Certification Labels for Trustworthy AI: Insights From an Empirical Mixed-Method Study-Reference-Cited by-同舟云学术

Certification Labels for Trustworthy AI: Insights From an Empirical Mixed-Method Study

Published:2023-06-12 Issue: Volume: Page:
ISSN:
Container-title:2023 ACM Conference on Fairness, Accountability, and Transparency
language:
Short-container-title:

Author:

Scharowski Nicolas¹^ORCID,Benk Michaela²^ORCID,Kühne Swen J.³^ORCID,Wettstein Léane¹^ORCID,Brühlmann Florian¹^ORCID

Affiliation:

1. University of Basel, Center for General Psychology and Methodology, Switzerland

2. ETH Zurich, Mobiliar Lab for Analytics, Switzerland

3. Zurich University of Applied Sciences, School of Applied Psychology, Switzerland

Publisher

ACM

Link

https://dl.acm.org/doi/pdf/10.1145/3593013.3593994

Reference73 articles.

1. FactSheets: Increasing trust in AI services through supplier's declarations of conformity

2. Shahar Avin , Haydn Belfield , Miles Brundage , Gretchen Krueger , Jasmine Wang , Adrian Weller , Markus Anderljung , Igor Krawczuk , David Krueger , Jonathan Lebensold , 2021. Filling gaps in trustworthy development of AI. Science 374, 6573 ( 2021 ), 1327–1329. https://doi.org/10.1126/science.abi7176 10.1126/science.abi7176 Shahar Avin, Haydn Belfield, Miles Brundage, Gretchen Krueger, Jasmine Wang, Adrian Weller, Markus Anderljung, Igor Krawczuk, David Krueger, Jonathan Lebensold, 2021. Filling gaps in trustworthy development of AI. Science 374, 6573 (2021), 1327–1329. https://doi.org/10.1126/science.abi7176

3. Problematic Machine Behavior

4. Explainable machine learning in deployment

5. 'It's Reducing a Human Being to a Percentage'

Cited by 4 articles. 订阅此论文施引文献订阅此论文施引文献，注册后可以免费订阅5篇论文的施引文献，订阅后可以查看论文全部施引文献

1. Should Users Trust Advanced AI Assistants? Justified Trust As a Function of Competence and Alignment;The 2024 ACM Conference on Fairness, Accountability, and Transparency;2024-06-03

2. Transparent AI Disclosure Obligations: Who, What, When, Where, Why, How;Extended Abstracts of the CHI Conference on Human Factors in Computing Systems;2024-05-02

3. Trustworthiness Assurance Assessment for High-Risk AI-Based Systems;IEEE Access;2024

4. Fairness Certification for Natural Language Processing and Large Language Models;Lecture Notes in Networks and Systems;2024