Two of the most socially consequential issues facing today’s children are the rise of artificial intelligence (AI) and the rapid changes to the earth’s climate. Both issues are complex and contested, and they are linked through the notable environmental costs of AI use. Using a systems thinking framework, we developed an interactive system called Ecoprompt to help children reason about the environmental impact of AI. EcoPrompt combines a prompt-level environmental footprint calculator with a simulation game that challenges players to reason about the impact of AI use on natural resources that the player manages. We evaluated the system through two participatory design sessions with 16 children ages 6–12. Our findings surfaced children’s perspectives on societal and environmental tradeoffs of AI use, as well as their sense of agency and responsibility. Taken together, these findings suggest opportunities for broadening AI literacy to include systems-level reasoning about AI’s environmental impact.

AI technologies have become increasingly embedded in children’s lives. While there are many frameworks for designing AI technologies for children’s well-being, few have been tested against the tensions children experience when using AI across different global contexts. This workshop explores how to design AI technologies that enhance children’s digital well-being in accordance with various developmental and child-computer interaction frameworks, as well as what developers and designers should consider as they do so. Our goal is to convene an interdisciplinary international community to pave the way for future research and practice that seeks to design AI technologies with children’s well-being in mind.

Long-distance relationships (LDRs) have become more common in the last few decades, primarily among young adults pursuing educational or employment opportunities.A common way for couples in LDRs to spend time together is by playing multiplayer video games, which are often a shared hobby and therefore a preferred joint activity.However, games are relatively understudied in the context of relational maintenance for LDRs.In this work, we used a mixed-methods approach to collect data on the experiences of 13 couples in LDRs who frequently play games together.We investigated different values around various game mechanics and modalities and found significant differences in couple play styles, and also detail how couples appropriate game mechanics to express affection to each other virtually.We also created prototypes and design implications based on couples' needs surrounding the lack of physical sensation and memorabilia storage in most popular games.

While much of the research in digital games has emphasized hedonic experiences, such as flow, enjoyment, and positive affect, recent years have seen increased interest in eudaimonic gaming experiences, typically mixed-affect and associated with personal meaningfulness and growth. The formation of such experiences in games is theorized to have four constituent elements: motivation, game use, experience, and effects. However, while the first three elements have been relatively well explored in the literature, the effects - and how they may influence positive individual outcomes - have been underexplored thus far. To this end, in this work, we investigate the perceived outcomes of eudaimonic gaming and how different components of the experience influence these effects. We conducted a survey (n = 166) in which respondents recounted meaningful gaming experiences and how they affected their present lives. We used a mixed-methods approach to classify effects and identify significant subcomponents of their formation. We contribute an empirical understanding of how meaningful gaming experiences can lead to positive reflective, learning, social, health, and career effects, extending current theoretical models of eudaimonic gaming experiences and offering implications for how researchers and practitioners might use these findings to promote positive outcomes for players.

Playful forms of construction, both analog and digital, enable players of all ages to build whatever they imagine. Engaging in construction-oriented play grants diverse people a wide range of benefits, such as enhanced collaborative problem solving, gains in spatial reasoning, and increases in demonstrated creativity. However, the inaccessibility of construction-oriented play, especially in the digital medium, precludes blind and low-vision players from these important benefits. In this work, we sought to understand how construction-oriented play affects blind players’ lives and the access challenges they face. Through semi-structured interviews with 17 participants aged 10 to 48, we found that construction-oriented play provides BLV individuals with socialization, cultural inclusion, and therapeutic benefits, fostering creativity and expression; however, vision-diverse players often rely on tactile references, sighted assistance, and/or customized game modifications to overcome accessibility challenges. We contribute a qualitative empirical understanding of how blind and low-vision people are interacting with digital and tangible construction media and discuss future directions for more accessible construction-oriented play.

In this work, we explore the effect of a social robot’s embodiment and creativity scaffolding on children’s creative problem solving skills in the context of a digital creative problem-solving game called Escape!Bot. Children aged 5-11 years played the video game, which involved assembling contraptions to escape a digital world, and the robot Jibo acted as a collaborative peer that offered questions, reflective prompts, challenges, and ideas. In order to evaluate the role of the robot’s co-presence and creativity scaffolding, we ran a 2x2 experiment to determine the factorial efficacy of the robot’s embodiment and creativity scaffolding behaviors. We observed mixed results, with the robot’s creativity scaffolding having a positive influence on the time taken to complete the game, but not on the overall use of novel objects or reuse of objects. We present the system design, user study and findings from Escape!Bot to investigate the feasibility of designing social robots to support creative problem solving.

Body-tracking artificial intelligence (AI) systems like Kinect games, Snapchat Augmented Reality (AR) Lenses, and Instagram AR Filters are some of the most engaging ways students experience AI in their everyday lives. Additionally, many students have existing interests in physical hobbies like sports and dance. In this paper, we present PoseBlocks; a suite of block-based programming tools which enable students to build compelling body-interactive AI projects in any web browser, integrating camera/microphone inputs and body-sensing user interactions. To accomplish this, we provide a custom block-based programming environment building on the open source Scratch project, introducing new AI-model-powered blocks supporting body, hand, and face tracking, emotion recognition, and the ability to integrate custom image/pose/audio models from the online transfer learning tool Teachable Machine. We introduce editor functionality such as a project video recorder, pre-computed video loops, and integration with curriculum materials. We discuss deploying this toolkit with an accompanying curriculum in a series of synchronous online pilots with 46 students, aged 9-14. In analyzing class projects and discussions, we find that students learned to design, train, and integrate machine learning models in projects of their own devising while exploring ethical considerations such as stakeholder values and algorithmic bias in their interactive AI systems.