Lifecycle Management of Trustworthy AI Models in 6G Networks: the Reason Approach

Artificial intelligence (AI) is expected to play a key role in 6G networks, including optimizing system management, operation, and evolution. This requires systematic lifecycle management of AI models, ensuring their impact on services and stakeholders is continuously monitored. While current 6G initiatives introduce AI, they often fall short in addressing end-to-end intelligence and crucial aspects like trust, transparency, privacy, and verifiability. Trustworthy AI is vital, especially for critical infrastructures like 6G. This article introduces the REASON approach for holistically addressing AI's native integration and trustworthiness in future 6G networks. The approach comprises AI orchestration (AIO) for model lifecycle management, cognition (COG) for performance evaluation and explanation, and AI monitoring (AIM) for tracking and feedback. Digital twin (DT) technology is leveraged to facilitate real-time monitoring and scenario testing, which are essential for AIO, COG, and AIM. We demonstrate this approach through an AI-enabled xAPP use case, leveraging a DT platform to validate, explain, and deploy trustworthy AI models.

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Publication Details

Journal
IEEE Wireless Communications
Published
2025-03-29
DOI
https://doi.org/10.1109/mwc.001.2400288
Citations
4
Primary Topic
Adversarial Robustness in Machine Learning
Type
article
Field-Weighted Citation Impact
9.92

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article

Lifecycle Management of Trustworthy AI Models in 6G Networks: the Reason Approach

Yulei Wu, Andrea Tassi, Xenofon Vasilakos, Darryl Hond et al.
4 citations
IEEE Wireless Communications
Adversarial Robustness in Machine Learning
9.92
article

Lifecycle Management of Trustworthy AI Models in 6G Networks: the Reason Approach

Yulei Wu, Andrea Tassi, Xenofon Vasilakos, Darryl Hond, Dimitra Simeonidou, Daniel Warren, Maqsood Mahmud, Xueqing Zhou, Juan Marcelo Parra-Ullauri, Shadi Moazzeni, Renjith Baby, Gabriele Incorvaia, Rasheed Hussain, Hamid Asgari
article en
4 citations

Abstract

Artificial intelligence (AI) is expected to play a key role in 6G networks, including optimizing system management, operation, and evolution. This requires systematic lifecycle management of AI models, ensuring their impact on services and stakeholders is continuously monitored. While current 6G initiatives introduce AI, they often fall short in addressing end-to-end intelligence and crucial aspects like trust, transparency, privacy, and verifiability. Trustworthy AI is vital, especially for critical infrastructures like 6G. This article introduces the REASON approach for holistically addressing AI's native integration and trustworthiness in future 6G networks. The approach comprises AI orchestration (AIO) for model lifecycle management, cognition (COG) for performance evaluation and explanation, and AI monitoring (AIM) for tracking and feedback. Digital twin (DT) technology is leveraged to facilitate real-time monitoring and scenario testing, which are essential for AIO, COG, and AIM. We demonstrate this approach through an AI-enabled xAPP use case, leveraging a DT platform to validate, explain, and deploy trustworthy AI models.

IEEE Wireless CommunicationsVol. 32(2)
University of Bristol (GB), Thales (United Kingdom) (GB), Samsung (United Kingdom) (GB), Digital Catapult (United Kingdom) (GB)
Government of the United Kingdom
Openalex Percentile: Top 2%
Adversarial Robustness in Machine Learning
9.92
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