Artificial Intelligence for I-O Psychologists : Research and Applications

著者名：Thompson, Isaac (EDT)/Yankov, Georgi P. (EDT)/Hernandez, Ivan (EDT)

Oxford University Press（2026/06/09発売）

• 言語：ENG
• ISBN：9780197807279
• eISBN：9780197807286

Description

Artificial Intelligence for I-O Psychologists: Research and Applications is the first comprehensive handbook dedicated to helping industrial-organizational psychologists navigate, understand, and shape the rapidly evolving landscape of artificial intelligence in the world of work. Edited by Georgi P. Yankov, Isaac Thompson, and Ivan Hernandez, this volume brings together 31 chapters written by 81 leading scholars, practitioners, technologists, and policy experts. Its purpose is clear: to provide authoritative, scientifically grounded, and practice-oriented guidance on how AI is transforming assessment, organizational research, and talent management-and how I-O psychologists can lead this transformation responsibly.The handbook is organized into five sections that mirror the major domains in which AI is reshaping I-O psychology. The opening section offers historical context, emerging trends, and theoretical foundations, explaining why AI represents a paradigm shift for the field. Subsequent sections explore how AI is revolutionizing assessment development and scoring, from automated interviews and simulations to generative item creation and novel data types. Additional chapters examine AI's influence on organizational psychology topics such as leadership development, coaching, DEI initiatives, teamwork with AI agents, workplace monitoring, stress, and access to work.A major focus of the handbook is equipping I-O psychologists to collaborate effectively with data scientists and engineers. Chapters introduce readers to product development methods, MLOps, evaluation and audit frameworks, and AI-enabled approaches to research design. The final section addresses the ethical, legal, and regulatory implications of AI-based HR technologies, offering practical guidance for ensuring fairness, transparency, and compliance in high-stakes organizational contexts.Throughout the volume, contributors balance innovation with scientific rigor, offering both critical commentary and practical tools. Readers will find roadmaps for adopting AI responsibly, frameworks for validating AI-based scores, and insights into future trends that will define the next decade of work psychology.

Table of Contents

Chapter 1 - Editorial ChapterIsaac Thompson, Georgi P. Yankov, and Ivan HernandezChapter 2 - History of Technological Shifts and Their Impact on I-O PsychologyMichael J. Zickar, Feng GuoChapter 3 - Artificial Intelligence and Computation in the Social Sciences A Paradigm ShiftRyan L. Boyd, Santosh Srinivas, Shruti Phadke, Steven R. Wilson, and Paola PascaChapter 4- Overview of AI in IO PsychologyEmily D. Campion, Michael A. CampionChapter 5 - The Future of Work in the AI Era What Changes and What EnduresNilima Ajaikumar, Reece Akhtar, and Tomas Chamorro-PremuzicChapter 6 - Establishing Reliability and Validity Evidence for AI-Based ScoresAndrew B. Speer, Frederick L. Oswald, and Dan J. PutkaChapter 7 - Overview of AI-Scored Interview and Psychometric EvidenceNikki Dudley, Josh Liff, Gema Ruiz de Huydobro,Cari Gardner, Colin Willis, Caleb Rottman, Nathan MondragonChapter 8 - Using Artificial Intelligence to Develop, Score, and Administer SimulationsLouis HickmanChapter 9 - Personality Assessment and AIRyne A. ShermanChapter 10 - Automatic Item Generation, Evaluation, and Scale Construction of Non-Cognitive Measures with Generative Language ModelsMartin C. Yu and Maura I. BurkeChapter 11 - Coaching and Artificial IntelligenceHunter T. Black, Kyle Sandell, Rainy Gu, & Karina SakanakaChapter 12 - Leadership Development and Artificial IntelligenceChristopher Coughlin and David DayChapter 13 - Artificial Intelligence and Performance ManagementAnn-Marie Johnson and Reese HaydonChapter 14 - Preparing for a New Era of TeamworkLindsay Larson and Alexandra Harrison-WatsonChapter 15 - Health and Stress and AIMindy Shoss, Tara Behrend, Hannah Crandell, and Meaghan TracyChapter 16 - Exploring DEI Through the Lens of Artificial IntelligenceAmal Chekili and Yasmine ElfekiChapter 17 - Implications of AI for Workplace Monitoring and PrivacyBenjamin D. Blachly, Mahtab Shafiei, Theophilus K. Kyeremateng, and Daniel M. RavidChapter 18 - Leveraging AI Technology to Enhance Access to WorkTeresa L. Ristow and Olivia J. SmithChapter 19 - Evolution, not RevolutionChristopher J. L. Cunningham and Shawn Bergman Chapter 20 - How to Get Started with AIData Science in IO PsychologyScott Tonidandel, Betsy Albritton, Divya Doshi, Joe BradleyChapter 21 - Using Artificial Intelligence with New Data Types Reliability, Validity, Practicality, and EthicsRichard N. Landers, Saron Demeke, Vivien LeeChapter 22 - How to Collaborate with Engineers and Data ScientistsNick Koenig and Daniel SchmerlingChapter 23 - Science in SprintsPhilip Walmsley and Mengqiao LiuChapter 24 - AI and I-O Collaboration for Research-backed Product DevelopmentNeil Morelli, Jon Willford, Ryan McCreedy, Nikki Blacksmith and Dane WagnerChapter 25 - Introduction to MLOPs for Industrial-Organizational PsychologistsDerek MracekChapter 26 - Choosing a Selection Vendor in the AI Age Anthony S. Boyce and Christine E. BoyceChapter 27 - A Proposal for Embracing AI-based Assessment ResponsiblyEric J. Sydell and Ketaki SodhiChapter 28 - An introduction to explainable AI applications for I-O psychologyBradley D. Pitcher and Pengda WangChapter 29 - The EEOC and AINick TruxalChapter 30 - AI Evaluations and AuditsCari MillerChapter 31 - Regulating Artificial IntelligenceBre Timko and Dave Schmidt