The democratic and emancipatory principles underpinning Participatory Design (PD) set PD methodology apart from other user-oriented design methodologies associated with Human-Computer Interaction. In turning PD principles into practice, PD facilitators play a vital role. However, at present, there is a lack of understanding regarding skills relevant to enacting the role. To address this issue, we present the results from an interview study involving fourteen respondents with considerable PD facilitation experience. The analysis of the interviews uncovered six facilitation skills of perceived relevance: openness, patience, empathy, attentiveness, responsiveness, and adaptiveness. The significance of each skill, as expressed by respondents, is accounted for. We further discuss the composition of skills in the derived skill set, possible implications of missing skills, and how the findings complement relevant existing work. Drawing on the findings, the paper offers an empirically based qualitative understanding of what constitutes skillful PD facilitation.
There is a growing interest among researchers to define and promote equitable practices in participatory design (PD). Our work contributes to this research by exploring the values of facilitators with varying professional backgrounds. We conducted interviews with 15 facilitators who are novice in their design background but who possess a range of domain expertise and community memberships. The interviews focused on their experiences leading a series of PD sessions with rural educators, community college instructors, community organization members, and rural librarians. We identified five key values that facilitators saw as fundamental to their PD practice: community and shared culture, co-production of knowledge, respect and non-hierarchy, trust building, and creating practical and sustainable solutions. This study demonstrates how values that are core to PD are refracted through novice facilitators' professional expertise and community membership. We offer two strategies for novice facilitators as they strive to practice more equitable PD.
Understanding how different user groups interact and perceive material selection for interactive markers in mobile augmented reality (MAR) games is essential for effective design. This study uses a qualitative approach, incorporating interviews and workshops to examine the preferences and behaviours of designers (N=6) and children (N=8). Designers highlighted the importance of using versatile and environmentally sustainable materials that can be customised for various games. Meanwhile, children’s interactions with these materials revealed challenges such as decision-making pressure and reliance on peer collaboration to navigate unfamiliar materials. The study identified five critical considerations for selecting materials: simplification, customisation, sustainability, balanced creativity, and collaboration. Our results show that while designers prioritise creative potential, user engagement is influenced by material ease and collaboration. This study provides key insights into the design considerations for MAR games, suggesting aligning designer expectations with actual user behaviour for creating successful and immersive MAR experiences.
Health-related artificial intelligence (health AI) systems are being rapidly created, largely without input from racially minoritized communities who experience persistent health inequities and stand to be negatively affected if these systems are poorly designed. Addressing this problematic trend, we critically review prior work focused on the participatory design of health AI innovations (participatory AI research), surfacing eight gaps in this work that inhibit racial health equity and provide strategies for addressing these gaps. Our strategies emphasize that “participation” in design must go beyond typical focus areas of data collection, annotation, and application co-design, to also include co-generating overarching health AI agendas and policies. Further, participatory AI methods must prioritize community-centered design that supports collaborative learning around health equity and AI, addresses root causes of inequity and AI stakeholder power dynamics, centers relationalism and emotion, supports flourishing, and facilitates longitudinal design. These strategies will help catalyze research that advances racial health equity.
Participatory Design (PD) has become increasingly prevalent in Human-Computer Interaction (HCI) research. However, there remains a lack of comprehensive understanding of how PD has been used by HCI scholars. To bridge this gap, we sampled PD application cases (N = 185) from the SIGCHI conferences {over the past decade} and examined these cases through the dimensions of application features (e.g., contexts and functions of PD) and PD principles (e.g., its political commitment and mutual learning principle). Our analysis reveals the various ways PD has been applied in HCI and how its core features have been or have not been manifested in these cases. Based on these findings, we reflect on the conceptual understanding of PD within the HCI community and discuss potential misconceptions. Ultimately, we hope this work can serve as a useful reference for HCI researchers and beyond who are interested in incorporating PD into their design and research practices.
In light of inherent trade-offs regarding fairness, privacy, interpretability and performance, as well as normative questions, the machine learning (ML) pipeline needs to be made accessible for public input, critical reflection and engagement of diverse stakeholders.
In this work, we introduce a participatory approach to gather input from the general public on the design of an ML pipeline. We show how people's input can be used to navigate and constrain the multiverse of decisions during both model development and evaluation. We highlight that central design decisions should be democratized rather than "optimized" to acknowledge their critical impact on the system's output downstream. We describe the iterative development of our approach and its exemplary implementation on a citizen science platform. Our results demonstrate how public participation can inform critical design decisions along the model-building pipeline and combat widespread lazy data practices.
Community and organizational policies are typically designed in a top-down, centralized fashion, with limited input from impacted stakeholders. This can result in policies that are misaligned with community needs or perceived as illegitimate. How can we support more collaborative, participatory approaches to policy design? In this paper, we present PolicyCraft, a system that structures collaborative policy design through case-grounded deliberation. Building on past research that highlights the value of concrete cases in establishing common ground, PolicyCraft supports users in collaboratively proposing, critiquing, and revising policies through discussion and voting on cases. A field study across two university courses showed that students using PolicyCraft reached greater consensus and developed better-supported course policies, compared with those using a baseline system that did not scaffold their use of concrete cases. Reflecting on our findings, we discuss opportunities for future HCI systems to help groups more effectively bridge between abstract policies and concrete cases.