Trends Research and Advisory has released a new study that addresses the challenges associated with algorithmic discrimination in Artificial Intelligence. The study highlighted the need for a multifaceted approach to address the risks of bias in AI. The approach carefully examines the datasets used to train algorithms, and establish a sound legal and ethical governance framework. The study, entitled “Unbiased Artificial Intelligence: Tackling Algorithmic Discrimination”, was conducted by researcher Noor Al Mazrouei, Head of AI and Future Studies Department. It showed that artificial intelligence has transformed many aspects of our lives. However, the emergence of algorithmic discrimination in AI presents a significant challenge to fairness, equality, and societal justice. Algorithmic discrimination occurs when AI systems perpetuate and amplify biases and discriminatory practices, leading to unequal treatment and outcomes for different groups. The study sheds light on multiple aspects of unbiased AI and seeks to answer important questions, such as How have recent cases highlighted the issue of AI fairness? What technical challenges exist in developing unbiased algorithms? How do data collection and processing contribute to bias? What role do legal and ethical frameworks play in perpetuating or preventing bias? What methodologies are being developed to detect and mitigate bias? How can diversity in AI development teams reduce the risk of discrimination? What are the predictions for the future of unbiased AI and its impact on society? The study provides valuable information on how to create fair, transparent, and ethical AI systems. It emphasizes the need for a multifaceted approach that addresses the risk of bias at all stages of the development and use of AI, from careful examination of the data sets used to train these algorithms, to the development of sound legal and ethical governance framework. The study also highlights the importance of collective effort to develop artificial intelligence systems that serve humanity without prejudice or discrimination.