Package: AIGovernance
Type: Package
Title: Statistical Auditing and Governance Reporting for Employment AI
        Systems
Version: 0.1.0
Authors@R: person("Subir", "Hait",
    email = "haitsubi@msu.edu",
    role  = c("aut", "cre"),
    comment = c(ORCID = "0009-0004-9871-9677"))
Description: 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.
License: MIT + file LICENSE
Encoding: UTF-8
LazyData: true
RoxygenNote: 7.3.3
Depends: R (>= 4.1.0)
Imports: cli, rlang, stats, tibble, dplyr
Suggests: ggplot2, knitr, rmarkdown, testthat (>= 3.0.0)
VignetteBuilder: knitr
Language: en-US
URL: https://github.com/causalfragility-lab/AIGovernance
BugReports: https://github.com/causalfragility-lab/AIGovernance/issues
NeedsCompilation: no
Packaged: 2026-05-19 14:37:57 UTC; Subir
Author: Subir Hait [aut, cre] (ORCID: <https://orcid.org/0009-0004-9871-9677>)
Maintainer: Subir Hait <haitsubi@msu.edu>
Repository: CRAN
Date/Publication: 2026-05-27 09:50:07 UTC
Built: R 4.5.2; ; 2026-05-27 11:34:39 UTC; unix
