Problem
Research questions and friction points this paper is trying to address.
Children
Trustworthy AI Chatbots
Design
Reasoning
AI Literacy
How Children Design and Reason about Trustworthy AI Chatbots
🤖 AI Summary
研究通过让儿童设计具有可调信任相关特性的聊天机器人，探讨了儿童如何配置和推理聊天机器人的可信度，以促进AI素养。
📝 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.
Innovation
Methods, ideas, or system contributions that make the work stand out.
chatbot-building environment
trust-relevant traits
age differences in trust calibration
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