Clinicians increasingly pay attention to Artificial Intelligence (AI) to improve the quality and timeliness of their services. There are converging opinions on the need for Explainable AI (XAI) in healthcare. However, prior work considers explanations as stationary entities with no account for the temporal dynamics of patient care. In this work, we involve 16 Idiopathic Pulmonary Fibrosis (IPF) clinicians from a European university medical centre and investigate their evolving uses and purposes for explainability throughout patient care. By applying a patient journey map for IPF, we elucidate clinicians' informational needs, how human agency and patient-specific conditions can influence the interaction with XAI systems, and the content, delivery, and relevance of explanations over time. We discuss implications for integrating XAI in clinical contexts and more broadly how explainability is defined and evaluated. Furthermore, we reflect on the role of medical education in addressing epistemic challenges related to AI literacy.@en

Designers are increasingly collaborating with data scientists to apply smart data technologies to understand large-scale user behavior during their design research. This is useful in specific impact domains with vulnerable users and unfamiliar contexts, such as healthcare design. Patient journey mapping is the most common design tool for developing and communicating patient-centred perspectives in healthcare design. However, creating a traditional patient journey map is labor intensive. Consequently, they often represent the experiences of a limited number of patients and, therefore, have limitations in including an extensive group patient experience. To overcome these challenges, we present a new data-driven and hybrid intelligent design approach that utilizes tens of thousands of online patient stories and machine-learning techniques through collaboration with data scientists. We set up two studies in the field of oncology and demonstrate that combining the two machine-learning techniques allows for quantifying the experiences of a wide range of patients, detecting relationships between co-occurring experiences within the journey, and detecting new design opportunities/directions. In these studies, designers gained a large-scale, yet qualitative and inspiring, understanding of a complex context in healthcare with reduced time and cost investments@en

The research question of this doctoral thesis is: What can be the future impact of design (activities) in digital health, given the rise of data collection and analysis technologies? I answered this question on three knowledge levels: design vision, knowledge-generating approach, and design tool. In Chapter 1, I envision design activities for the collective computing era (an upcoming modern computing era with complex systems of massive social interaction through various connected computing devices) that data collection and analysis technologies are a part of. Based on the literature review and informants’ interviews, I developed a design vision that demonstrates the changes posed in design activities (design tasks, processes, and the designer’s role) due to the upcoming collective computing era, and provides guidance for adopting the changes. Consequently, the vision proposes that design tasks in the collective computing era move towards designing ‘complex system(s)’ and testing these within ‘society as a lab’. The vision’s guidance states that designers can approach these tasks by addressing communities and engaging with their data. In terms of the design process, the vision claims the ‘coexploration’ of the design problem and solution spaces. To tackle such change, the guidance suggests designers: the flexible combination and analysis of mixed data, working on social forces at a system level, and developing through multiple soft launches with modular designs. Finally, the designer’s role becomes conducting an ‘accountable implementation.’ The vision recommends approaching accountable implementation by incorporating a transdisciplinary vision of the value and control of the design output....@en

In this study, we envision engineering design activities for collective computing, an upcoming era of complex systems of massive social interaction through a wide variety of connected computing devices. A literature review reveals how collective computing, compared to the previous eras of personal and ubiquitous computing, may lead to new design tasks and design processes, as well as new roles for designers. Based on this review, new design activities for the collective computing era are envisioned, and further revised in an interview study with 24 informants. The result is a vision for design in the collective computing era, with actionable guidance for designers in terms of a coherent set of new design activities proposed in relation to advances in computing.

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This paper aims to envision design activities –design task, design process, and designer–for the collective computing era, an upcomingdominance of applications where many people interact with each other through many computing devices(Abowd, 2016). To achieve this aim, thetypical design activities over the last two computing eras, personal and ubiquitous, are studied through a literature review. Based on the activities shift discovered there, new design activities for collective computing are envisioned. This study urgesdesigners to change the way to work with user-data: from referring the small but in-depth ethnographical user-centeredliving-lab data (during the ubiquitous computing era), to create an understanding about both the individual user and the society or crowd as a whole(collective computing era). These different types of data provide designers with a rich understanding on the usersin their contexts, both as individual and community levels. Also, the design process that authors envision is a process of co-exploration (merge of problem exploration and solution delivery), and co-evolution (the constant reflection back and forth with exchange of information) of design problem and solution spaces. Moreover, the designersin collective computing erahave to take ethical and privacyissues into account. They have to create plans for dealing with the uncontrollability of the data generated and uncertainty about the social impact of the design that come with it. This research cantrigger the designers to innovate and remodel their workat the forefront of new computing technologies.@en