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This survey aims to explore the importance of explainable artificial intelligence (XAI) in building trust and transparency within AI systems.

January 1, 2018IEEE AccessOpen Access

Peeking Inside the Black-Box: A Survey on Explainable Artificial Intelligence (XAI)

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This survey aims to explore the importance of explainable artificial intelligence (XAI) in building trust and transparency within AI systems.
Reviewed key literature in the field of explainable AI (XAI)
Discussed existing approaches to understanding AI transparency
Analyzed trends and research trajectories in XAI
Identified major challenges related to the black-box nature of AI systems
Highlighted the significance of trust and transparency for widespread AI adoption
Outlined potential future directions for XAI research

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Survey explores explainable AI, aiming to improve trust and transparency in AI systems, indicating its critical importance.

Adadi et al. (2018) studied this question.

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