Rafia Inam

The role of Trustworthy AI / Explainable AI in Telecom industry

Rafia Inam is a Senior Project Manager at Ericsson Research in Trustworthy AI and Adjunct Professor at KTH. She has conducted research for Ericsson for the past nine years on 5G for industries, network slices, and network management; and AI for automation. She specializes in trustworthy AI, Explainable AI, risk assessment and mitigations using AI methods, and safety for cyber-physical systems; for telecom and collaborative robots. .  She won Ericsson Top Performance Competition 2021 on her work on AI for 5G network slice assurance, and was awarded multiple Ericsson Key Impact Awards. She has won best paper awards on her two papers. Rafia received her PhD in predictable real-time embedded software from Mälardalen University in 2014. She has co-authored 50+ refereed scientific publications and 55+ patent families and is a program committee member, referee, and guest editor for several international conferences and journals. 

Trust and reliance on modern telecom systems are widespread. However, the adoption of AI introduces new risks and necessitates countermeasures. Governments, companies, and standards bodies worldwide are recognizing the need for trustworthy AI systems. The presentation will discuss the importance of Trustworthy AI and Explainable AI for Telecom industry to enable customer trust; and how these techniques can support the industry to ensure correctness of AI models, provide transparency to different users, enable automation of telecom use cases, and help to identify and describe unexplained or new behavior of the models. The work presents different telecom examples using different explainable AI techniques.. 

Share
with

Subscribe to our Newsletter

Fourth Newsletter

Thales Alenia Space delivers cost-effective solutions for telecommunications, navigation, Earth observation, environmental management, exploration, science and orbital infrastructures. Governments

Francisco Fraile

AI-Powered Human-Centred Robot Interactions for Smart Manufacturing Francisco Fraile is an associate professor and senior

Serge Gratton

Multilevel Physics Informed Methods Serge Gratton is a Professor of Exceptional Class in Applied Mathematics