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Explainable and Ethical AI in Education and Healthcare: Bridging Trust, Transparency, and Innovation
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Author(s): Hewa Majeed Zangana (Duhok Polytechnic University, Iraq), Hakem Beitollahi (Soran University, Iraq), Marwan Omar (Illinois Institute of Technology, USA), Sabat Salih Muhamad (Soran University, Iraq), Firas Mahmood Mustafa (Duhok Polytechnic University, Iraq), Aquil Mirza Mohammed (Hong Kong Polytechnic University, Hong Kong)and Sharyar Wani (International Islamic University Malaysia, Malaysia)
Copyright: 2027
Pages: 27
Source title:
Encyclopedia of Modern Artificial Intelligence
Source Author(s)/Editor(s): Mehdi Khosrow-Pour, D.B.A. (Founding Editor-in-Chief, Information Resources Management Journal (IRMJ), USA)
DOI: 10.4018/406021
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Abstract
Artificial Intelligence (AI) is increasingly integrated into education and healthcare systems, offering transformative benefits such as personalized learning and precision medicine. However, the adoption of AI in these critical domains necessitates a strong emphasis on explainability and ethical considerations to ensure trust, accountability, and societal acceptance. This chapter explores the intersection of explainable AI (XAI) and ethical AI in education and healthcare, emphasizing how transparent and interpretable models can foster informed decision-making and equitable outcomes. It highlights current challenges, regulatory landscapes, and the role of interdisciplinary collaboration in developing AI systems that are both innovative and aligned with human values. By bridging trust, transparency, and innovation, the chapter provides a comprehensive framework for deploying responsible AI that benefits both learners and patients alike.
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