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Implementation standards, guidelines, and documented best practices for AI development.
Also in Shared Infrastructure
2.1 Decisions based on AI systems should be fair and non-discriminatory, judged against the same standards as decision-making processes conducted entirely by humans. 2.2 The use of AI systems by organisations that develop, deploy or use AI systems and Governments should not serve to exempt or attenuate the need for fairness, although it may mean refocussing applicable concepts, standards and rules to accommodate AI. 2.3 Users of AI systems and persons subject to their decisions must have an effective way to seek remedy in discriminatory or unfair situations generated by biased or erroneous AI systems, whether used by organisations that develop, deploy or use AI systems or governments, and to obtain redress for any harm.
Reasoning
Establishes fairness and non-discrimination standards guiding AI decision-making across organizations and governments.
Ethical Purpose and Societal Benefit
Organisations that develop, deploy or use AI systems and any national laws that regulate such use should require the purposes of such implementation to be identified and ensure that such purposes are consistent with the overall ethical purposes of beneficence and non-maleficence, as well as the other principles of the Policy Framework for Responsible AI.
3.2.2 Technical StandardsEthical Purpose and Societal Benefit > Overarching principles
2.1.3 Policies & ProceduresEthical Purpose and Societal Benefit > Work and automation
2.2.1 Risk AssessmentEthical Purpose and Societal Benefit > Environmental impact
2.2.1 Risk AssessmentEthical Purpose and Societal Benefit > Weaponised AI
3.1.3 International AgreementsEthical Purpose and Societal Benefit > The weaponisation of false or misleading information
1.2.1 Guardrails & FilteringOther (outside lifecycle)
Outside the standard AI system lifecycle
Governance Actor
Regulator, standards body, or oversight entity shaping AI policy
Govern
Policies, processes, and accountability structures for AI risk management