Dominik Kowald ^1,2* Sebastian Scher ^2,3 Viktoria Pammer-Schindler ¹ Peter Müllner ² Kerstin Waxnegger ² Lea Demelius ² Angela Fessl ^1,2 Maximilian Toller ² Inti Gabriel Mendoza Estrada ² Ilija Simic ² Vedran Sabol ² Andreas Truegler ^1,2,3 Eduardo Veas ^1,2 Roman Kern ^1,2 Tomislav Nad ⁴ Simone Kopeinik ^2*

• ¹ Graz University of Technology, Graz, Styria, Austria
• ² Know Center, Graz, Austria
• ³ University of Graz, Graz, Styria, Austria
• ⁴ SGS Digital Trust Services GmbH, Graz, Styria, Austria

Artificial intelligence (AI) technologies (re-)shape modern life, driving innovation in a wide range of sectors. However, some AI systems have yielded unexpected or undesirable outcomes or have been used in questionable manners. As a result, there has been a surge in public and academic discussions about aspects that AI systems must fulfill to be considered trustworthy. In this paper, we synthesize existing conceptualizations of trustworthy AI along six requirements: 1) human agency and oversight, 2) fairness and non-discrimination, 3) transparency and explainability, 4) robustness and accuracy, 5) privacy and security, and 6) accountability. For each one, we provide a definition, describe how it can be established and evaluated, and discuss requirement-specific research challenges. Finally, we conclude this analysis by identifying overarching research challenges across the requirements with respect to 1) interdisciplinary research, 2) conceptual clarity, 3) context-dependency, 4) dynamics in evolving systems, and 5) investigations in real-world contexts. Thus, this paper synthesizes and consolidates a wide-ranging and active discussion currently taking place in various academic sub-communities and public forums. It aims to serve as a reference for a broad audience and as a basis for future research directions.