Research Fellowship in AI and the Law

Stanford University provides pay ranges representing its good faith estimate of the hourly wage the university reasonably expects to pay for a position upon hire. The pay offered to a selected candidate will be determined based on factors such as the scope and responsibilities of the position, qualifications, departmental budget availability, internal equity, geographic location, and external market pay for comparable jobs.

Pay

$29.52 to $34.13 per hour

Schedule

Full-time, fixed-term for one year with the intention to renew for a second year, subject to approval. The fellow is expected to be physically present and working from Stanford Law School.

About the Role

This research fellowship provides opportunities to assist the Legal Innovation through Frontier Technology Lab (liftlab), jointly led by Professor Julian Nyarko and Dr. Megan Ma, in its research on AI and other legal technological developments. The fellowship is aimed at recent graduates considering entering a graduate degree program (Ph.D. / JD) in the near future. The first two fellows have gone on to pursue PhDs at MIT and Harvard, respectively, as well as a JD at Stanford.

Examples of Current Projects

• Improving contract drafting practices by identifying litigation-triggering language
• Developing a benchmark to compare rubrics and preference ranks as a method to elicit quality in high-judgment domains
• Developing and experimentally testing LLM-based interventions to improve negotiation outcomes
• LLM personalization to improve downstream outcomes
• Large-scale evaluation of AI tutors for law
• Developing a methodology to predict future innovations in the social sciences
• Auditing and mitigation of bias in LLMs via pruning

Responsibilities

• Designing methods to validate data to ensure high-quality output
• Identifying new sources of data and methods to improve data collection, analysis, and reporting
• Conceptualization and implementation of statistical models
• Collecting, managing, and structuring quantitative datasets
• Report writing and manuscript preparation
• Using LLM agents for the implementation and execution of research
• Plan and perform research tasks requiring initiative and judgment by applying basic knowledge and understanding of scientific theory when precedents do not provide specific guidance
• Participate in the development and administration of survey instruments and rating scales requiring judgment in applying non-routine procedures
• Analyze and summarize results for review with supervisor
• Audit the accuracy and validity of data
• Review and audit case report forms for completion and accuracy with source documents, ensuring compliance with research protocols
• Identify, select, extract, and summarize data and structured information
• Conduct literature searches, and write literature summaries and manuscripts
• Build and organize data as requested by principal investigator or supervisor
• Adapt new, nonstandard methods outlined by supervisor in designing and evaluating phases of research projects
• Assist with development, communication, and design of research findings to internal and external audiences
• May orient and train new staff or students

Requirements

• Bachelor of Arts degree in an applicable social science-related field, or combination of education and relevant experience in an applicable social science

Qualifications

Minimum

• General understanding of scientific theory and methods, typically gained through completion of an undergraduate degree in a related field
• General computer skills and ability to quickly learn and master computer programs
• Ability to work under deadlines with general guidance
• Excellent organizational skills and demonstrated ability to complete detailed work accurately
• Effective oral and written communication skills
• Ability to work with human study participants

Preferred

• A Bachelor’s degree in a relevant field
• Experience with statistics
• Programming experience
• Experience and knowledge of the following is highly desirable:
  • A Bachelor’s degree in computer science with a background in NLP, a Bachelor’s degree in (computational) linguistics, or in symbolic systems
  • A strong, demonstrated interest in conducting academic research in a relevant field
  • Interest in legal research
  • Interest in causal inference and social science
  • Experience with machine learning / deep learning
  • Substantial experience with Python
  • Substantial experience with R