What we learned while automating bias detection in AI hiring systems for compliance with NYC Local Law 144
Fuente:
arXiv
Guardado en:
| Autores principales: | , |
|---|---|
| Formato: | Preprint |
| Publicado: |
2024
|
| Materias: | |
| Acceso en línea: | |
| Etiquetas: |
Agregar Etiqueta
Sin Etiquetas, Sea el primero en etiquetar este registro!
|
| _version_ | 1866910788987387904 |
|---|---|
| author | Clavell, Gemma Galdon González-Sendino, Rubén |
| author_facet | Clavell, Gemma Galdon González-Sendino, Rubén |
| contents | Since July 5, 2023, New York City's Local Law 144 requires employers to conduct independent bias audits for any automated employment decision tools (AEDTs) used in hiring processes. The law outlines a minimum set of bias tests that AI developers and implementers must perform to ensure compliance. Over the past few months, we have collected and analyzed audits conducted under this law, identified best practices, and developed a software tool to streamline employer compliance. Our tool, ITACA_144, tailors our broader bias auditing framework to meet the specific requirements of Local Law 144. While automating these legal mandates, we identified several critical challenges that merit attention to ensure AI bias regulations and audit methodologies are both effective and practical. This document presents the insights gained from automating compliance with NYC Local Law 144. It aims to support other cities and states in crafting similar legislation while addressing the limitations of the NYC framework. The discussion focuses on key areas including data requirements, demographic inclusiveness, impact ratios, effective bias, metrics, and data reliability. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2501_10371 |
| institution | arXiv |
| publishDate | 2024 |
| record_format | arxiv |
| spellingShingle | What we learned while automating bias detection in AI hiring systems for compliance with NYC Local Law 144 Clavell, Gemma Galdon González-Sendino, Rubén Computers and Society Artificial Intelligence Since July 5, 2023, New York City's Local Law 144 requires employers to conduct independent bias audits for any automated employment decision tools (AEDTs) used in hiring processes. The law outlines a minimum set of bias tests that AI developers and implementers must perform to ensure compliance. Over the past few months, we have collected and analyzed audits conducted under this law, identified best practices, and developed a software tool to streamline employer compliance. Our tool, ITACA_144, tailors our broader bias auditing framework to meet the specific requirements of Local Law 144. While automating these legal mandates, we identified several critical challenges that merit attention to ensure AI bias regulations and audit methodologies are both effective and practical. This document presents the insights gained from automating compliance with NYC Local Law 144. It aims to support other cities and states in crafting similar legislation while addressing the limitations of the NYC framework. The discussion focuses on key areas including data requirements, demographic inclusiveness, impact ratios, effective bias, metrics, and data reliability. |
| title | What we learned while automating bias detection in AI hiring systems for compliance with NYC Local Law 144 |
| topic | Computers and Society Artificial Intelligence |
| url | https://arxiv.org/abs/2501.10371 |