Innovations in Assessment
The Human Capital Solutions workgroup at AIR has been conducting applied research in employment assessment since 1950. In the last few decades, we have witnessed a sea change in the assessment space due to the advent of technology and artificial intelligence (AI). Our team of industrial and organizational psychologists, research methodologist/quantitative researchers, and data scientists, therefore, is dedicated to exploring, researching, and implementing AI-based assessments.
Stemming from our research and applied work is our keen understanding of:
- Considerations to establish automatic item generation (AIG) infrastructure within organization’s testing program;
- Factors to consider when exploring AI assessments and how to evaluate vendors against this process;
- Common challenges in operationally implementing AI assessments, and methods to overcome them; and
- Critical elements that impact whether to adopt or delay AI in a testing program.
Our groundwork has afforded us the technical knowhow to guide current and prospective clients who are considering AIG for their assessment needs, as well as prepared us for larger scale research on the state of AI in the assessment industry.
We understand that AI assessments must meet the same rigorous legal and regulatory criteria that traditional assessments do, and we are particularly attuned to the risks of algorithmic bias. We pay special attention to diversity, equity, inclusion, and access (DEIA) in our assessment research, development, and evaluation.
We have been doing research related to using AI and assessments and have substantial familiarity with what is happening in the field of assessments with respect to AI.
Presentations from Our Experts
Belwalkar, B. B. (Chair) & Curnow, C. (Moderator) (2023, March). Is Automatic Item Generation (AIG) Right for Your Testing Program? Panel discussion presented at the Innovations in Assessment annual conference of the Association of Test Publishers, Dallas, TX, United States.
Belwalkar, B. B. (Co-Chair) & Curnow, C. (Co-Chair) (2022, April). Leveraging Data Science and Machine Learning for Enhancing I O Tools and Processes Symposium. Symposium presented at of the 37th annual conference of the Society of Industrial and Organizational Psychology, Seattle, WA, United States.