Exploring the Ethical and Social Impact of Artificial Intelligence: A BERTopic Analysis of Academic Literature

Artificial intelligence (AI) is fundamentally transforming society, making its ethical and social implications an increasingly critical and evolving area of study. This study investigated the dominant themes in academic literature on AI’s societal effects, with a focus on ethical, economic, and broader social implications. While previous research has explored specific aspects of AI’s impact, the comprehensive examination of overarching themes and their implications remain an ongoing and necessary endeavour. Accordingly, this study employed BERTopic, an advanced topic modelling technique, to analyse a large corpus of academic literature retrieved from Scopus and Web of Science. The search strategy combined AI-related concepts with social impact themes. The analysis identified six dominant clusters: (1) AI in Transportation and Urban Mobility; (2) AI in Agriculture, Environment, and Energy; (3) AI in Renewable Energy, Sustainability, and Industrial Systems; (4) AI and Robotics in Society: Education, Care, and Employment; (5) AI in Media, Security, and Ethical Systems; (6) AI in Governance, Creativity, and Sustainable Development. These clusters represent the dominant themes concerning AI’s social impact. In-depth analysis drew attention to pressing societal challenges, particularly ethical considerations, as well as AI’s pronounced role in healthcare and education. It also revealed emerging trends such as generative AI and the growing emphasis on sustainability, highlighting how these shape the discourse. The findings emphasise the need for interdisciplinary research and policy interventions to mitigate AI’s societal risks and promote its responsible adoption. This study contributes to the growing body of literature by providing a structured overview of dominant themes, identifying research gaps, and offering actionable insights for stakeholders. Recommendations include the development of strong governance frameworks, the promotion of interdisciplinary collaboration, and the advancement of equity and inclusivity in the development and deployment of AI initiatives.