Sandboxes/Testbeds
Controlled environments for safe AI experimentation.
How the laws define this
Both regulatory instruments conceptualize sandboxes and testbeds as designated controlled environments and testing or experimental facilities for piloting, evaluating, and testing AI systems before full or wider deployment. Where they diverge is in their target scope, specific regulatory objectives, and sectoral focus. The National Strategy for Artificial Intelligence (National strategi for kunstig intelligens) broadly frames these spaces for both public and private actors to undergo monitored learning under regulatory and data-protection guidance, explicitly driving innovation while securing compliance with GDPR and ethical requirements. In contrast, the Malaysia National Artificial Intelligence Roadmap 2021-2025 (AI-RMAP) restricts its focus to high-risk or sectoral AI applications. Rather than focusing on general data-protection compliance, the Malaysia National Artificial Intelligence Roadmap 2021-2025 (AI-RMAP) recommends sandboxes for conformity testing and safety evaluation, specifically aiming to reduce adoption friction in sensitive domains such as healthcare and public services.
Synthesised from the 2 statutory definitions below. Each one is quoted in full, with its source.
Definitions (2)
Designated controlled environments and experimental facilities where public and private actors can pilot AI systems under regulatory and data-protection guidance, enabling testing, evaluation and monitored learning before wider deployment. The strategy promotes their use to support innovation while ensuring compliance with GDPR and ethical requirements.
Designated controlled environments and testing facilities for piloting, validating and evaluating high-risk or sectoral AI applications before full deployment. Sandboxes/testbeds are recommended for conformity testing, safety evaluation, and to reduce adoption friction for sensitive domains such as healthcare and public services.
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