Practical requirements extracted from policy instruments, with the source article, the actors they bind, evidence examples and original framework mappings. Legal requirements are marked; everything else is voluntary guidance.
31 results · page 2 of 2
UK AI regulation framework · Principle 3, Part 3
AI systems should not undermine legal rights, discriminate unfairly or create unfair market outcomes. The Equality Act 2010 and UK GDPR fairness principle make key parts of this binding.
Singapore Model AI Governance Framework · Second edition, Part on human involvement in AI-augmented decision-making
Using a risk-impact matrix (probability and severity of harm), organisations choose human-in-the-loop, human-over-the-loop or human-out-of-the-loop designs and document the rationale.
UK AI regulation framework · Principle 5, Part 3
Affected people should be able to contest harmful AI decisions or outcomes and obtain redress, through existing complaint routes and regulators.
NIST AI RMF · MANAGE function
Manage allocates resources to mapped and measured risks, plans responses including decommissioning, manages third-party risks, and documents post-deployment monitoring, incident response and communication.
UK AI regulation framework · Principle 2, Part 3
Organisations should communicate when and how AI is used and provide explanations proportionate to the risk, so that people can understand decisions affecting them. For personal data, UK GDPR transparency and automated decision-making rights make this binding in practice.
Australian Voluntary AI Safety Standard · Guardrails 7, 8 and 9
Establish processes for people impacted by AI to challenge use or outcomes; be transparent with other organisations across the AI supply chain about data, models and systems; and keep and maintain records to allow third parties to assess compliance.
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