AI governance. It establishes guidelines and objectives for advancing AI adoption, development, and strategic integration within the nation.

This draft document establishes a principle-code using a comply-or-explain approach for generative AI developers and providers. It aims to balance technological advancement with intellectual property protection and transparency. Businesses are expected to publish transparency measures, respect IP rights, and respond to specific disclosure requests from rights holders and users.

This guidance outlines four key principles to help critical infrastructure owners and operators assess whether artificial intelligence (AI) is suitable for operational technology (OT) environments, understand the unique risks and impacts, establish clear rules and responsibilities, and embed safety and security into AI-enabled systems. It covers techniques ranging from traditional statistical modeling to machine learning and large language models, emphasizing human oversight and functional safety. The document is co-authored by international cybersecurity authorities including CISA, ASD's ACSC, and the NSA.

This document outlines a proposed artificial intelligence bill in Colombia designed to establish a comprehensive legal framework for ethical, responsible, and innovative AI development. It creates an institutional governance structure led by MinCiencias, introduces a risk-based classification system, and sets obligations for AI actors across sectors such as healthcare, education, and labor. The bill also establishes regulatory sandboxes, intellectual property provisions, and a progressive supervisory regime.

This publication ethics and publication malpractice statement outlines the responsibilities of editors, reviewers, and authors for the Irish Journal of Applied Social Studies. It is based on the Committee on Publication Ethics (COPE) guidelines and governs academic integrity, peer review, conflicts of interest, and open access publishing. The text ensures transparent handling of manuscripts, original research standards, and proper licensing through Creative Commons.

This publication ethics and publication malpractice statement outlines the responsibilities of editors, reviewers, and authors for the Irish Journal of Applied Social Studies. It establishes guidelines on peer review, confidentiality, conflicts of interest, originality, plagiarism, and authorship. The policy ensures transparent and ethical academic publishing standards for all submissions.

Recital 10 of the AI Act clarifies that the regulation does not affect existing EU data protection laws, including Regulations (EU) 2016/679 and (EU) 2018/1725, Directive (EU) 2016/680, and Directive 2002/58/EC. It ensures that data subjects retain all their rights, guarantees, and protections—such as those related to automated decision-making and profiling—when AI systems process personal data. Furthermore, the AI Act's harmonised rules are designed to facilitate the effective implementation and exercise of these existing data protection rights and remedies.

This document provides recommendations on the protection of personal data in the field of artificial intelligence under the Personal Data Protection Law No. 6698. It outlines general principles, technical and administrative measures, and specific guidance for developers, manufacturers, service providers, and decision makers. The aim is to ensure that AI applications respect fundamental rights, human dignity, and privacy.

This document outlines the draft regulation for Peru's Law No. 31814, which promotes the development and responsible use of artificial intelligence for economic and social development. It establishes general provisions, a governance framework led by the Presidency of the Council of Ministers, risk management classifications, and specific obligations for public administration and private entities. Additionally, it addresses data protection, transparency, digital security measures, and the promotion of talent, ethics, and controlled experimentation environments (sandboxes).

This document presents responses to a questionnaire concerning the impact of artificial intelligence and digital technologies on the rights of women and girls in Haiti. It examines issues such as technology-facilitated gender-based violence, gender representation in tech, algorithmic bias, and barriers to digital education and employment. The submission calls for proactive measures including legal frameworks, inclusive training programs, and data disaggregation to ensure AI promotes gender equality rather than reinforcing existing inequalities.

This voluntary resource helps New Zealand businesses, sole traders, and non-profits realize the benefits of artificial intelligence by using and developing AI systems in a trustworthy manner. It outlines considerations, risks, and safeguards aligned with OECD AI principles and New Zealand's proportionate risk-based approach to AI. The guidance is structured around understanding your purpose for AI, establishing good business foundations, and considering AI system-specific factors across the AI life cycle.

This document is an academic or professional journal issue published by the Escuela del Cuerpo de Abogados y Abogadas del Estado. The text contains binary and encoded data streams that prevent the extraction of specific governance facts, summaries, or structured content.

These guidelines from the Ministry of Business, Innovation and Employment advise businesses on managing stakeholder interactions during AI development and use. It covers conducting stakeholder impact assessments, engaging and consulting with impacted groups including underrepresented communities, maintaining transparency, and establishing effective feedback and complaints processes.

This statement by the European Data Protection Board (EDPB) addresses the role of national data protection authorities (DPAs) within the regulatory framework of the European Union's Artificial Intelligence Act. It highlights that EU data protection law and the AI Act are complementary, emphasizes the suitability of DPAs to act as market surveillance authorities for high-risk AI systems, and recommends close cooperation and adequate resourcing.

This statement by the European Data Protection Board outlines the role of data protection authorities in the implementation and enforcement framework of the EU Artificial Intelligence Act. It recommends that Member States designate data protection authorities as market surveillance authorities for high-risk AI systems and points of contact. Furthermore, it emphasizes the need for complementary enforcement, adequate resources, and effective cooperation between data protection authorities and the EU AI Office.

