Mental Models of Generative AI Chatbot Ecosystem
Authors
The capability of GenAI-based chatbots, such as ChatGPT and Gemini, has expanded quickly in recent years, turning them into GenAI Chatbot Ecosystems. Yet, users' understanding of how such ecosystems work remains unknown. In this paper, we investigate users' mental models of how GenAI Chatbot Ecosystems work. This is an important question because users' mental models guide their behaviors, including making decisions that impact their privacy. Through 21 semi-structured interviews, we uncovered users' four mental models towards first-party (e.g., Google Gemini) and third-party (e.g., ChatGPT) GenAI Chatbot Ecosystems. These mental models centered around the role of the chatbot in the entire ecosystem. We further found that participants held a more consistent and simpler mental model towards third-party ecosystems than the first-party ones, resulting in higher trust and fewer concerns towards the third-party ecosystems. We discuss the design and policy implications based on our results.
Research Questions / Practical Problems
Question signals indexed for this paper.
Research Questions
3- How do users understand data flows and privacy protection in generative AI (GenAI) chatbot ecosystems?Category: LLM Trust and Over/Under-RelianceSimilar questionsarrow_forward
- How do user trust and privacy concerns differ between first-party systems (e.g., Google Gemini) and third-party systems (e.g., ChatGPT)?Category: LLM Trust and Over/Under-RelianceSimilar questionsarrow_forward
- How do different mental models affect users' trust and data privacy decisions?Category: LLM Trust and Over/Under-RelianceSimilar questionsarrow_forward
Practical Problems
1- Users struggle to understand complex AI ecosystems, affecting privacy decisions.Category: LLM Trust and Over/Under-RelianceSimilar questionsarrow_forward
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