Promotes responsible AI innovation through sector-specific regulation, risk-based approaches, and "soft" regulatory tools. Establishes an AI Policy Coordination Center to advise and coordinate AI regulation, fostering international consistency. Recommends adopting ethical AI principles and creating tools for responsible AI development.
Good coverage — Comprehensive governance measures or mitigations with clear procedures relating to the risk subdomain are explicitly described.
Minimal coverage — Brief mention but no specific mitigations, recommendations or governance measures relating to the risk subdomain are described.
All other risk subdomains had no coverage in this document.
Risk Coverage Summary
The document has good coverage of approximately 12-14 subdomains, with strong focus on discrimination (1.1, 1.3), privacy (2.1), security (2.2), misinformation (3.1), human-computer interaction (5.1, 5.2), socioeconomic impacts (6.1, 6.2, 6.4, 6.5), and AI system safety (7.3, 7.4). Coverage is concentrated in fairness, transparency, governance, and technical reliability domains.
Minimal coverage — Brief mention but no specific mitigations, recommendations or governance measures relating to the sector are described.
All other sectors had no coverage in this document.
Sectors Summary
This is a cross-sectoral policy document that provides guidance for regulating AI across all economic sectors in Israel's private sector. It explicitly mentions healthcare, finance, education, transportation, agriculture, energy, construction, and manufacturing. The policy adopts a sectoral regulation approach where each sector's regulator develops appropriate AI governance.
Soft Law
Legislative Status Summary
This is a non-binding policy document that provides recommendations and guidelines for sectoral regulators. It explicitly uses voluntary language ('should', 'recommends') and establishes principles that are 'not construed as legally binding.' The document creates a coordination framework rather than enforceable obligations.
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Lifecycle stages covered by the documents, as defined in the OECD Framework for the Classification of AI Systems
AI Lifecycle Summary
The document explicitly addresses the entire AI lifecycle with special focus on use and deployment stages. It covers planning and design through ethical principles, data collection through privacy considerations, model development through accountability requirements, validation through risk assessment, deployment through disclosure requirements, and operation through monitoring and accountability frameworks.
Terms relating to technical scope that are mentioned or implicitly referenced in the document
Technical Scope Summary
The document explicitly mentions AI systems and AI models throughout. It references Foundation Models and Frontier AI as areas for future work. It does not explicitly define or distinguish between general purpose AI, task-specific AI, generative AI, or predictive AI. There is no mention of compute thresholds or open-weight/open-source models.
Document data from AGORA, CSET Emerging Technology Observatory.