Conversational AI for Social Good (CAI4SG): An Overview of Emerging Trends, Applications, and Challenges

Role matters for responsible design: The paper introduces a role-based framework showing that conversational AI systems designed for social good take on different functions—from empathetic mental health supporters to accessibility assistants—and each role requires distinct ethical considerations rather than a one-size-fits-all approach to responsible AI.

Emotional engagement creates unique risks: Systems designed with higher emotional engagement (like those providing mental health support) introduce particular challenges around algorithmic bias and socio-technical harms that differ from less emotionally-engaged applications, suggesting that more emotionally intimate AI requires heightened safeguards.

Three critical challenges demand attention: The paper identifies algorithmic bias, data privacy, and socio-technical harms as key obstacles to responsible deployment, with the specific manifestation of these challenges varying depending on the conversational AI's intended role and level of emotional involvement with users.

Accessibility and equity are central to social good: Beyond addressing global challenges, responsible conversational AI must actively serve accessibility needs and promote equitable outcomes, positioning accessibility not as an afterthought but as a core component of social good applications.

Current landscape requires guidance for future development: The paper emphasizes that understanding these role-based differences is essential for guiding future research and design decisions to ensure conversational AI systems are developed equitably, ethically, and effectively.