White Paper on Artificial Intelligence Regulation in Ukraine: Vision of the Ministry of Digital Transformation of Ukraine 2024

• Authority: Other authorities
• Collections: Miscellaneous documents
• Most recent activity: Enacted
• Most recent activity date: 2024-06-26

Risk subdomain coverage

Good coverage — Comprehensive governance measures or mitigations with clear procedures relating to the risk subdomain are explicitly described.

• Unfair discrimination and misrepresentation
• Governance failure
• Lack of transparency or interpretability

Minimal coverage — Brief mention but no specific mitigations, recommendations or governance measures relating to the risk subdomain are described.

• Unequal performance across groups
• Compromise of privacy
• False or misleading information
• Disinformation, surveillance, and influence at scale

All other risk subdomains had no coverage in this document.

Risk Coverage Summary

The document has good coverage of approximately 8-10 subdomains, with strong focus on governance failure (6.5), lack of transparency (7.4), unfair discrimination (1.1), privacy compromise (2.1), false information (3.1), disinformation and surveillance (4.1), and unequal performance (1.3). Coverage is concentrated in governance, transparency, discrimination, and misinformation domains.

Sector coverage

Minimal coverage — Brief mention but no specific mitigations, recommendations or governance measures relating to the sector are described.

• Information
• Health Care & Social Assistance
• Public Administration (excl. National Security)
• National Security

All other sectors had no coverage in this document.

Sectors Summary

This is a cross-sectoral governance framework that applies to AI systems across all economic sectors. The document explicitly mentions healthcare and journalism as examples but is designed as a general regulatory approach applicable to both public and private sectors broadly. The regulatory sandbox, impact assessment methodology, and voluntary codes are sector-agnostic tools.

Legislative Status

Soft Law

Legislative Status Summary

This is a policy white paper proposing voluntary tools, recommendations, and codes of conduct to prepare for future mandatory regulation. The document explicitly states these are non-binding measures during Stage 1, with mandatory regulation deferred to Stage 2.

Actors

Proposer

• Entity Types: AI_Governance_Actor
• Entities: Ministry of Digital Transformation of Ukraine
• Summary: The document is explicitly authored and proposed by the Ministry of Digital Transformation of Ukraine, as stated in the title and throughout the document where it describes 'our approach' and 'we propose'.

Target

• Entity Types: AI_Developer, AI_Deployer
• Entities: businesses; companies; private sector; small and medium-sized businesses; startups; large AI platforms; Open AI; Microsoft; AWS; Google
• Summary: The document targets AI developers and deployers, including both private sector companies developing AI products and those deploying them. Specific large platforms are named for cooperation, and the tools are designed for businesses preparing for future regulation.

Enforcer

• Entity Types: AI_Governance_Actor
• Entities: future regulatory body; regulatory authorities of the member states
• Summary: The document discusses the need to establish a future regulatory body for Stage 2 mandatory regulation. Currently, enforcement is through reputational mechanisms for voluntary measures, but a formal regulatory authority is planned.

Monitor

• Entity Types: AI_Governance_Actor, Affected_Stakeholder
• Entities: Ministry of Digital Transformation; NGO Digital Security Lab; Center for Democracy and Rule of Law; civil society organizations
• Summary: The Ministry will monitor through the regulatory sandbox and Responsible AI Centre. Civil society organizations are designated as Trusted Flaggers to monitor platform compliance with user terms regarding human rights violations.

AI Lifecycle Stages

Lifecycle stages covered by the documents, as defined in the OECD Framework for the Classification of AI Systems

• Plan and Design
• Collect and Process Data
• Build and Use Model
• Verify and Validate
• Deploy
• Operate and Monitor

AI Lifecycle Summary

The document covers multiple lifecycle stages with primary focus on Plan and Design, Verify and Validate, Deploy, and Operate and Monitor. The regulatory sandbox, impact assessment methodology, and labeling systems address planning, validation, deployment and monitoring phases. Less emphasis on data collection and model building specifics.

Technical Scope

Terms relating to technical scope that are mentioned or implicitly referenced in the document

• AI Systems
• Generative AI

Technical Scope Summary

The document explicitly mentions AI systems and AI products throughout but does not provide formal definitions. It does not specifically mention AI models, frontier AI, GPAI, foundation models, generative AI, predictive AI, open-weight models, or compute thresholds. The focus is on AI systems broadly without technical categorization.