AI auditing: The Broken Bus on the Road to AI Accountability

Fuente: arXiv
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Main Authors: Birhane, Abeba, Steed, Ryan, Ojewale, Victor, Vecchione, Briana, Raji, Inioluwa Deborah
Format: Preprint
Published: 2024
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author Birhane, Abeba
Steed, Ryan
Ojewale, Victor
Vecchione, Briana
Raji, Inioluwa Deborah
author_facet Birhane, Abeba
Steed, Ryan
Ojewale, Victor
Vecchione, Briana
Raji, Inioluwa Deborah
contents One of the most concrete measures to take towards meaningful AI accountability is to consequentially assess and report the systems' performance and impact. However, the practical nature of the "AI audit" ecosystem is muddled and imprecise, making it difficult to work through various concepts and map out the stakeholders involved in the practice. First, we taxonomize current AI audit practices as completed by regulators, law firms, civil society, journalism, academia, consulting agencies. Next, we assess the impact of audits done by stakeholders within each domain. We find that only a subset of AI audit studies translate to desired accountability outcomes. We thus assess and isolate practices necessary for effective AI audit results, articulating the observed connections between AI audit design, methodology and institutional context on its effectiveness as a meaningful mechanism for accountability.
format Preprint
id arxiv_https___arxiv_org_abs_2401_14462
institution arXiv
publishDate 2024
record_format arxiv
spellingShingle AI auditing: The Broken Bus on the Road to AI Accountability
Birhane, Abeba
Steed, Ryan
Ojewale, Victor
Vecchione, Briana
Raji, Inioluwa Deborah
Computers and Society
One of the most concrete measures to take towards meaningful AI accountability is to consequentially assess and report the systems' performance and impact. However, the practical nature of the "AI audit" ecosystem is muddled and imprecise, making it difficult to work through various concepts and map out the stakeholders involved in the practice. First, we taxonomize current AI audit practices as completed by regulators, law firms, civil society, journalism, academia, consulting agencies. Next, we assess the impact of audits done by stakeholders within each domain. We find that only a subset of AI audit studies translate to desired accountability outcomes. We thus assess and isolate practices necessary for effective AI audit results, articulating the observed connections between AI audit design, methodology and institutional context on its effectiveness as a meaningful mechanism for accountability.
title AI auditing: The Broken Bus on the Road to AI Accountability
topic Computers and Society
url https://arxiv.org/abs/2401.14462