Emphasizing problem formulation in AI literacy activities with children is vital, yet we lack empirical studies on their structure and affordances. We propose that participatory design involving teachable machines facilitates problem formulation activities. To test this, we integrated problem reduction heuristics into storyboarding and invited a university-based intergenerational design team of 10 children (ages 8-13) and 9 adults to co-design a teachable machine. We find that children draw from personal experiences when formulating AI problems; they assume voice and video capabilities, explore diverse machine learning approaches, and plan for error handling. Their ideas promote human involvement in AI, though some are drawn to more autonomous systems. Their designs prioritize values like capability, logic, helpfulness, responsibility, and obedience, and a preference for a comfortable life, family security, inner harmony, and excitement as end-states. We conclude by discussing how these results can inform the design of future participatory AI activities.

Societal implications of technology are often considered after public deployment. However, broader impacts ought to be considered during the onset and throughout development to reduce potential for harmful uses, biases, and exclusions. There is a need for tools and frameworks that help technologists become more aware of broader contexts of their work and engage in more responsible and inclusive practices. In this paper, we introduce an online card tool containing questions to scaffold critical reflection about projects’ impacts on society, business, and research. We present the iterative design of the Responsible & Inclusive Cards and findings from five workshops (n=21 participants) with teams distributed across a multinational technology corporation, as well as interviews with people with disabilities to assess gameplay and mental models. We found the tool promoted discussions about challenging topics, reduced power gaps through democratized turn-taking, and enabled participants to identify concrete areas to improve their practice.

Participatory Design (PD) aims to promote inclusivity by involving users throughout the design process. However, Human-Computer Interaction (HCI) and social computing research have pointed to instances where PD as practiced can, paradoxically, be exclusive. We aim to understand some of the challenges that could lead to exclusivity in order to design more inclusive PD practices. To investigate this, we conducted interviews with ten expert PD practitioners based in the Global North whose focus is on inclusion. Synthesizing practitioners' accounts, we advance understandings of challenges surrounding: 1) instantiating shared spaces that empower partners; 2) developing common ground among stakeholders; and 3) balancing funding needs with open-ended PD. We contribute theoretical and empirical insights into these challenges and close by articulating potential implications for addressing these challenges to inclusion in PD.

Peer feedback is essential for learning in project-based disciplines. However, students often need guidance when acting as either a feedback provider or a feedback receiver, both to gain from peer feedback and to criticize their peers' work. This paper explores how to more effectively scaffold this exchange such that peers more deeply engage in the feedback process. Within a game design course, we introduced different processes for feedback receivers to write questions to guide peer feedback. Feedback receivers wrote four main types of guiding questions: improve, share, brainstorm, critique. We found that "improve'' questions tended to lead to better feedback (more specific, critical, and actionable) than other question types, but feedback receivers wrote improve questions least often. We offer insights on how best to scaffold the question-writing process to facilitate peer feedback exchange.