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The aim of this study is to examine the ethical conundrums that arise when artificial intelligence (AI) is used to drive decision-making processes in various industries, with a particular emphasis on the ethical implications of employing Big data for decision-making, and also to identify and analyze the ethical issues that arise in various industries at various steps of the algorithm development process due to the usage of AI and Big data in decision-making. Analysis at the data collection stage led to ethical grey areas in the development of machine learning algorithms using biased datasets. Multidisciplinary research and case studies from a range of industries, including healthcare, finance, marketing, and education, were employed in the study process. Some of the main subjects addressed were invasions of privacy, impartiality and inherent bias in decision-making algorithms, the openness and explainability of AI systems, accountability in automated decision-making and the ethical implications of data ownership and control and their effect on data subjects. This research adds to a better understanding of the ethical environment surrounding Big data and AI applications by combining insights from many businesses. It emphasizes how crucial it is to take proactive ethical considerations into account when designing, implementing and governing AI-driven technologies in order to guarantee their responsible, advantageous and most crucially, consensual integration across industries. The study concludes with the consequences and implications of entrusting AI with human lives directly and indirectly and the ultimate question regarding the future of algorithms which govern humans.

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