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.
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ICO AI guidance · UK GDPR Article 22 as amended by the Data (Use and Access) Act 2025
Individuals have rights in relation to solely automated decisions that produce legal or similarly significant effects, including being told about the decision, obtaining human intervention, and contesting it. The Data (Use and Access) Act 2025 amended these rules; the reviewer must confirm the current wording.
EU AI Act · Article 14; Article 26(2) for deployers
High-risk systems must be designed with human-machine interface tools so natural persons can effectively oversee them, understand capacities and limitations, avoid automation bias, interpret output, decide not to use the system, and intervene or stop it. Deployers must assign oversight to people with the necessary competence, training and authority. For certain remote biometric identification systems, action requires verification by at least two competent persons.
UAE PDPL · Article on data-subject rights relating to automated processing (reviewer to cite article number)
Data subjects may object to decisions based solely on automated processing, including profiling, that produce legal or similarly serious effects, subject to exceptions such as contractual necessity or consent.
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.
Australian Voluntary AI Safety Standard · Guardrails 4, 5 and 6
Test AI models and systems before deployment and monitor them in operation; enable meaningful human control and intervention; and inform end users about AI-enabled decisions, interactions with AI and AI-generated content.
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