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:
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Ensuring that results, protocols, and documentation have been archived or otherwise transmitted to the larger organization.
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.
1 position, graduate student, half-time at 20 hours/week. The details of the work arrangement are negotiable, but the position is envisioned to be telework, with the possibility of occasional in-person meetings on the NIST Gaithersburg campus.
Tagged as: Life Sciences
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