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Overviewing Biases in Generative AI-Powered Models in the Arabic Language: AI Fairness for Sustainable Future
Abstract
Natural Language Processing (NLP) is an emerging field often integrated into Artificial Intelligence (AI) technologies. NLP has significantly advanced, leading to the widespread use of generative AI-powered (Gen-AI) models across various domains. However, while Gen-AI systems have been successfully implemented in several languages, AI-based language models still face considerable challenges and shortcomings, including generating biases in sensitive languages like Arabic. Therefore, the primary objective of this chapter is to provide an overview of the biases in Gen-AI-powered models in the context of the Arabic language, exploring the sources of these biases, their implications, and potential strategies for mitigation. The biases in Gen-AI-powered models underscore the need for ongoing research and development to create more equitable and accurate AI systems. By understanding the origins and implications of these biases and implementing effective mitigation strategies, we can work towards AI models that better serve diverse linguistic communities.
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