Ascertaining trustworthiness of AI systems in telecommunications

With the rapid uptake of Artificial Intelligence (AI) in the Telecommunications (Telco) industry and the pivotal role AI is expected to play in future generation technologies (e.g., 5G, 5G Advanced and 6G), establishing the trustworthiness of AI used in Telco becomes critical. Trustworthy Artificial Intelligence (TWAI) guidelines need to be implemented to establish trust in AI-powered products and services by being compliant to these guidelines. This paper focuses on measuring compliance to such guidelines. This paper proposes a Large Language Model (LLM)-driven approach to measure TWAI compliance of multiple public AI code repositories using off-the-shelf LLMs. This paper proposes an LLM-based scanner for automated measurement of the trustworthiness of any AI system. The proposed solution measures and reports the level of compliance of an AI system. Results of the experiments demonstrate the feasibility of the proposed approached for the automated measurement of trustworthiness of AI systems.