SDAIA issues AI bias reference guide with over 100 bias types

A new reference guide from the Saudi Data and Artificial Intelligence Authority catalogues over 100 types of bias in AI systems, outlining their origins, real-world implications, and methods to enhance fairness.

As AI adoption accelerates in critical sectors worldwide, addressing algorithmic bias has become a priority for regulators and developers alike.

July 21, 2026 | 11:14 PM

July 21, 2026 | 11:14 PM

Saudi Gazette

Last Updated: July 21, 2026 | 11:14 PM

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RIYADH — The Saudi Data and Artificial Intelligence Authority (SDAIA) has released the first edition of its AI Bias Reference Guide, identifying more than 100 types of bias that could affect the accuracy and fairness of artificial intelligence systems.

The publication categorizes AI bias variations, clarifies how they originate, assesses their societal impact, and offers tangible examples along with actionable steps to reduce their effects.

SDAIA said the rapid adoption of AI across critical sectors, including justice, healthcare and education, has heightened the need to address biases that may influence decision-making due to the complexity of AI systems and the multiple stages involved in their development.

The guide states that unaddressed bias may compromise AI performance, transforming systems designed to foster equity into instruments that perpetuate inequality. It also cautions that such bias can harm institutional credibility and lead to legal risks and public grievances.

The guide identifies several sources of bias, including training data that does not adequately represent all population groups, algorithms that may unintentionally favor certain characteristics, and assumptions made during data interpretation. It cites recruitment tools that may give preference to candidates from elite educational backgrounds over equally qualified applicants from less privileged backgrounds as one example.

The publication builds on SDAIA's broader efforts to promote responsible and ethical AI, following the release of its AI Ethics Principles, Generative AI Principles for government entities and the public, the AI Adoption Framework, and its study titled Bias in Artificial Intelligence Systems: Challenges and Solutions.

As the Kingdom's national authority for data and artificial intelligence, SDAIA said it will continue supporting specialized knowledge and developing national capabilities in advanced technologies to encourage the responsible use of AI, and strengthen digital innovation.

The release of this guide underscores SDAIA's commitment to responsible AI development amid increasing reliance on automated systems in high-stakes domains. By cataloguing diverse bias types, the authority aims to provide a practical resource for developers and policymakers. With global attention on AI fairness, such frameworks are becoming essential tools for ensuring equitable outcomes.