From Interaction to Collaboration: How Hybrid Intelligence Enhances Chatbot Feedback
This addresses the challenge of enhancing feedback quality for organizations using chatbots to build customer relationships, though it appears incremental as it builds on existing feedback mechanisms.
This study tackled the problem of improving user feedback for generative AI chatbots by comparing standard AI-focused interactions with hybrid intelligence (HI) framed interactions, finding that the HI narrative led to participants providing significantly more detailed feedback.
Generative AI (GenAI) chatbots are becoming increasingly integrated into virtual assistant technologies, yet their success hinges on the ability to gather meaningful user feedback to improve interaction quality, system outcomes, and overall user acceptance. Successful chatbot interactions can enable organizations to build long-term relationships with their customers and users, supporting customer loyalty and furthering the organization's goals. This study explores the impact of two distinct narratives and feedback collection mechanisms on user engagement and feedback behavior: a standard AI-focused interaction versus a hybrid intelligence (HI) framed interaction. Initial findings indicate that while small-scale survey measures allowed for no significant differences in user willingness to leave feedback, use the system, or trust the system, participants exposed to the HI narrative statistically significantly provided more detailed feedback. These initial findings offer insights into designing effective feedback systems for GenAI virtual assistants, balancing user effort with system improvement potential.