Artificial Intelligence, Algorithm Biases and Racisms: The Dark Side of Algorithm Justice
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Abstract
This article aims to identify some negative externalities arising from the failure to comply with specific ethical standards in Artificial Intelligence (AI) models. This study highlights the importance of paying rigorous attention to the data used in building AI models, such as listing potential solutions to reduce the incidence of skewed algorithms and mitigate their harmful consequences. This article followed an exploratory descriptive methodology, addressing practical cases, and turned to bibliographic review as a technical procedure. The main finding is that skewed algorithms cause disastrous social consequences, violating fundamental rights and actings as catalyzers, increasing and perpetuating prejudice and segregation inherent to their society, thus contributing to the structural racism that permeates society and the criminal justice system.
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References
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