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              <text>Exploring the Balance Between Automated Decision-Making and Human Judgment in Managerial Contexts</text>
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              <text>Artificial intelligence; Machine learning; Managerial decision-making</text>
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              <text>The study delves into the dynamic and evolving discussion surrounding the balance between automated and human judgment within the realm of managerial decision-making. The primary objective of this research is to gain insight into how AI is evolving to mitigate ethical biases that are inherent in managerial decision-making. To accomplish this goal, the study adopts a theoretical approach, supported by qualitative analysis through an extensive review of existing literature. By systematically investigating AI techniques for managerial decision-making, the research contributes to a broader understanding of how AI is progressing to promote ethically sound managerial decisions in future. The findings from this study are pertinent to business leaders, policymakers, and researchers, offering guidance as they navigate the intricate relationship between automation and human judgment in todays managerial landscape.  The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2024.</text>
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              <text>Alex V.P.; Anirudh H.V.; Siby A.</text>
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              <text>Lecture Notes in Networks and Systems, Vol-946, pp. 159-167.</text>
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              <text>&lt;a href="https://doi.org/10.1007/978-981-97-1323-3_13" target="_blank" rel="noreferrer noopener"&gt;https://doi.org/10.1007/978-981-97-1323-3_13&lt;/a&gt;
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              <text>ISSN: 23673370; ISBN: 978-981971322-6</text>
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              <text>Alex V.P., CHRIST (Deemed to be University), Bengaluru, India; Anirudh H.V., CHRIST (Deemed to be University), Bengaluru, India; Siby A., CHRIST (Deemed to be University), Bengaluru, India</text>
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