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Auditing Algorithmic Risk: A Critical Examination of Potential Threats #AlgorithmicRiskAudit

Auditing Algorithmic Risk

The content discusses various references related to ethics, fairness, and discrimination in artificial intelligence and algorithmic decision-making. It includes references to the Ethical Matrix framework, explainable fairness in regulatory algorithms, racial bias in mortgage lending, credit scores among different ethnicities, adding rent payments to credit reports, the four-fifths rule in employment selection, regulations on unfair discrimination in insurance practices, and evaluation of language models. Additionally, it mentions instances where AI chatbots have faced criticism for focusing on harmful topics like weight loss and providing incorrect advice on legal and tax matters. The content emphasizes the importance of considering ethical implications and stakeholder concerns in the development and deployment of AI technologies.

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Source link: https://sloanreview.mit.edu/article/auditing-algorithmic-risk/

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