The development and deployment of AI systems require a strong commitment to reliability, safety, security, ethics, and social responsibility. This paper identifies key research issues and challenges for trustworthy AI based on practical experiences from ongoing projects at Mälardalen University (MDU), Sweden, in mobility, transportation, and healthcare domains. It highlights critical technical components including fairness, safety, transparency, explainability, accountability, rigorous testing, verification, and a human-centric approach, providing guidance for the design and deployment of AI systems aligned with state-of-the-art practices. Published: 6 October 2024 | Version v1

Link/DOI: 10.5281/zenodo.13895825