Artificial Intelligence as a Research Tool in Social Sciences: Contemporary Opportunities and Emerging Challenges

Abstract The integration of Artificial Intelligence (AI) into social science research marks a pivotal transformation in both methodological practice and analytical scope. While traditional paradigms in the social sciences have prioritized interpretive depth and qualitative nuance, AI technologies—ranging from machine learning and computational linguistics to advanced predictive analytics—enable researchers to engage with large-scale, complex datasets in novel and efficient ways. This paper offers a critical examination of the expanding role of AI in social research, articulating the opportunities it presents for enhanced data interpretation, uncovering subtle behavioral trends, and informing evidence-based policymaking. Alongside these advancements, the study addresses the emerging methodological and ethical dilemmas associated with AI-driven research. Issues such as algorithmic bias, the ethical management of personal and public data, and epistemological concerns surrounding the quantification of human experience are scrutinized through a multidisciplinary lens. The discussion highlights the inherent tension between technological innovation and the humanistic ethos central to social inquiry. This investigation draws on a range of empirical studies and theoretical perspectives to assess AI’s dual impact: as a transformative research enabler and as a source of interpretive and ethical complexity. By positioning this analysis at the intersection of social science, computational methodology, and research ethics, the paper advocates for a balanced, critically engaged adoption of AI. It concludes with strategic recommendations aimed at fostering interdisciplinary collaboration, establishing ethical governance protocols, and equipping researchers with the necessary competencies to responsibly navigate AI’s evolving role in social science research.