Integration of Explainable AI in Microservices Systems Operating on Multi-Cloud Digital Infrastructure for Regulatory Compliance and Transparency
Keywords:
Explainable AI, microservices, multi-cloud, regulatory compliance, transparency, XAI, distributed systems, AI governance, containerizationAbstract
In the context of increasing regulatory pressures and rising expectations for ethical artificial intelligence, this paper explores the integration of Explainable AI (XAI) within microservices-based architectures deployed across multi-cloud environments. Emphasizing compliance and transparency, the work identifies the challenges of black-box AI in distributed systems and evaluates frameworks that combine explainability with scalability. Using architectural models and deployment flowcharts, we discuss how XAI can facilitate governance, ensure legal accountability, and align AI decision-making with ethical standards in financial, healthcare, and public sector domains..
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Copyright (c) 2020 García Lorca Vallejo (Author)
This work is licensed under a Creative Commons Attribution-NonCommercial 4.0 International License.
