Saudi Data & AI Authority Issues Guide to Tackle AI Bias

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

The guide examines how bias can emerge throughout the development of AI systems, from data collection and model training to deployment and interpretation. It also outlines the potential societal impacts of biased systems and offers practical strategies to help organisations identify and mitigate these risks.

According to SDAIA, the rapid adoption of artificial intelligence across sectors including healthcare, education and justice has increased the need to address bias at every stage of AI development. The authority warned that unchecked bias can reduce the effectiveness of AI systems, reinforce discriminatory outcomes, damage institutional reputations and expose organisations to legal liability and consumer complaints.

The publication highlights several sources of bias, including training data that does not adequately represent different population groups, algorithms that unintentionally favour certain characteristics and assumptions made during data analysis. It cites AI-powered recruitment tools that may prioritise applicants from elite educational backgrounds over equally qualified candidates from less privileged institutions as one example of how bias can emerge in practice.

The guide builds on SDAIA's previous work on responsible artificial intelligence, including its AI Ethics Principles, Generative AI Principles, AI Adoption Framework, and the study 'Bias in Artificial Intelligence Systems: Challenges and Solutions'. The authority said it will continue developing guidance and national capabilities to support the responsible adoption of AI and strengthen digital innovation.