Unveiling explainability in artificial intelligence: a step to-‎wards transparent AI

  • Authors

    • Ridwan Boya Marqas Computer Engineering
    • Saman M. Almufti Reasearcher at Computer Science dept., Knowledge University, Erbil, Iraq
    • Rezhna Azad Yusif Computer Dept., Knowledge University, Erbil, Iraq
    2025-01-31
    https://doi.org/10.14419/f2agrs86
  • Explainable AI; Transparency; Post-Hoc Explanations; Causality-Based Explanations; Neuro-Symbolic AI; Ethics In AI; AI Accountability; ‎Trustworthy AI; AI Interpretability; Autonomous Systems‎.
  • Abstract

    Explainability in artificial intelligence (AI) is an essential factor for building transparent, trustworthy, and ethical systems, particularly in ‎high-stakes domains such as healthcare, finance, justice, and autonomous systems. This study examines the foundations of AI explainability, ‎its critical role in fostering trust, and the current methodologies used to interpret AI models, such as post-hoc techniques, intrinsically inter-‎pretable models, and hybrid approaches. Despite these advancements, challenges persist, including trade-offs between accuracy and inter-‎pretability, scalability, ethical risks, and transparency gaps. The paper explores emerging trends like causality-based explanations, neuro-‎symbolic AI, and personalized frameworks, while emphasizing the integration of ethics and the need for automation in explainability. Future ‎directions stress the importance of collaboration among researchers, practitioners, and policymakers to establish industry standards and ‎regulations, ensuring that AI systems align with societal values and expectations.

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  • How to Cite

    Boya Marqas, R., Almufti, S. M. ., & Azad Yusif , R. . (2025). Unveiling explainability in artificial intelligence: a step to-‎wards transparent AI. International Journal of Scientific World, 11(1), 13-20. https://doi.org/10.14419/f2agrs86