Children build and think differently about trustworthy AI chatbots
How Children Design and Reason about Trustworthy AI Chatbots
Human-Computer InteractionArtificial Intelligence
Summary
Children are using AI chatbots more and need to know when to trust them. This paper looked at how kids aged 8 to 18 build their own chatbots and what makes them trust these bots. Younger kids often trust chatbots that do the job they were made for, even if they are wrong, while older kids want chatbots to be clear and honest about their answers. The study found that kids also change how formal or clear chatbots are, depending on the chatbot's purpose. The authors identified seven key ways children think about trust in chatbots to help improve AI learning tools.
What this means in practice
- •For educational software developers: Create AI chatbot building tools tailored to children's trust perceptions and developmental differences in AI literacy.
- •For user experience designers: Design chatbot interfaces that adjust transparency and formality based on the chatbot’s intended use to improve trustworthiness perceptions.
Authors
Deniz Ozturk, Jiayu Li, Daksh Pratap Singh, Yasitha Rajapaksha, Fasika Melese, Bahare Riahi, Shiyan Jiang, Qiao, Jin, Joey Huang, Veronica Cateté, Tiffany Barnes, Xiaoyi Tian
Abstract
Children increasingly interact with AI chatbots, making trust calibration essential to AI literacy. Prior research has examined children's trust in AI mainly as users evaluating systems built by others, rather than as designers of their own chatbots. We developed a chatbot-building environment with adjustable trust-relevant traits (e.g., confidence, transparency, formality, assertiveness), rules, and persona. We conducted mixed-methods study with 115 learners (ages 8-18) who made 119 chatbots. We examined how children configured their chatbots, reasoned about trustworthiness, and how closely chatbot behavior aligned with their designs. Younger students (age 10-13) set significantly higher confidence than older students (age 14-18), and some deliberately built chatbots that gave wrong answers on purpose, yet still called them trustworthy, arguing that a chatbot does what it was built to do. Younger students equated trust with purpose-fulfillment, while older students linked it to transparent, calibrated design. Students also calibrated academic chatbots to be more transparent and formal than hobby chatbots. We identify seven design dimensions describing what children believe makes a chatbot trustworthy, and discuss implications for AI literacy tools.