Smart Dubai AI Ethics Principles & Guidelines
SMART DUBAI AI ETHICS PRINCIPLES & GUIDELINES
This document outlines the AI Ethics Principles and Guidelines established by Smart Dubai to support the ethical design, deployment, and governance of artificial intelligence systems. It focuses on four core pillars: fairness, accountability, transparency, and explainability, particularly for systems that inform significant or critical decisions in both public and private sectors. The framework aims to foster responsible AI innovation that delivers human benefit, fairness, and trust.
Summary and content fields are drawn from the document text and are pending editorial review.
Who issued it
Who it governs
This document is for AI developers, operators, policymakers, and organizations in the public and private sectors seeking practical guidance on implementing ethical AI practices.
What the document contains
The document covers principles and guidelines for ethical AI design and deployment, specifically addressing fairness, accountability, transparency, and explainability for systems that make or inform significant or critical decisions. It provides detailed definitions, guidance notes, and practical examples for developers and operators across public and private sectors.
The guidelines explicitly exclude employment issues, general model accuracy (except for fairness and redress), privacy concerns (as they are governed separately), and external auditing mechanisms, which are currently suspended.
- AI systems should be fair, accountable, transparent, and as explainable as technically possible.
- Accountability for AI outcomes rests with the designers, developers, and operators rather than the AI system itself.
- Organizations should ensure that datasets are representative and that decision-making processes avoid non-operational bias.
- Affected individuals should be informed when significant decisions are made by AI and given pathways to challenge or appeal such decisions.
- The guidelines apply to systems making or informing significant or critical decisions in both public and private sectors.
· AI Principles (Ethics, Security, Humanity, Inclusiveness) · AI Guidelines (Introduction, Scope, Definitions) · 1.1 We will make AI systems fair · 1.2 We will make AI systems accountable · 1.3 We will make AI systems transparent · 1.4 We will make AI systems as explainable as technically possible · Changelog · Bibliography
How it scores
Each score is backed by a quote verified against the document text. Editorial review has not yet confirmed them.
Accountability
4/5Clear responsibility for AI outcomes
Accountability for the outcomes of an AI system lies not with the system itself but is apportioned between those who design, develop and deploy it
WE WILL MAKE AI SYSTEMS ACCOUNTABLE
screening score · 2026-10-23
Fairness
4/5Non-discrimination and equitable treatment
AI developer organisations and AI operator organisations should refrain from training AI systems on data that is not likely to be representative of the affected AI subjects
1.1.1.2
screening score · 2026-10-23
Human Dignity
4/5Respect for the inherent worth of persons
AI systems should conform to international norms and standards with respect to human values and people rights and acceptable behaviour
INCLUSIVENESS
screening score · 2026-10-23
Human Oversight
4/5Humans remain in control of consequential decisions
Such systems should be able to be overridden or their decisions reversed by designated people
AI SYSTEMS WILL BE SAFE, SECURE AND CONTROLLABLE BY HUMANS
screening score · 2026-10-23
Privacy
4/5Protection of personal data and private life
Surveillance or other AI-driven technologies should not be deployed to the extent of violating internationally and/or UAE’s accepted standards of privacy and human dignity and people rights
INCLUSIVENESS
screening score · 2026-10-23
Transparency
4/5Openness about how AI systems work and are used
People should be told when significant decisions about them are being made by AI
WE WILL MAKE AI SYSTEMS TRANSPARENT
screening score · 2026-10-23
Enforcement
1/5Consequences and compliance mechanisms with real force
AI operator organisations could consider compensating affected AI subjects in the case of loss or inconvenience caused by incorrect automated decisions
1.2.4.6
screening score · 2026-10-23
Impact Assessment
4/5Required assessment of an AI system's risks/impacts before or during use
AI developer organisations and AI operator organisations could consider formal procedures such as Discrimination Impact Assessments as a means of ensuring fairness
1.1.3.1
screening score · 2026-10-23