PREP0003674 Human and LLM Annotations for AI Risk Assessment Researcher

PREP Research Associate

Opportunity No.: PREP0003674

This position is part of the National Institute of Standards and Technology (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, and 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.

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Human and LLM Annotations for AI Risk Assessment Researcher

Project Description:

Reliability of Human and LLM Annotations for AI Risk Assessment: This project focuses on using Large Language Models (LLMs) to provide annotations of evaluation data (a.k.a., LLM as judge), and the design of an Inter-Annotator Agreement study to assess the reliability of both human and LLM annotations. The candidate will explore assessing the indicators of a given AI-related risk, determining how to identify them, and providing annotators with examples to annotate the presence of various risks. The project aims to develop an annotation framework for AI risk assessment and establish metrics for data quality in AI risk research, supporting broader work at NIST in assessing and measuring the validity and reliability of AI-related risks in data annotation.

Key Responsibilities: 

• Gain familiarity with existing literature on data annotation and LLM as a judge
• Understand NIST’s role and ongoing efforts in assessing and measuring the validity and reliability of AI-related risks in data annotation
• Contribute to developing an annotation framework for AI risk assessment
• Collaborate effectively with cross-functional and interdisciplinary stakeholders to ensure successful project outcomes
• Contributions to a NIST report that supports ongoing NIST AI evaluation efforts focused on the design of an Inter-Annotator Agreement to assess the reliability of both human and LLM annotations

Desired Qualifications: 

• Undergraduate or graduate student in Computer Science, Data Science, or a related field
• Strong interest in data annotation and AI risks
• Familiarity with scientific reading and technical writing

Other Details:

• Part-time: the participant is expected to work 20 hours a week
• Location: Hybrid - the participant will work at the NIST Gaithersburg Campus and telework.
• Duration: this is expected to be a one-year position. Extensions are sometimes granted depending on the availability of funds.
• For questions related to the research project or the nature of the work in this position, please contact Dr. Mark A. Przybocki (mark.przybocki@nist.gov). For questions related to the online application or NIST PREP more generally, please contact msu-nistprep@morgan.edu.

Privacy Act Statement

Authority: 15 U.S.C. § 278g-1(e)(1) and (e)(3) and 15 U.S.C. § 272(b) and (c)

Purpose: The National Institute for Standards and Technology (NIST) hosts the Professional Research Experience Program (PREP) which is designed to provide valuable laboratory experience and financial assistance to undergraduates, post-bachelor’s degree holders, graduate students, master’s degree holders, postdocs, and faculty.

PREP is a 5-year cooperative agreement between NIST laboratories and participating PREP Universities to establish a collaborative research relationship between NIST and U.S. institutions of higher education in the following disciplines including (but may not be limited to) biochemistry, biological sciences, chemistry, computer science, engineering, electronics, materials science, mathematics, nanoscale science, neutron science, physical science, physics, and statistics. This collection of information is needed to facilitate the administrative functions of the PREP Program.

Routine Uses: NIST will use the information collected to perform the requisite reviews of the applications to determine eligibility, and to meet programmatic requirements. Disclosure of this information is also subject to all the published routine uses as identified in the Privacy Act System of Records Notices: NIST-1: NIST Associates.

Disclosure: Furnishing this information is voluntary. When you submit the form, you are indicating your voluntary consent for NIST to use the information you submit for the purpose stated.