As artificial intelligence (AI) transforms the assessment space, professionals seek innovative ways to harness its potential. This seminar deep dives into strategic applications of AI across the assessment lifecycle, empowering attendees to harness its potential.
This seminar addresses critical considerations for AI-enabled assessment, including validity arguments, bias, transparency, and regulatory compliance. Attendees will gain practical knowledge to enhance their assessment practices, streamline processes, and improve outcomes. By advancing the science of assessment through AI, this seminar supports the evolving needs of I-O psychologists and assessment professionals.
Presenters

Dr. Rachel Dreibelbis is currently a manager of Talent Strategy at Booz Allen Hamilton, where she leads comprehensive talent selection and management initiatives in the digital battlespace function. In her current role, she also serves as a workforce advisor for foreign nations. Dr. Dreibelbis is a seasoned expert in talent assessment and workforce strategy, with nearly a decade of experience working in technical, consulting, and government organizations driving innovation in assessment development. Previously, in her role at Meta, Dr. Dreibelbis led global talent selection initiatives to develop and implement assessments for technical and nontechnical populations, and spearheaded research to demonstrate the impact of generative AI on the accuracy and efficiency of assessment development. She has developed two award-winning, high-fidelity assessments for selection and has extensive knowledge and experience applying and developing national technical workforce frameworks to drive workforce development policy. Dr. Dreibelbis’ prior research has focused on the intersection of human performance and technology, and she has published numerous book chapters exploring the impact of assessment innovation on technical workforce selection and development. Dr. Dreibelbis received her MA and PhD in Industrial-Organizational Psychology from the University of South Florida in Tampa, FL.

Dr. Tianjun Sun is an assistant professor of Industrial-Organizational Psychology and Quantitative Methods in the Department of Psychological Sciences at Rice University School of Social Sciences. Before joining Rice, Dr. Sun was an assistant professor at Kansas State University for 3 years. Dr. Sun received her PhD in Industrial/Personality Psychology from University of Illinois Urbana-Champaign in 2021. Prior to the doctorate, she also obtained from Illinois her bachelor’s and master’s degrees in both Psychology and Statistics. Dr. Sun’s research primarily focuses on personnel selection, individual differences, psychometrics, and using advanced technology and quantitative methods to enhance staffing decisions, improve candidate/employee experiences, and solve organizational problems. Dr. Sun is actively publishing in reputable and high-impact journal outlets, and her projects have received support from the National Science Foundation (NSF), the National Institutes of Health (NIH), and the Society for Industrial and Organizational Psychology (SIOP) Foundation. Dr. Sun was recognized as a Rising Star by the Association for Psychological Science (APS) and has received a series of awards from SIOP, the American Psychological Association (APA), and the Academy of Management (AOM). Dr. Sun served as an Editorial Fellow 2023-2024 and now is a contributing editor at Journal of Applied Psychology and is on the editorial boards of Organizational Research Methods, Human Performance, and Journal of Business and Psychology. On the applied side, Dr. Sun has broad experience working in consulting, testing, and tech industries, as well as in areas of people analytics, learning and assessment, and talent management.

Dr. David Dorsey is currently a vice president with the Human Resources Research Organization (HumRRO). Dr. Dorsey is an accomplished organizational psychologist and former senior executive with the U.S. Department of Defense. During his time in government and in external consulting work, Dr. Dorsey has worked extensively with a wide range of organizations to develop and field assessment, training, and certification-related interventions, including systems for mission critical positions. Dr. Dorsey also previously served in government as a directorate level senior data scientist, helping to build corporate level data science platforms and communities. Dr. Dorsey has produced over 70 book chapters, articles, and presentations. He has conducted innovative research and development in the areas of understanding adaptive performance, innovating performance management, using modeling and simulation technologies for learning, understanding career paths, and building corporate approaches to modern data science, including AI. He is the recipient of two major research awards and an award for being a top leader in government. In 2017, Dr. Dorsey was elected a Fellow by the Society for Industrial and Organizational Psychology. Dr. Dorsey recently served as a committee member for the National Academies of Sciences, Engineering, and Medicine, working on an effort related to foreign language assessment for the U.S. State Department’s Foreign Service Institute.
Intended Audience
Intermediate. Business coaching experience and some familiarity with artificial intelligence and machine learning concepts are helpful, but neither is required. Solid understanding of basic concepts and methodologies about assessment development and validation principles as well as a basic understanding and introductory-level experience with Generative AI.
Learning Objectives
- Identify at least five strategic applications of generative AI.
- Develop and apply at least three advanced prompting techniques to generate high-quality assessment items using generative AI tools.
- Evaluate AI-generated assessment content using established frameworks and psychometric principles.
- Conduct AI-driven reporting and visualization with at least one business analytics tool (e.g., Tableau, Power BI).
- Construct customized generative AI chatbots tailored for at least two assessment tasks, such as item creation or results interpretation.
Topic
2025 Annual Conference
Date
April 4, 2025
Time
8:30 a.m. - 11:30 a.m.
Delivery Type
In-Person
Certification Type
Continuing Education (CE)
Workshop Coordinator
Wenmo Kong, Meta Platforms
Associated Resources
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