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In an era where data profoundly influences decision-making across various sectors, this comprehensive review critically examines the evolving landscape of data science ethics, particularly focusing on the interplay between technological advancements and ethical standards. The study aims to investigate and synthesize current ethical practices and challenges in modern data collection and analysis, tracing the evolution of ethical standards in data science, understanding the significance of ethical considerations in contemporary data practices, and exploring the development of global regulatory and ethical frameworks. The paper encompasses a systematic literature review, focusing on core ethical principles in data collection and analytical processes, the roles of consent and privacy, the complexities introduced by big data, and the intricacies of ethical frameworks across different regions. It bridges the research gap in data ethics by providing insights into practical ethical frameworks and instructional models, guiding researchers, policymakers, and practitioners in ethical data handling. The study concludes that ethical considerations are integral to data science practices and contribute significantly to societal well-being. It recommends enhanced ethical education in data science, development of inclusive ethical frameworks, strengthening regulatory oversight, and promoting public engagement in data ethics discussions. These steps are essential for ensuring responsible and beneficial use of data in an ethically complex landscape. Keywords: Data Ethics, Data Science, Ethical Standards, Privacy, Consent, Regulatory.
Okorie et al. (Tue,) studied this question.