How HCI Adopts Service Design

Lee, Jung Joo; Yap, Christine Ee Ling; Roto, Virpi

doi:10.1145/3491102.3502128

Cited by 4 publications

(6 citation statements)

References 73 publications

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“…We then used another thirty minutes to have the participants discuss and co-construct an "ideal" journey map using a journey map template we offered, focusing on envisioning the opportunities to better navigate cross-functional collaboration. Note that, similar to prior HCI research using journey maps in their study design (e.g., [49]), our goal for the workshop was not to produce a perfect journey map as an artifact-based contribution of the research, but instead, we used the process of discussing and producing journey maps to elicit participants' perceived challenges, needs, and opportunities, as well as to scaffold the workshop discussions with specific details from participants' roles, teams, and organizations.…”

Section: Role or Job Titles Company Employee Number Gender Locationmentioning

confidence: 66%

“…After running the first two workshop sessions, we observed that our participants particularly needed to explore the opportunities they saw for ideal cross-functional collaboration. We thus revised our workshop protocol to provide a space for brainstorming desired cross-collaboration opportunities via "journey mapping" [49]a technique from user experience research that can be used to identify interactions between different stakeholders over time and support participants in moving from the current state to an ideal state. Before joining the workshops, participants watched a short tutorial video we prepared and filled out a journey map defining their teams' phases of AI development and the stakeholders involved in each phase, based on the nature of their team and organization.…”

Section: Stage One: Semi-structured Interviewsmentioning

confidence: 99%

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Investigating Practices and Opportunities for Cross-functional Collaboration around AI Fairness in Industry Practice

Deng

Yildirim

Chang

et al. 2023

2023 ACM Conference on Fairness, Accountability, and Transparency

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An emerging body of research indicates that ineffective cross-functional collaboration -the interdisciplinary work done by industry practitioners across roles -represents a major barrier to addressing issues of fairness in AI design and development. In this research, we sought to better understand practitioners' current practices and tactics to enact cross-functional collaboration for AI fairness, in order to identify opportunities to support more effective collaboration. We conducted a series of interviews and design workshops with 23 industry practitioners spanning various roles from 17 companies. We found that practitioners engaged in bridging work to overcome frictions in understanding, contextualization, and evaluation around AI fairness across roles. In addition, in organizational contexts with a lack of resources and incentives for fairness work, practitioners often piggybacked on existing requirements (e.g., for privacy assessments) and AI development norms (e.g., the use of quantitative evaluation metrics), although they worry that these tactics may be fundamentally compromised. Finally, we draw attention to the invisible labor that practitioners take on as part of this bridging and piggybacking work to enact interdisciplinary collaboration for fairness. We close by discussing opportunities for both FAccT researchers and AI practitioners to better support crossfunctional collaboration for fairness in the design and development of AI systems.

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Section: Role or Job Titles Company Employee Number Gender Locationmentioning

confidence: 66%

Section: Stage One: Semi-structured Interviewsmentioning

confidence: 99%

Investigating Practices and Opportunities for Cross-functional Collaboration around AI Fairness in Industry Practice

Deng

Yildirim

Chang

et al. 2023

2023 ACM Conference on Fairness, Accountability, and Transparency

View full text Add to dashboard Cite

show abstract

“…Service design considers yet a larger framework, as it broadens the focus from an individual user and takes into account also other stakeholders (Forlizzi, 2018). Lee et al (2022) have presented four dimensions for service design from interaction level to system level, which are 1) the customer experience, 2) backstage work, 3) collaborative network, and 4) ecosystem and infrastructure. The viewpoint of the service provider is important to take into account in order to enable creating services, which result in functional and seamless experiences for the end-user.…”

Section: Service Design As An Approachmentioning

confidence: 99%

“…Also, it is important to remember that services do not operate in isolation, but can be seen as part of a larger ecosystem and utilize some infrastructure. It has been pointed out that HCI oriented research on service design often focuses on the interaction dimension, whereas the system level dimension includes tools and methods that are more business-oriented (Lee et al, 2022).…”

Section: Service Design As An Approachmentioning

confidence: 99%

“…For instance, when designing a mobile sport coaching app for young athletes, in addition to the teenage mobile app user, the service design process takes into account stakeholders such as the sports coach, medical support, and the service platform handling the data (Häkkilä et al, 2016). As a consequence, the design process needs to consider a more complex contextual framework of users and a wider set of other stakeholders than traditionally considered in human-computer interaction design cases (Lee, Yap, & Roto, 2022).…”

Section: Introductionmentioning

confidence: 99%

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Service Design Methods for the Design of Smart Surfaces

Häkkilä

Löchtefeld

Brun

et al. 2023

Springer Series in Design and Innovation

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Smart environments, integrating different sensors and other technology solutions, are one of the key direction in which everyday spaces in buildings are expected to develop in the future. One aspect of smart environments includes large interactive surface areas, which are embedded to walls, tables or other furniture. This chapter introduces how service design methods have been applied in our research on smart surfaces, and discusses different design methods and their strengths in this context. Specifically, we present three service design cases, interactive wallpaper, a smart building infrastructure and a smart cafe table, and how the related use cases have been studied with service design methods. These three design cases are positioned at different maturity levels of the product development process, the interactive wallpaper and smart building representing early design concepts, and the interactive table a functional prototype.

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