Trustworthy Deep Learning in 6G-Enabled Mass Autonomy: From Concept to Quality-of-Trust Key Performance Indicators

Mass autonomy promises to revolutionize a wide range of engineering, service, and mobility industries. Coordinating complex communication among hyperdense autonomous agents requires new artificial intelligence (AI)-enabled orchestration of wireless communication services beyond 5G and 6G mobile networks. In particular, safety and mission-critical tasks will legally require both transparent AI decision processes and quantifiable quality-of-trust (QoT) metrics for a range of human end users (consumer, engineer, and legal). The authors outline the concept of trustworthy autonomy for 6G, including essential elements such as how explainable AI (XAI) can generate the qualitative and quantitative modalities of trust. The authors also provide XAI test protocols for integration with radio resource management and associated key performance indicators (KPIs) for trust. The research directions proposed will enable researchers to start testing existing AI optimization algorithms and develop new ones with the view that trust and transparency should be built in from the design through the testing phase.

• Record URL:
  • https://doi.org/10.1109/MVT.2020.3017181
• Availability:
  • Find a library where document is available. Order URL: http://worldcat.org/issn/15566072
• Supplemental Notes:
  • Copyright © 2020, IEEE.
• Authors:
  • Li, Chen
  • 0009-0001-6129-0481
  • Guo, Weisi
  • Sun, Schyler
  • Al-Rubaye, Saba
  • Tsourdos, Antonios
• Publication Date: 2020-12

Language

• English

Media Info

• Media Type: Web
• Features: References;
• Pagination: pp 112-121
• Serial:
  • IEEE Vehicular Technology Magazine
  • Volume: 15
  • Issue Number: 4
  • Publisher: Institute of Electrical and Electronics Engineers (IEEE)
  • ISSN: 1556-6072
  • Serial URL: http://ieeexplore.ieee.org/xpl/tocresult.jsp?isnumber=34840

Subject/Index Terms

• TRT Terms: Artificial intelligence; Design; Intelligent agents; Machine learning; Performance measurement; Psychological trust; Testing; Wireless communication systems
• Subject Areas: Data and Information Technology; Transportation (General); Vehicles and Equipment;

Filing Info

• Accession Number: 01761170
• Record Type: Publication
• Files: TRIS
• Created Date: Dec 23 2020 10:03AM