THE INTERSECTION BETWEEN ARTIFICIAL INTELLIGENCE (AI), COMPLEX THINKING AND BIAS AUDIT METHODOLOGY
Abstract
This paper explores the intersection between artificial intelligence (AI), complex thinking, and bias auditing methodology, focusing on how these tools can ensure ethical and equitable AI algorithm development. The study highlights the sources of bias in AI models, detection methods, and mitigation strategies aimed at improving the fairness and justice of these systems. Additionally, the importance of complex thinking is discussed in understanding the multiple dimensions and interconnections of algorithmic biases, and how bias auditing plays a crucial role in identifying and correcting these injustices
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