What question did this study set out to answer?

This research aims to establish open-source reference architectures that enhance transparency in AI systems across different industries.

May 30, 2026Open Access

Cross-Industry AI Transparency Stacks: Open Source Reference Architectures for XAI

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This research aims to establish open-source reference architectures that enhance transparency in AI systems across different industries.
Development of cross-industry AI transparency stacks
Analysis of current frameworks for explainability
Creation of a reference model for XAI implementation
Proposes three distinct open source reference architectures for AI transparency stacks.
Demonstrates improved model interpretability and user trust in AI systems.
Highlights the potential for ethical AI application across diverse sectors.

Implication

Research article showcases open source architectures for AI transparency in various industries, highlighting their importance for ethical AI practices.

Abstract

Research article: Cross-Industry AI Transparency Stacks: Open Source Reference Architectures for XAI

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Cite This Study

Ivchenko et al. (2026) studied this question.

synapsesocial.com/papers/6a1a81bf0307b78509433859 https://doi.org/10.5281/zenodo.20420849

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Implication

Research article showcases open source architectures for AI transparency in various industries, highlighting their importance for ethical AI practices.

Abstract

Research article: Cross-Industry AI Transparency Stacks: Open Source Reference Architectures for XAI

Cross-Industry AI Transparency Stacks: Open Source Reference Architectures for XAI

Key Points

Implication

Abstract

Discussion

Cite This Study

Cross-Industry AI Transparency Stacks: Open Source Reference Architectures for XAI

Key Points

Implication

Abstract

Discussion

Cite This Study

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