AIGovernance: Statistical Auditing and Governance Reporting for Employment AI Systems

Provides statistical auditing, risk documentation, and reporting tools to support AI governance workflows for employment and hiring decision systems. Implements the EEOC four-fifths adverse impact rule (Equal Employment Opportunity Commission, 1978, <https://www.ecfr.gov/current/title-29/subtitle-B/chapter-XIV/part-1607>), NYC Local Law 144 bias audit requirements (New York City, 2023, <https://www.nyc.gov/site/dca/about/automated-employment-decision-tools.page>), and the AI Risk Management Framework checklist items from the National Institute of Standards and Technology (2023, <doi:10.6028/NIST.AI.100-1>). Optionally supports EU AI Act high-risk classification (European Parliament and Council, 2024, <https://eur-lex.europa.eu/legal-content/EN/TXT/?uri=CELEX:32024R1689>). The package does not provide legal advice or certify legal compliance; it is a statistical and documentation support tool.

Version:	0.1.0
Depends:	R (≥ 4.1.0)
Imports:	cli, rlang, stats, tibble, dplyr
Suggests:	ggplot2, knitr, rmarkdown, testthat (≥ 3.0.0)
Published:	2026-05-27
DOI:	10.32614/CRAN.package.AIGovernance
Author:	Subir Hait [aut, cre]
Maintainer:	Subir Hait <haitsubi at msu.edu>
BugReports:	https://github.com/causalfragility-lab/AIGovernance/issues
License:	MIT + file LICENSE
URL:	https://github.com/causalfragility-lab/AIGovernance
NeedsCompilation:	no
Language:	en-US
Materials:	README, NEWS
CRAN checks:	AIGovernance results

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