This document provides an official analysis and response from the Legal Bureau of the Ministry of Communication and Digital regarding questions about artificial intelligence regulation in Indonesia. It outlines the role of AI in national digital transformation, the legal justification for using soft law instruments such as circular letters, and the ongoing drafting of two Presidential Regulations concerning the National AI Roadmap and AI Ethics. Furthermore, it details how AI has been incorporated into the National Long-Term and Medium-Term Development Plans for 2025–2045.

This document outlines Australia's national strategy for ensuring robotics and automation technologies are developed and used safely, securely, ethically, and inclusively. It focuses on updating regulatory frameworks, understanding social impacts, engaging in international standards-setting, and improving the safety and cyber security of robotics. Case studies illustrate ethical guidelines for drone use on Jawoyn Country and assistive robotics for people with spinal cord injuries.

The National AI Policy for the Republic of Rwanda serves as a strategic roadmap to harness artificial intelligence for sustainable and inclusive socio-economic growth, positioning the country as a leading African innovation hub and center of excellence. It outlines six priority policy areas covering 21st-century skills, reliable infrastructure, robust data strategy, public sector adoption, private sector adoption, and practical ethical guidelines. The policy includes a comprehensive implementation plan to coordinate stakeholders, foster innovation, and mitigate the risks associated with AI deployment.

The National Guidelines on AI Governance & Ethics provide a framework for the responsible development and deployment of artificial intelligence technologies in Malaysia. They outline core ethical principles and practical guidance for stakeholders to ensure safe, transparent, and fair AI systems.

This guidance document helps businesses understand their purpose, principles, and objectives when adopting or developing artificial intelligence systems. It outlines practical steps for getting started, such as identifying inefficiencies, evaluating data assets, conducting cost-benefit analyses, and experimenting safely. Additionally, it encourages cross-functional teams to align AI adoption with existing policies on information security, data management, legal compliance, and privacy.

This guidance document covers considerations for managing AI system inputs, outputs, and human-in-the-loop decision-making in business settings. It highlights risks such as hallucinations, data privacy concerns with prompts, automation bias, and intellectual property challenges, offering practical tips and scenarios for responsible AI deployment.

This institutional guidance from Health New Zealand | Te Whatu Ora outlines requirements and restrictions for health professionals regarding the use of generative artificial intelligence and large language models. It details mandatory prohibitions against entering personal or confidential patient information into unapproved tools and using them for clinical decisions or personalized advice. Furthermore, it outlines benefits, risks such as privacy breaches and inaccuracies, and requires employees to take full responsibility for generated information and acknowledge its use.

This landscape report offers a comparative study of the global legal landscape regarding the intersection of artificial intelligence and intellectual property law. It examines key issues such as whether AI systems can be named as inventors or authors, patentability requirements, copyright protection for AI-generated works, design and trademark implications, and the challenges of IP infringement in the age of AI. Published as a collaboration between the Intellectual Property Office of Singapore and the SMU Centre for AI and Data Governance, the report serves as a resource for policymakers, lawmakers, technology developers, and civil society.

This whitepaper outlines the establishment, objectives, and ongoing work of the ITU/WHO Focus Group on Artificial Intelligence for Health (FG-AI4H). It details how the group develops international evaluation standards, guidelines, and an online benchmarking platform to assess AI solutions in healthcare. Additionally, it discusses current AI applications in health, major technical and ethical challenges such as data bias and interpretability, and future directions for global digital health standardization.

This academic and legal position paper examines civil liability for errors and damages caused by robots and artificial intelligence systems under Bahraini civil law. It analyzes different jurisprudential approaches regarding the legal status of robots—ranging from treating them as things or animals to recognizing them as having a special legal nature or independent legal personality. Finally, the author proposes legislative recommendations, including mandatory insurance requirements, stricter regulations on robot manufacturing and use, and amendments to the Bahraini Civil Code to address AI-related liabilities.

This is the information security policy of the Ministry of Digital Economy and Entrepreneurship in Jordan, aiming to protect information confidentiality, integrity, and availability. The policy applies to permanent and temporary employees as well as external contractors, establishing security controls and risk management based on the ISO 27001 standard.

This information security policy by the Jordanian Ministry of Digital Economy and Entrepreneurship aims to ensure the confidentiality, integrity, and availability of information assets. It establishes security controls, risk management practices aligned with ISO 27001, and awareness programs to protect critical infrastructure and services. The policy applies to all permanent and temporary employees, contractors, and business partners.

This document outlines the information security policy of the Ministry of Digital Economy and Entrepreneurship in Jordan. It establishes security controls to protect information assets, ensure confidentiality, integrity, and availability, and comply with local legislation and international standards like ISO 27001. The policy applies to all permanent and temporary employees, external contractors, and business partners.