IQP CS TS2 Exploring Inclusive Reasoning in AIPublic Deposited
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The advent of artificial intelligence has ushered in a fourth revolution in human cognitive abilities. However, despite the enormous potential, AI systems can exhibit algorithmic biases that can lead to unfair competition, algorithmic discrimination, and abuse. These biases come from different sources, including subjective factors and cognitive biases of algorithm designers, data bias, and the opacity of the algorithm. In addition, AI algorithms are not value-neutral; they reflect the values of their creators. To address algorithmic bias, while going through the technical aspects of optimizing algorithms, we must also hold AI algorithm designers and users accountable for their actions, ensure the accuracy of data mining, and improve the transparency and interpretability of algorithms.
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