NSF Award
2301846
This Engineering Research Initiation (ERI) project aims to understand the role of affect in developing trust during collaborations between users and Artificial Intelligence (AI) system for engineering design, which will then inform design guidelines for improving trust and collaboration outcomes. Modern AI systems have become more interactive and sophisticated than legacy automated systems. However, trust between humans and AI systems is in a potential crisis. While affect is an essential element of trust development and can significantly influence people’s tendency to collaborate, it has not been studied quantitatively in human-AI collaboration or modeled holistically with respect to system design attributes. To address this gap, this research will: (1) examine the influence of affect in user trust during interactions with an AI-powered conversational agent; (2) investigate how trust in AI influences human-AI collaboration; and (3) develop a value model that considers affect and system attributes comprehensively. This research will advance knowledge of trust development with an emphasis on affect and the design of AI systems. The knowledge will inform a design framework that enables AI systems to be trusted, accepted, and utilized more to augment human capabilities in completing complex tasks. Improved human-AI collaboration will enhance the quality of human life and potentially benefit disadvantaged populations, such as senior citizens, who are not early technology adopters, as well as telehealth applications, where trust can be tenuous. <br/><br/>The overarching goal of this project is to advance knowledge about the nature of trust development in human-Artificial Intelligence (AI) collaboration and how engineering designers can enhance trust in the design of AI systems to improve collaboration outcomes. The research examines the effect of affect, system performance, and system characteristics on user trust in an AI-powered conversational agent for a collaborative design task, and investigates how human-AI trust influences design outcomes. The research will holistically model users’ value judgments using a modified conjoint analysis of both affect and system-related attributes. The results will inform an innovative design framework that indicates the relative importance of the attributes and favorable design directions for human-AI collaboration. The research has the potential for broad societal impact by providing tangible guidelines for how to improve and maintain trustworthy human-AI collaborations, which augment the human capability of completing cognitively demanding tasks and may particularly benefit disadvantaged populations. The research serves as the basis for a broader range of design applications beyond web interfaces and dialogues, and will provide transformative knowledge of human-AI interactions in virtual environments and for complex systems.<br/><br/>This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.
