“…Advances in digital technology, along with debates about biased algorithms and ethical and regulatory challenges of autonomous systems (Baker & Hawn, 2022 ; Coeckelbergh, 2019 ) underscore the fact that management of AI is as much a social and political issue rather than exclusively an engineering challenge (Coeckelbergh, 2022 ; Nabavi, 2019 ). This realization has caused policy, research, and industry actors to take non-technical aspects of AI into account, which can be seen in the increased awareness of ‘responsibility’ in AI systems (Constantinescu et al, 2021 ), defined broadly as including principles such as transparency, fairness, and accountability in creating AI technologies that meet legal requirements and societal expectation, norms and values. Common concerns in this area include privacy, accountability, safety and security, transparency and explainability, fairness and non-discrimination, human control of technology, professional responsibility, and promotion of human values (Fjeld et al, 2020 ).…”