Epistemology and Methodology of Research in the AI Age maps how artificial intelligence (AI), digital platforms, and big data reshape the foundations of social science and management research. It connects epistemology and research design to the practical choices researchers now face, from defining questions in data-rich environments to handling algorithmic bias and ethical risk.
Key features include:
• Explains how research paradigms and epistemological assumptions shape digital and AI-enabled inquiry.
• Translates validity, reliability, and ethics into concrete decisions about sampling, online data, platform effects, and transparency.
• Shows how to frame research questions and hypotheses when automation and analytics influence what counts as evidence.
• Guides the literature review in the AI age, including digital search strategies, systematic reviews, and meta-analysis.
Written for doctoral students, early-career researchers, and methods instructors, this volume supports dissertation work and methods teaching across sociology, psychology, education, economics, and information science. It also anchors the wider series by setting a shared conceptual and ethical baseline for the volumes that follow.
This book maps how artificial intelligence, digital platforms, and big data reshape the foundations of social science and management research. It connects epistemology and research design to the practical choices researchers now face, from defining questions in data-rich environments to handling algorithmic bias and ethical risk.
