A Bibliometric Analysis of the Ethical and Social Implications of AI

The rapid advancement of artificial intelligence (AI) has raised significant ethical and social concerns, necessitating a systematic analysis of research trends in this domain. This study employs a bibliometric analysis using data from Scopus and visualization through VOSviewer to map the scholarly landscape of AI ethics. The analysis identifies key research themes, including algorithmic bias, data privacy, transparency, accountability, and trust, while highlighting emerging topics such as ChatGPT, adversarial machine learning, AI in education and healthcare, and sustainability. The co-authorship and country collaboration networks reveal a highly interdisciplinary and globally connected research community, with strong contributions from the United States, Germany, India, and China, but limited representation from the Global South. Findings indicate that AI ethics research is evolving beyond theoretical discussions to address real-world applications and governance challenges. The study underscores the need for more inclusive AI policies, interdisciplinary collaborations, and ethical AI governance frameworks to ensure responsible AI development. Future research should focus on bridging the gap between AI engineering and ethical oversight, regulating AI-driven misinformation, and expanding the global diversity of AI ethics discourse.