From Likert Scale to the Chatbot

Abstract

Personality assessment has undergone a significant historical transformation in personnel selection, evolving from initial skepticism about its usefulness to widespread acceptance as a robust predictor of work behavior and organizational outcomes. This chapter traces the historical, conceptual, and methodological foundations that underlie this shift, emphasizing the central role of construct validity in advancing personality research and practice. It reviews contemporary models of personality structure, including hierarchical, nomological, ideal point, network, and machine-learning-based approaches, and examines how emerging technologies such as simulations, gamified assessments, conversational agents, and artificial intelligence (AI)-enabled behavioral analytics are reshaping how personality is measured. Across traditional and technology-based methods, the chapter highlights enduring challenges related to response bias, subgroup differences, fairness, and validation, and it argues that in the AI era, these concerns are only amplified rather than diminished. The chapter also considers the relevance of personality beyond individual-level outcomes, including team, organizational, and collective phenomena. The chapter concludes by arguing that the future of personality assessment depends not on abandoning psychometric principles, but on integrating technological innovation with theory-driven, construct-centered measurement to ensure interpretability, fairness, and practical relevance in modern selection systems.