Abstract This research commentary explores how requirements engineering (RE) can contribute to achieving digital humanism in AI-enabled healthcare, ensuring that technological innovation is balanced with human values. Drawing on insights from a panel discussion at the REWBAH’25 (RE for Well-Being, Aging, and Health) workshop, we identify four key themes: the necessity of interdisciplinary collaboration, the nuances of cultural and individual differences, human-AI collaborative decision-making, and the challenge of balancing technological advancement with sustainability and emotional considerations. We argue that RE is well suited for addressing these issues because it brings together diverse stakeholder perspectives to define what systems should achieve and how they should be used. In this paper, we build on digital humanism principles, on RE-relevant frameworks for AI, and on the above themes to frame the role of RE in supporting human-centred healthcare. We highlight open challenges, and outline five promising research directions and related research questions to guide future research and practice in RE, aiming to ensure that AI-enabled healthcare systems better reflect the values of digital humanism.

This vision paper focuses on the mental health crisis impacting healthcare workers (HCWs), which exacerbated by the COVID-19 pandemic, leads to increased stress and psychological issues like burnout. Peer Support Programs (PSP) are a recognized intervention for mitigating these issues. These programs are increasingly being delivered virtually through Peer Support Systems (PSS) for increased convenience and accessibility. However, HCWs' perception of these systems results in fear of information sharing, perceived lack of safety, and low participation rate, which challenges these systems' ability to achieve their goals. In line with the rich body of research on the requirements and properties of trustworthy systems, we posit that increasing HCWs' trust in PSS could address these challenges. However, extant research focuses on objectively defined trustworthiness rather than perceptual trust because trustworthy requirements are viewed as more controllable and easier to operationalize. This study proposes a novel approach to elicit perceptual trust requirements by proposing a trust framework anchored in recognized trust theories from different disciplines that unpacks trust into its recognized types and their antecedents. This approach allows the identification of trust requirements beyond those already proposed for trustworthy systems, providing a strong foundation for improving the effectiveness of PSS for HCWs.

The Systems Modeling Language (SysML) is a popular and standardized UML profile for systems engineering applications. In addition to seven conventional UML diagram types, SysML supports requirement diagrams and tables that can be used to capture requirements, their attributes, and their relationships. However, several important concepts such as goals and contributions are not predefined in SysML, hindering the reasoning about tradeoffs and adaptation, especially in emerging socio-cyber-physical systems such as smart cities. In this paper, we provide a preliminary investigation of different ways of combining SysML with the User Requirements Notation (URN), a standard that focuses on the modeling and analysis of goals and scenarios. We argue that SysML and URN are complementary and synergistic, and that their combination enables new requirements modeling, analysis, and management opportunities for new types of systems. Examples of potential integration approaches are discussed, briefly assessed, and illustrated with existing tools for SysML, URN, and requirements management.