Conversational AI for Social Good (CAI4SG): An Overview of Emerging Trends, Applications, and Challenges
Yi-Chieh Lee, Junti Zhang, Tianqi Song, Yugin Tan
TL;DR
The paper addresses how Conversational AI can be harnessed for social good by introducing a role-based framework that separates systems by AI autonomy and emotional engagement. It surveys a diverse set of applications across four quadrants, detailing concrete use cases in public services, accessibility, mental health, education, and misinformation control, while highlighting associated risks such as bias, privacy, and emotional dependency. The authors synthesize ethical, technical, and governance challenges across roles and propose future directions focusing on role boundaries, cross-cultural research, and robust normative frameworks. By connecting real-world deployments with principled design and governance, the work underscores the potential for CAI4SG to scale beneficial impact responsibly and equitably.
Abstract
The integration of Conversational Agents (CAs) into daily life offers opportunities to tackle global challenges, leading to the emergence of Conversational AI for Social Good (CAI4SG). This paper examines the advancements of CAI4SG using a role-based framework that categorizes systems according to their AI autonomy and emotional engagement. This framework emphasizes the importance of considering the role of CAs in social good contexts, such as serving as empathetic supporters in mental health or functioning as assistants for accessibility. Additionally, exploring the deployment of CAs in various roles raises unique challenges, including algorithmic bias, data privacy, and potential socio-technical harms. These issues can differ based on the CA's role and level of engagement. This paper provides an overview of the current landscape, offering a role-based understanding that can guide future research and design aimed at the equitable, ethical, and effective development of CAI4SG.