AI-Based Assessment Webinar Panel

AI-based Assessment: Promises, Progress, and Pitfalls

Artificial Intelligence (AI) assessment applications are becoming ubiquitous in testing and assessment in healthcare, education, and business, but there is still much to learn about how AI can enhance or hamper the assessment process in these contexts. The goal of this intermediate-level program is to provide researchers and practitioners an opportunity to learn more about the advantages and disadvantages of using AI-based assessment from five psychologists representing different fields of psychology. This workshop is co-hosted by Buros Center for Testing and UNL MAP Academy. Continuing education credits are available (2.5 credit hours). See CE Sponsor approvals.

Learning Objectives

At the end of this presentation, participants will be able to:

  1. Describe at least three advantages and disadvantages of AI-based assessments.
  2. Apply recommendations and cautions for utilizing AI-based assessment in research or professional practice.
  3. Identify research that is still needed to support the use of AI-based assessment as an evidence-based practice.


Professional educators, clinicians/counselors, industrial/organizational psychologists, measurement professionals, researchers, and graduate students

Program Recording

CLICK HERE to access the recording of the webinar.

Questions: Dr. Jessica Jonson

presenter panel

Kristen DiCerbo class=

Kristen DiCerbo, PhD

Chief Learning Officer

Khan Academy

Qiwei Britt He class=

Qiwei (Britt) He, PhD

Associate Professor, Interdisciplinary Program of Data Science and Analytics

Georgetown University

Ivan Hernandez

Ivan Hernandez, PhD

Assistant Professor, Industrial-Organizational Psychology

Virginia Tech

Richard Landers

Richard Landers, PhD

Professor, Industrial-Organizational Psychology

University of Minnesota

Matteo Malgaroli

Matteo Malgaroli, PhD

Assistant Professor, Psychiatry

NYU Grossman School of Medicine