Despite the growing consensus that stakeholders affected by AI systems should participate
in their design, enormous variation and implicit disagreements exist among current …

Ethics, explainability, responsibility, and accountability are important concepts for
questioning the societal impacts of artificial intelligence and machine learning (AI), but are …

HCI research has explored AI as a design material, suggesting that designers can envision
AI's design opportunities to improve UX. Recent research claimed that enterprise …

Child welfare agencies across the United States are turning to data-driven predictive
technologies (commonly called predictive analytics) which use government administrative …

AI is becoming increasingly integrated in common technologies, which suggests that
learning experiences for audiences seeking a" casual" understanding of AI-ie understanding …

There is a growing consensus in HCI and AI research that the design of AI systems needs to
engage and empower stakeholders who will be affected by AI. However, the manner in …

Despite growing calls for participation in AI design, there are to date few empirical studies of
what these processes look like and how they can be structured for meaningful engagement …

Decolonizing discourses teach us that we need to move away from the universalizing 'grand
narratives' of knowledge production and focus on contextualizing diverse and situated …

Engaging end user groups with machine learning (ML) models can help align the design of
predictive systems with people's needs and expectations. We present a co-design study …

Participatory Design, User-Centered Design, People Centered Design, User-oriented
Design, Human-Centered Design, Contextual Design, Co-design, Cooperative Design …