This book evaluates algorithmic models significantly exacerbating discrimination, suggesting improvements in algorithmic governance.
Kathy O' Neil' s Weapons of Math Destruction exposes the systemic risks concealed within the widespread application of big data algorithmic models in contemporary society. The book critically introduces the core concept of “Weapons of Math Destruction” (WMDs) , characterized by their opacity, scale, and destructive potential. Through meticulous case analyses, the author demonstrates how these algorithms, operating under the guise of “efficiency” and “objectivity, ” leverage data biases, flaws in model design, and feedback loop mechanisms. This results in the entrenchment of discrimination, harm inflicted upon vulnerable groups, exacerbation of social injustice, and even the erosion of democratic foundations. The core value of this work lies in its incisive critical perspective, systematic reflection on algorithmic ethics, and its cautionary warning urging the advancement of algorithmic governance and fairness.
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Jimin Zhang (2025) studied this question.
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