Post Bachelor
The National Institute of Standards and Technology (NIST) is developing human-centered approaches to
AI evaluation through research on perceptions and use of AI systems. Human-centered evaluations of AI
systems depend on a variety of methods for capturing and measuring interactions between humans and
AI systems. The candidate will assist in designing and executing human-AI interaction research. The
candidate will actively participate in NIST measurement science and be involved in developing human-
centered evaluations of AI technologies. The candidate will work alongside world-class researchers at
NIST.
Human-Centered AI Research and Evaluation
The individual must have the following minimum knowledge, skills, and abilities.
- Background in any of the following or comparable fields: Computer Science, Human-Computer
Interaction (HCI), Industrial/Organizational (I/O) Psychology, Cognitive Psychology, Human
Factors/Engineering Psychology, Psychometrics, Economics. - Education level: graduate student or higher.
- Strong background in quantitative and/or qualitative research methodology.
- Experience with human subjects research on AI use and adoption.
- Programming skills and experience creating tools for human-centered AI evaluation.
- Knowledge/interest in human-computer interaction and human-AI interaction.
- Knowledge/interest in machine learning and AI test and evaluation.
- Ability to work both in teams and independently.
- Strong oral and written communication skills.
Key responsibilities will include but are not limited to:
- Design/conduct human-subject studies (experimental design, surveys, and/or interviews).
- Conduct data analysis of human-subject experiments, surveys and/or interview data using
inferential statistical methods and qualitative thematic and grounded theory analysis - Perform literature surveys relevant to HCAI, human-AI interaction, and AI evaluation
- Develop infrastructure and approaches for human-centered AI evaluation
- Write/prepare reports, research papers, and presentations of project information at internal and
external meetings