Work

From information to operations: Exploring the impact of integrated AI-HI on information diffusion and users' willingness in humanitarian aid

Year: 2025

Type: article

Abstract: The advancement in AI usage and technological capabilities has provided greater convenience in the diffusion of information within humanitarian aid operations, offering aid workers expanded operational possibilities and improving the efficiency of response. Consequently, experts in the field suggest that integrating AI and HI represents the next major development in humanitarian aid. Unfortunately, there is currently a lack of research exploring the integration of AI within communication platforms as an information hub, leaving a gap for both aid workers and scholars. To address this gap, this study, based on the concept of perceived affordances and combined with affordance theory, investigates the interaction and overlay of AI and communication platforms. We conducted three studies in an online environment using real disaster relief videos and simulated communication platforms. Our findings indicate that the integration of AI (vs. Without AI) in communication platforms functioning as information hubs enhances perceived affordances. Specifically, AI improves perceived visibility and perceived editability, which in turn increases aid workers' willingness to exchange information and use the platform. Moreover, the facilitating effect of AI integration is less constrained by the actual level of affordances. Additionally, time pressure moderates these effects. Our study contributes to the field of humanitarian aid. • Examines the impact of AI-HI integration in humanitarian aid communication platforms on user willingness. • Investigates the role of AI in enhancing perceived affordance, including perceived visibility and perceived editability. • Finds that AI’s facilitating effect is less constrained by the actual level of affordances. • Analyzes the impact of time pressure on AI in humanitarian aid operations using the Conservation of Resources theory.

Source: Technological Forecasting and Social Change

DOI: 10.1016/j.techfore.2025.124501

Authors: Shizhen Bai, Jiamin Zhou, Chunjia Han, Mu Yang, Chen Wang, Brij B. Gupta