This position is part of the National Institute of Standards (NIST) Professional Research Experience (PREP) program. NIST recognizes that its research staff may wish to collaborate with researchers at academic institutions on specific projects of mutual interest, thus requires that such institutions must be the recipient of a PREP award. The PREP program requires staff from a wide range of backgrounds to work on scientific research in many areas. Employees in this position will perform technical work that underpins the scientific research of the collaboration.
Research Title:
Human-Centered AI Research: Categorizing AI Use Scenarios
NIST Researchers for PREP Watchlist:
Theodore Jensen (sponsor), Yee-Yin Choong (secondary), Kristen Greene (tertiary)
The work will entail:
The National Institute of Standards and Technology (NIST) is building a library of sector-specific scenarios to facilitate AI evaluations and measurements. These scenarios are grounded in real-world AI use cases and developed with input from the broader AI community and sector stakeholders. Well-defined key elements of scenarios will ensure AI evaluations are both realistic and effective. The PREP candidate will be responsible for assisting in gathering, refining, and documenting the AI scenario collection and generation process. The candidate will actively participate in NIST measurement science and be involved in human-centered research and evaluations of AI technologies.
Key responsibilities will include but are not limited to:
- Developing and conducting methods (e.g., interviews) to collect various AI use scenarios within an organization.
- Replicating AI use scenario collection methods with various stakeholders.
- Analyzing collected data using appropriate methods (e.g., qualitative coding, thematic analysis).
- Refining and documenting the AI scenario collection and generation process for replicability and efficient scenario library development.
- Presenting results at internal meetings and occasional meetings with external stakeholders.
- Ensuring that results, protocols, and documentation have been archived or otherwise transmitted to the larger organization.
Qualifications
- Background in any of the following or comparable fields: Human-Computer Interaction (HCI), Industrial/Organizational (I/O) Psychology, Cognitive Psychology, Human Factors/Engineering Psychology, Psychometrics, Economics, Computer Science
- Education level: graduate student.
- Strong background in research methodology with demonstrated research experience.
- Competency in quantitative and/or qualitative research and data analysis.
- 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.
The university is an Equal Employment Opportunity/Affirmative Action employer that does not unlawfully discriminate in any of its programs or activities on the basis of race, color, religion, sex, national origin, age, disability, veteran status, sexual orientation, gender identity or expression, or on any other basis prohibited by applicable law.