Dublin Core The Dublin Core metadata element set is common to all Omeka records, including items, files, and collections. For more information see, http://dublincore.org/documents/dces/. Title A name given to the resource Faculty Publications Book Chapter Faculty Publications- Book Chapter Dublin Core The Dublin Core metadata element set is common to all Omeka records, including items, files, and collections. For more information see, http://dublincore.org/documents/dces/. Creator An entity primarily responsible for making the resource Deepti, A.R.; Manimekala, B.; Basith, Farzeen; Vivek, K.; Rajamanickam, Vijayanandh Title A name given to the resource Ethical AI in HR: Navigating the Data-driven Frontier Date A point or period of time associated with an event in the lifecycle of the resource 01-01-2025 Source A related resource from which the described resource is derived Innovate to Integrate: Data-Driven Management and TechStrat Fusion Unveiled;pp.19-36 Identifier An unambiguous reference to the resource within a given context <a href="https://doi.org/10.1108/978-1-83708-460-920251002" target="_blank" rel="noreferrer noopener">https://doi.org/10.1108/978-1-83708-460-920251002</a> <br /><br /><a href="https://www.scopus.com/pages/publications/105024282793?origin=resultslist" target="_blank" rel="noreferrer noopener">https://www.scopus.com/pages/publications/105024282793?origin=resultslist</a> Coverage The spatial or temporal topic of the resource, the spatial applicability of the resource, or the jurisdiction under which the resource is relevant Deepti A.R., Department of MCA, Acharya Institute of Graduate Studies, Bengaluru, India; Manimekala B., Department of Computer Science, Christ University, Bengaluru, India; Basith F., Department of MCA, Acharya Institute of Graduate Studies, Bengaluru, India; Vivek K., Department of MCA, Acharya Institute of Graduate Studies, Bengaluru, India; Rajamanickam V., Department of Computing and Information Technology, The University of the West Indies, West Indies, Jamaica Description An account of the resource The integration of artificial intelligence (AI) in human resources (HRs) presents significant opportunities while raising ethical dilemmas for an organisation. This chapter examines challenges in AI-enhanced HR concerning bias mitigation, data protection, transparency and governance through literature review, and real-life examples. Through a mixture of academic research and industry use cases including Amazon's AI hiring tool, HireVue video interview analysis, IBM Watson Career Coach and Unilever recruitment powered through AI study analyses AI impact on HR functions and approaches to address ethical concerns. This research offers an advanced methodological framework for ethical implementation of AI in HR which is based upon eight foundational components including interdisciplinary collaboration, bias minimisation, transparency and explainability, ethics-based privacy policies governance, continuous monitoring improving engagement with stakeholders, and adaptive trust-enhancing policy. The model weights a set of quantitative suggestion, new metrics such as Team Integration Score (TIS) for assessing cross-functional relationship success. Synthesis of multiple academic sources and case studies mentioned the chapter plan on responsible AI implementation in HR through stakeholder engagement, transparency practices, and review mechanisms. This approach balances technological advancement and ethical considerations within AI-driven HR processes. The significance of this chapter is to bring together academic sources and experts from the industry to provide a complete guide of integrating global best practices for implementing ethical AI. The proposed framework serves as a valuable tool for HR AI practitioners and researchers offering a structured approach to the ethical AI deployment while remaining adaptable to emerging challenges and opportunities in this rapidly growing area. 2026 by A.R. Deepti, B. Manimekala, Farzeen Basith, Vivek K. and Vijayanandh Rajamanickam. All rights reserved. Subject The topic of the resource Bias mitigation; Data privacy; Ethical AI governance; Explainable AI; HRs; Multidisciplinary collaboration Publisher An entity responsible for making the resource available Emerald Publishing Relation A related resource ISBN: 978-183708460-9; 978-183708461-6; Language A language of the resource English Type The nature or genre of the resource Book chapter Rights Information about rights held in and over the resource Restricted Access; Hardcopy may be available in the library Format The file format, physical medium, or dimensions of the resource online