Explainability and Transparency in Artificial Intelligence: Ethical Imperatives and Practical Challenges

Vijayalaxmi Methuku; Sharath Chandra Kondaparthy; Direesh Reddy Aunugu

doi:10.22161/eec.84.2

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Explainability and Transparency in Artificial Intelligence: Ethical Imperatives and Practical Challenges

Vijayalaxmi Methuku , Sharath Chandra Kondaparthy , Direesh Reddy Aunugu

International Journal of Electrical, Electronics and Computers (IJECC), Vol-8,Issue-4, July - August 2023, Pages 7-12, 10.22161/eec.84.2

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Article Info: Received: 30 Jun 2023; Accepted:27 Jul 2023; Date of Publication: 02 Aug 2023

Abstract:

Artificial Intelligence (AI) is increasingly embedded in high-stakes domains such as healthcare, finance, and law enforcement, where opaque decision-making raises significant ethical concerns. Among the core challenges in AI ethics are explainability and transparency—key to fostering trust, accountability, and fairness in algorithmic systems. This review explores the ethical foundations of explainable AI (XAI), surveys leading technical approaches such as model-agnostic interpretability techniques and post-hoc explanation methods and examines their inherent limitations and trade-offs. A real-world case study from the healthcare sector highlights the critical consequences of deploying non-transparent AI models in clinical decision-making. The article also discusses emerging regulatory frameworks and underscores the need for interdisciplinary collaboration to address the evolving ethical landscape. The review concludes with recommendations for aligning technical innovation with ethical imperatives through responsible design and governance.

Keywords:

Explainable AI (XAI), Transparency, Ethical AI, Interpretability, Regulatory Frameworks

References:

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Explainability and Transparency in Artificial Intelligence: Ethical Imperatives and Practical Challenges

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