Differential Item Functioning for AI-Scored Assessments R package aiDIF version 0.1.0 Detects and quantifies differential item functioning (DIF) in AI-scored educational and psychological assessments. Provides a fully self-contained robust DIF engine (M-estimation via iteratively re-weighted least squares with the bi-square loss) alongside the novel Differential AI Scoring Bias (DASB) test, which detects item-level scoring shifts that differ across subgroups when comparing human and AI scoring conditions. Includes simulation utilities, anchor weight diagnostics, and an AI-effect classification framework. Software Depends: R (>= 3.5.0) Imports: Matrix, stats, graphics Suggests: mirt, testthat (>= 3.0.0), knitr, rmarkdown Subir Hait <haitsubi@msu.edu> Comprehensive R Archive Network (CRAN) Subir Hait [aut, cre] (ORCID: <https://orcid.org/0009-0004-9871-9677>) GPL (>= 3) 2026-04-21 application/tgz https://CRAN.R-project.org/package=aiDIF doi:10.32614/CRAN.package.aiDIF