PlantWhisperer: Designing Conversational AI to Support Plant Care

2026-02-28

AI Summary

This study investigates how conversational AI can enhance users’ psychological well-being through anthropomorphized plant interactions. Grounded in the PERMA model of well-being, the research developed a mobile application enabling users to engage in dialogue with a “talking” plant chatbot. User experiences were explored via semi-structured interviews and qualitative analysis. Findings indicate that the design significantly strengthened emotional bonds between users and their virtual plants and heightened feelings of caregiving accomplishment, thereby demonstrating the positive impact of human–plant–AI triadic interaction on mental well-being. This work represents the first application of the PERMA framework to plant-based conversational AI, revealing the critical role and diverse needs of personalized interaction in fostering psychological well-being.

Technology Category

• Humans and AI: Interaction Techniques and Devices
• Intelligent Robots: Human-Robot Interaction
• Data Mining & Knowledge Management: Conversational Systems for Recommendation & Retrieval

Application Category

• User Modeling, Personalization and Recommendation: Psychology-informed user models and recommender systems
• Search and Retrieval-Augmented AI: Assisted, interactive, and conversational search
• Semantics and Knowledge: Data modeling to support human-machine intelligence, including LLMs agents, intelligent system behavior, explanations, and user-friendly interactions

Abstract

Research in Human-Computer Interaction (HCI) has shown that caring for others, including both humans (e.g., close friends) and computers (e.g., Tamagotchi), can have a positive effect on people's wellbeing. However, we know less about the potential role of conversational AI in such settings. In this work, we explore how AI chatbots can support plant care and, in turn, positively influence people's well-being. We developed a mobile application that allows users to `talk' to their plants via chatbots. We evaluated the application with ten participants and conducted semi-structured interviews based on Seligman's PERMA model, which identifies pillars of psychological well-being. Our findings suggest positive effects, with participants reflecting on a sense of connection to their plants and corresponding feelings of accomplishment. While our findings suggest that participants were generally positive about the app, they also raised concerns about the diverse preferences and expectations of users regarding interactions with chatbots representing plants.

Problem

• Conversational AI
• Plant Care
• Well-being
• Human-Computer Interaction
• Chatbot

Innovation

• Conversational AI
• Plant Care
• Human-Computer Interaction
• Well-being
• PERMA Model