Two new papers by IMU researchers on Trustworthy AI and AutoML applications published in the journal “Intelligent Decision Technologies”.

The first paper entitled “Exploring the landscape of trustworthy artificial intelligence: Status and challenges“ reviews the landscape of research on supporting the trustworthiness of AI systems. We commence with an examination of the characteristics inherent in trustworthy AI, along with the corresponding principles and standards associated with them. We then examine the methods and tools that are available to designers and developers in their quest to operationalize trusted AI systems. Finally, we outline research challenges towards end-to-end engineering of trustworthy AI by-design.

The second paper entitled “An AutoML-based approach for automatic traffic incident detection in smart cities“ propose and apply an AutoML-based methodology for traffic incident detection and compare it with state-ofthe-art ML approaches. Our approach integrates data preprocessing with AutoML, and uses Tree-based Pipeline Optimization Tool (TPOT) to refine the process from raw data to prediction. We have tested the efficiency of our approach in two major European cities, Athens and Antwerp. Finally, we present the limitations of our work and outline recommendations for application of AutoML in the incident detection task and potentially in other domains.