Citation :

Venkata Sathya Kumar Koppisetti, 2024. "The Role of Explainable AI in Building Trustworthy Machine Learning Systems" ESP International Journal of Advancements in Science & Technology (ESP-IJAST)  Volume 2, Issue 2: 16-21.

Abstract :

The field of Explainable Artificial Intelligence (XAI) is one of the pivotal phases that is under Intelligent AI and Machine Learning (ML) research and development. The absence of transparency and accountability has become a huge concern at some point, as algorithms are more frequently engaged in high-stakes tasks, e.g. medical diagnostics, finance, and judicial systems. This article seeks to establish the role of XAI in developing trustworthy ML motors, among others, highlighting the necessity for interpretability and transparency so that AI systems will not only be strong and powerful but also credible and ethical. We consider the techniques that supply the transparent nature of ML models and explore the current research advancements, realizing what sector practical application looks like. Consequently, we address these problems and suggest how to improve AI models in terms of risk avoidance while maintaining good performance. The results of our in-depth analysis, thus, expose the vital role played by XAI in clearly articulating human trust and comprehension in the context of AI.

References :

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[5] Venkata Sathya Kumar Koppisetti, "Automation of Vendor Invoice Process with OpenText Vendor Invoice Management ," International Journal of Computer Trends and Technology, vol. 71, no. 8, pp. 71-75, 2023. Crossref, https://doi.org/10.14445/22312803/IJCTT-V71I8P111

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[9] Venkata Sathya Kumar Koppisetti, 2024. "The Future of Remote Collaboration: Leveraging AR and VR for Teamwork" ESP International Journal of Advancements in Computational Technology (ESP-IJACT) Volume 2, Issue 1: 56-65.

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Keywords :

Explainable AI, Machine Learning, Interpretability, Transparency, Trustworthy AI, Accountability.