Research

A Framework for Valid and Reliable Audits of Biases in Large Language Models

Funded by American Family Funding Initiative

Research Overview

This research explores translanguaging in AI-assisted classrooms.

Objectives

  • Understand how students switch languages while learning.
  • Build AI tools that adapt to language diversity.
  • Enable equitable education through tech.

Image Example

TRAIL Lab Logo

Dataset Sample

{
  "student_id": "abc123",
  "language": "Spanglish",
  "utterance": "Yo pienso que the Earth orbits el sol."
}

Inline code like const x = 5 is also supported.

Results Table

Metric Value
Accuracy 93.5%
Precision 91.2%
Recall 92.7%

External Resources

Future Work

  1. Expand model support for additional languages.
  2. Partner with more bilingual schools.
  3. Publish findings in academic venues.

Generated on: June 19, 2025