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Youth regularly use technology driven by artificial intelligence (AI). However, it is increasingly well-known that AI can cause harm on small and large scales, especially for those underrepresented in tech fields. Recently, users have played active roles in surfacing and mitigating harm from algorithmic bias. Despite being frequent users of AI, youth have been under-explored as potential contributors and stakeholders to the future of AI. We consider three notions that may be at the root of youth facing barriers to playing an active role in responsible AI, which are youth (1) cannot understand the technical aspects of AI, (2) cannot understand the ethical issues around AI, and (3) need protection from serious topics related to bias and injustice. In this study, we worked with youth (N = 30) in first through twelfth grade and parents (N = 6) to explore how youth can be part of identifying algorithmic bias and designing future systems to address problematic technology behavior. We found that youth are capable of identifying and articulating algorithmic bias, often in great detail. Participants suggested different ways users could give feedback for AI that reflects their values of diversity and inclusion. Youth who may have less experience with computing or exposure to societal structures can be supported by peers or adults with more of this knowledge, leading to critical conversations about fairer AI. This work illustrates youths' insights, suggesting that they should be integrated in building a future of responsible AI.
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Digital games featuring programmable agents are popular tools for teaching coding and computational thinking skills. However, today's games perpetuate an arguably obsolete relationship between programmable agents and human operators. Borrowing from the field of human-robotics interaction, we argue that collaborative robots, or cobots, are a better model for thinking about computational agents, working directly with humans rather than in place of or at arm's length from them. In this paper, we describe an initial design inquiry into the design of “cobot games”, programmable agent scenarios in which players program an in-game ally to assist them in accomplishing gameplay objectives. We detail three questions that emerged out of this exploration, our present thinking on them, and plans for deepening inquiry into cobot game design moving forward.more » « less
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Fostering equal design partnerships in adult-child codesign interactions is a well-documented challenge in HCI. It is assumed that adults come into these interactions with power and have to make adjustments to allow childrens’ input to be equally valued. However, power is not a unilateral construct - it is in part determined by social and cultural norms that often disadvantage minoritized groups. Striving for equal partnership without centering users’ and participants’ intersectional identities may lead to unproductive adult-child codesign interactions. We codesigned a game, primarily facilitated by a black woman researcher, with K-5 afterschool programs comprised of students from three different communities – a middle-class, racially diverse community; a low-income, primarily African American community; and a working-class rural, white, community over a period of 20 weeks. We share preliminary insights on how racial and gender biases affect codesign partnerships and describe future research plans to modify our program structure to foster more effective adult-child interactions.more » « less
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null (Ed.)Feedback is a key element of project-based learning, but only if students reflect on and learn from the feedback they receive. Students often struggle to deeply engage with feedback, whether due to lack of confidence, time, or skill. This work seeks to identify challenges that make reflecting on feedback difficult for students, and to design possible solutions for supporting reflection. Through observing two university game design courses, our research found that without concrete reflection strategies, students tended to be attracted to feedback that looks useful, but does not necessarily them move forward. When we introduced three different reflection scaffolds to support students, we found that the most effective approach promoted interactive learning by allowing time for self-reflection before team reflection, offering time limits, providing activities for feedback prioritization, helping teams align their goals, and equalizing team member participation. We present design guidelines for future systems to support reflection on feedback.more » « less
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The Internet-of-things (IoT) embeds computing in everyday objects, but has largely focused on new devices while ignoring the home's many existing possessions. We present a field study with 10 American families to understand how these possessions could be included in the smart home through upcycling. We describe three patterns for how families collaborate around home responsibilities; we explore families' mental models of home that may be in tension with existing IoT systems; and we identify ways that families can more easily imagine a smart home that includes their existing possessions. These insights can help us design an upcycled approach to IoT that supports users in reconfiguring objects (and social roles as mediated by objects) in a way that is sensitive to what will be displaced, discarded, or made obsolete. Our findings inform the design of future lightweight systems for the upcycled home.more » « less