{"slug":"uk-principles-fairness","id":"AIPT-OBL-0074","permanent_url":"https://aipolicytracker.org/id/AIPT-OBL-0074","title":"Use AI in ways that are fair and do not discriminate unlawfully","short_title":"Fairness","category":"governance_accountability","summary":"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.\n","practical_action":"Test for disparate outcomes across protected characteristics before and after deployment.\n","is_binding":false,"applies_from":null,"section":"Part 3","source_reference":"Principle 3, Part 3","official_source_url":"https://www.gov.uk/government/publications/ai-regulation-a-pro-innovation-approach","review_status":"verified","confidence_level":"high","last_verified_at":"2026-09-26","reviewed_by":"Bhaskar Bhatt","actors":["provider","deployer"],"sectors":["cross_sector","employment","financial_services"],"use_cases":["hiring_and_hr","finance_and_credit"],"applicability":[{"description":"All AI uses affecting people; binding under equality and data-protection law.","actors":["provider","deployer"],"conditions":null}],"evidence_examples":[{"title":"Bias and fairness testing report","description":null,"artifact_type":"report"}],"framework_mappings":[{"framework":"nist_ai_rmf","framework_name":"NIST AI RMF 1.0","reference":"MEASURE 2.11","note":"Fairness and bias evaluation.","confidence_level":"medium","is_original":true}],"controls":[{"slug":"accuracy-robustness-security-testing","title":"Accuracy, robustness, fairness and security testing","kind":"technical","relationship":"satisfies","note":"Disparate-outcome testing across protected characteristics before and after deployment.","confidence_level":"medium","url":"https://aipolicytracker.org/controls/accuracy-robustness-security-testing"},{"slug":"data-governance-and-dataset-documentation","title":"Data governance and dataset documentation","kind":"process","relationship":"supports","note":"Bias checks on training data.","confidence_level":"medium","url":"https://aipolicytracker.org/controls/data-governance-and-dataset-documentation"},{"slug":"ai-impact-assessment","title":"AI impact and fundamental-rights impact assessment","kind":"process","relationship":"supports","note":"Identifies groups at risk of unfair treatment.","confidence_level":"medium","url":"https://aipolicytracker.org/controls/ai-impact-assessment"}],"url":"https://aipolicytracker.org/obligations/uk-principles-fairness","policy":{"slug":"uk-ai-regulation-white-paper","title":"A pro-innovation approach to AI regulation (white paper and government response)","status":"guidance","jurisdiction":"uk","url":"https://aipolicytracker.org/policies/uk-ai-regulation-white-paper"}}