DeepAudit deploys advanced machine learning tools to analyze large volumes of educational materials for ideological content that undermines academic excellence and institutional neutrality.
Our capabilities to examine in-depth and at scale include:
Course Descriptions | Lesson Plans | Curricula | Syllabi | Grants | Websites | Journal Articles | Meeting Minutes | State Standards | Laws | Policies | Strategic Plans | Reports | Budgets | Assessments
Material Identification: We use data science techniques to collect and process education materials for analysis (e.g., K-12 curricula, university policies, educator training powerpoints).
Semantic Search: Our machine learning agent scores each material based on its similarity to ideological reference materials.
Human Review: Our analysts review the highest-scoring sections to verify which ones are genuine instances of the ideology in question.
Reporting: We produce clear, actionable reports identifying which materials warrant review or revision, along with reform recommendations tailored to your needs.
AI Startup Reveals DEI-Related Language Embedded in Maine Education Laws (April 3rd, 2025)
DeepAudit DEI in Education Law Maine (March, 31 2025)
UT Austin Education School Dominated by Leftwing Ideology, Report Finds (March 19th, 2025)
DeepAudit Press Release (March, 15 2025)
DeepAudit UT Austin College of Education (March 2025)
DeepAudit Florida Gulf Coast University Vice Provost Search (March 2025)
DeepAudit FGCU VP Search Press Release (March 2025)
DeepAudit/Rasmussen Semantic Similarity as an Auditing Tool (December 2024)