Ethical Considerations in Data Analytics: Privacy, Bias, and Accountability
Abstract
As data analytics becomes increasingly pervasive, ethical concerns surrounding data usage have come to the forefront. This review paper examines the ethical challenges associated with data analytics, including issues of data privacy, algorithmic bias, and accountability. It explores frameworks and regulations such as GDPR and CCPA, as well as techniques for mitigating bias in machine learning models. The paper also discusses the role of ethical AI in ensuring fairness and transparency, offering recommendations for organizations to adopt responsible data practices.
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