Participatory Design of AI with Children: Reflections on IDC Design Challenge

• URL: http://arxiv.org/abs/2304.09091v1
• Date: Tue, 18 Apr 2023 15:58:46 GMT
• Title: Participatory Design of AI with Children: Reflections on IDC Design Challenge
• Authors: Zhen Bai, Frances Judd, Naomi Polinsky, Elmira Yadollahi
• Abstract summary: Participatory Design (PD) empowers children to bring their interests, needs, and creativity to the design process of future technologies. While PD has drawn increasing attention to human-centered AI design, it remains largely untapped in facilitating the design process of AI technologies relevant to children and their community. We report intriguing children's design ideas on AI technologies resulting from the "Research and Design Challenge" of the 22nd ACM Interaction Design and Children (IDC 2023) conference.
• Score: 1.3381749415517021
• License: http://creativecommons.org/licenses/by-nc-nd/4.0/
• Abstract: Children growing up in the era of Artificial Intelligence (AI) will be most impacted by the technology across their life span. Participatory Design (PD) is widely adopted by the Interaction Design and Children (IDC) community, which empowers children to bring their interests, needs, and creativity to the design process of future technologies. While PD has drawn increasing attention to human-centered AI design, it remains largely untapped in facilitating the design process of AI technologies relevant to children and their community. In this paper, we report intriguing children's design ideas on AI technologies resulting from the "Research and Design Challenge" of the 22nd ACM Interaction Design and Children (IDC 2023) conference. The diversity of design problems, AI applications and capabilities revealed by the children's design ideas shed light on the potential of engaging children in PD activities for future AI technologies. We discuss opportunities and challenges for accessible and inclusive PD experiences with children in shaping the future of AI-powered society.

Related papers

• Responding to Generative AI Technologies with Research-through-Design: The Ryelands AI Lab as an Exploratory Study [6.028558240668647]
  We partner with a primary school to develop a constructionist curriculum centered on students interacting with a generative AI technology. We provide a detailed account of the design of and outputs from the curriculum and learning materials, finding centrally that the reflexive and prolonged hands-on' approach led to a co-development of students' practical and critical competencies.
  arXiv  Detail & Related papers  (2024-05-07T21:34:10Z)
• Inclusive Practices for Child-Centered AI Design and Testing [1.534667887016089]
  We offer insights on creating AI technologies that are accessible and include input from neurodivergent children. We emphasize the importance of adaptable and supportive AI technologies and design processes.
  arXiv  Detail & Related papers  (2024-04-09T00:51:24Z)
• Now, Later, and Lasting: Ten Priorities for AI Research, Policy, and Practice [63.20307830884542]
  Next several decades may well be a turning point for humanity, comparable to the industrial revolution. Launched a decade ago, the project is committed to a perpetual series of studies by multidisciplinary experts. We offer ten recommendations for action that collectively address both the short- and long-term potential impacts of AI technologies.
  arXiv  Detail & Related papers  (2024-04-06T22:18:31Z)
• Exploring Parent's Needs for Children-Centered AI to Support Preschoolers' Interactive Storytelling and Reading Activities [52.828843153565984]
  AI-based storytelling and reading technologies are becoming increasingly ubiquitous in preschoolers' lives. This paper investigates how they function in practical storytelling and reading scenarios and, how parents, the most critical stakeholders, experience and perceive them. Our findings suggest that even though AI-based storytelling and reading technologies provide more immersive and engaging interaction, they still cannot meet parents' expectations due to a series of interactive and algorithmic challenges.
  arXiv  Detail & Related papers  (2024-01-24T20:55:40Z)
• Grasping AI: experiential exercises for designers [8.95562850825636]
  We investigate techniques for exploring and reflecting on the interactional affordances, the unique relational possibilities, and the wider social implications of AI systems. We find that exercises around metaphors and enactments make questions of training and learning, privacy and consent, autonomy and agency more tangible.
  arXiv  Detail & Related papers  (2023-10-02T15:34:08Z)
• Expansive Participatory AI: Supporting Dreaming within Inequitable Institutions [0.2538209532048867]
  Participatory Artificial Intelligence (PAI) has recently gained interest by researchers as means to inform the design of technology through collective's lived experience. In this work we propose co-design principals for AI that address institutional power dynamics focusing on Participatory AI with youth.
  arXiv  Detail & Related papers  (2022-11-22T17:44:03Z)
• Seamful XAI: Operationalizing Seamful Design in Explainable AI [59.89011292395202]
  Mistakes in AI systems are inevitable, arising from both technical limitations and sociotechnical gaps. We propose that seamful design can foster AI explainability by revealing sociotechnical and infrastructural mismatches. We explore this process with 43 AI practitioners and real end-users.
  arXiv  Detail & Related papers  (2022-11-12T21:54:05Z)
• StoryBuddy: A Human-AI Collaborative Chatbot for Parent-Child Interactive Storytelling with Flexible Parental Involvement [61.47157418485633]
  We developed StoryBuddy, an AI-enabled system for parents to create interactive storytelling experiences. A user study validated StoryBuddy's usability and suggested design insights for future parent-AI collaboration systems.
  arXiv  Detail & Related papers  (2022-02-13T04:53:28Z)
• Stakeholder Participation in AI: Beyond "Add Diverse Stakeholders and Stir" [76.44130385507894]
  This paper aims to ground what we dub a 'participatory turn' in AI design by synthesizing existing literature on participation and through empirical analysis of its current practices. Based on our literature synthesis and empirical research, this paper presents a conceptual framework for analyzing participatory approaches to AI design.
  arXiv  Detail & Related papers  (2021-11-01T17:57:04Z)
• Building Bridges: Generative Artworks to Explore AI Ethics [56.058588908294446]
  In recent years, there has been an increased emphasis on understanding and mitigating adverse impacts of artificial intelligence (AI) technologies on society. A significant challenge in the design of ethical AI systems is that there are multiple stakeholders in the AI pipeline, each with their own set of constraints and interests. This position paper outlines some potential ways in which generative artworks can play this role by serving as accessible and powerful educational tools.
  arXiv  Detail & Related papers  (2021-06-25T22:31:55Z)
• Towards a New Participatory Approach for Designing Artificial Intelligence and Data-Driven Technologies [23.36435820457202]
  Participatory design (PD) is often used with marginalized communities for the design of social development, policy, IT and other matters and solutions. This paper argues for the use of PD for the design of AI technologies, and introduces and proposes a new PD, which we call agile participatory design.
  arXiv  Detail & Related papers  (2021-03-30T23:36:25Z)

This list is automatically generated from the titles and abstracts of the papers in this site.

This site does not guarantee the quality of this site (including all information) and is not responsible for any consequences.