Users' Mental Models of Generative AI Chatbot Ecosystems

TL;DR

This study explores how users understand GenAI chatbot ecosystems, revealing diverse mental models that influence trust and privacy concerns, with implications for design and policy.

Contribution

It uncovers users' mental models of GenAI ecosystems through interviews, highlighting differences between first-party and third-party perceptions.

Findings

Users have four mental models centered on the chatbot's role.

Third-party ecosystems are perceived more simply and with higher trust.

Users show fewer concerns towards third-party ecosystems.

Abstract

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.