Research Issues and Challenges in the Computational Development of Trustworthy AI

The development and deployment of AI systems
necessitate a steadfast commitment to reliability, safety,
security, ethics, and social responsibility. This paper introduces
key research issues and challenges for trustworthy AI based on
our experience working on several ongoing research projects at
Mälardalen University (MDU), Sweden, which considers
practical, real-world scenarios from the mobility,
transportation, and healthcare domains. Our observations
have highlighted several critical technical components that
underpin trustworthy AI. These components include fairness,
safety, transparency, explainability, accountability, rigorous
testing, verification, and a human-centric approach to AI.
Notably, these elements align closely with the current state-ofthe-
art practices in the field.