Artificial Intelligence and Computation in the Social Sciences: A Paradigm Shift.

Chapter 3 explores artificial intelligence’s (AI) transformative role at multiple levels of analysis—individual, group, and societal—highlighting its capacity to enhance theory, measurement, and practical applications. The chapter examines how AI methods, from natural language processing (NLP) to agent-based modeling, can be strategically integrated to generate novel insights across disciplines. At the individual level, AI enables dynamic assessment through computerized adaptive testing (CAT) and multimodal behavioral signals. At the group level, AI facilitates team collaboration, conflict resolution, and intergroup communication analysis using large language models (LLMs). At the societal level, AI tracks public sentiment, organizational behavior, and structural inequalities. The chapter addresses critical challenges including algorithmic bias, interpretability, and ethical concerns. The interdisciplinary nature of AI as a research toolkit demonstrates how computational methods can advance understanding while requiring careful oversight to ensure responsible implementation.