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pro vyhledávání: '"Vecchione, Briana"'
Autor:
Wright, Lucas, Muenster, Roxana Mike, Vecchione, Briana, Qu, Tianyao, Pika, Cai, Investigators, COMM/INFO 2450 Student, Metcalf, Jacob, Matias, J. Nathan
In July 2023, New York City became the first jurisdiction globally to mandate bias audits for commercial algorithmic systems, specifically for automated employment decisions systems (AEDTs) used in hiring and promotion. Local Law 144 (LL 144) require
Externí odkaz:
http://arxiv.org/abs/2406.01399
Audits are critical mechanisms for identifying the risks and limitations of deployed artificial intelligence (AI) systems. However, the effective execution of AI audits remains incredibly difficult. As a result, practitioners make use of various tool
Externí odkaz:
http://arxiv.org/abs/2402.17861
In July 2023, New York City (NYC) initiated the first algorithm auditing system for commercial machine-learning systems. Local Law 144 (LL 144) mandates NYC-based employers using automated employment decision-making tools (AEDTs) in hiring to undergo
Externí odkaz:
http://arxiv.org/abs/2402.08101
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
Externí odkaz:
http://arxiv.org/abs/2401.14462
Algorithmic audits have been embraced as tools to investigate the functioning and consequences of sociotechnical systems. Though the term is used somewhat loosely in the algorithmic context and encompasses a variety of methods, it maintains a close c
Externí odkaz:
http://arxiv.org/abs/2109.06974
Autor:
Nazari, Zahra, Charbuillet, Christophe, Pages, Johan, Laurent, Martin, Charrier, Denis, Vecchione, Briana, Carterette, Ben
Recommender systems are increasingly used to predict and serve content that aligns with user taste, yet the task of matching new users with relevant content remains a challenge. We consider podcasting to be an emerging medium with rapid growth in ado
Externí odkaz:
http://arxiv.org/abs/2007.13287
Autor:
Gebru, Timnit, Morgenstern, Jamie, Vecchione, Briana, Vaughan, Jennifer Wortman, Wallach, Hanna, Daumé III, Hal, Crawford, Kate
The machine learning community currently has no standardized process for documenting datasets, which can lead to severe consequences in high-stakes domains. To address this gap, we propose datasheets for datasets. In the electronics industry, every c
Externí odkaz:
http://arxiv.org/abs/1803.09010
Autor:
GEBRU, TIMNIT, MORGENSTERN, JAMIE, VECCHIONE, BRIANA, VAUGHAN, JENNIFER WORTMAN, WALLACH, HANNA, III, HAL DAUMÉ, CRAWFORD, KATE
Publikováno v:
Communications of the ACM; Dec2021, Vol. 64 Issue 12, p86-92, 7p, 1 Color Photograph
Akademický článek
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