Kaiwen Sun, University of Michigan School of Information; Ritesh Kanchi, School of Computer Science & Engineering University of Washington; Frances Marie Tabio Ello, Human Centered Design & Engineering University of Washington; Li-Neishin Co, The Information School & Department of Psychology University of Washington; Mandy Wu, Human Centered Design & Engineering University of Washington; Susan Gelman, Department of Psychology University of Michigan; Jenny Radesky, Department of Pediatrics University of Michigan Medical School; Florian Schaub, University of Michigan School of Information; Jason Yip, The Information School University of Washington
Children struggle to understand hidden data processes (e.g., inferences) and related privacy implications (e.g., profiling). Children use visual cues to reason about technical processes in digital products, sometimes drawing inaccurate conclusions when interface cues are vague or absent. We conducted five consecutive participatory design sessions with children (ages 7–12), probing their perceptions of visual cues and data processes; and iteratively designed and reviewed new visual cues with them. We found that children conceptualized data collection concretely, lacked awareness of its pervasive nature, expressed limited understanding of data inferences, and recognized certain visual cues (e.g., loading, cloud) but unable to explain their meanings. We designed visual cues in “symbolic” and “concrete” styles using icons and metaphors, which helped children understand data flows. Our work contributes to developing comprehensible visual cues for children to support their data and privacy literacy. We discuss design and policy implications of our findings.
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