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

15 May 2023

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

7 / 7 papers shown

Title
Bridging the Communication Gap: Evaluating AI Labeling Practices for Trustworthy AI Development Raphael Fischer Magdalena Wischnewski Alexander van der Staay Katharina Poitz Christian Janiesch Thomas Liebig 45 0 0 21 Jan 2025
Why am I seeing this: Democratizing End User Auditing for Online Content Recommendations Chaoran Chen Leyang Li Luke Cao Yanfang Ye Tianshi Li Yaxing Yao Toby Jia-jun Li MLAU 43 2 0 07 Oct 2024
Surveys Considered Harmful? Reflecting on the Use of Surveys in AI Research, Development, and Governance Mohammmad Tahaei Daricia Wilkinson Alisa Frik Chi Lok Yu Ruba Abu-Salma Lauren Wilcox 38 3 0 26 Jul 2024
Transparent AI Disclosure Obligations: Who, What, When, Where, Why, How Abdallah El Ali Karthikeya Puttur Venkatraj Sophie Morosoli Laurens Naudts Natali Helberger Pablo César 34 14 0 11 Mar 2024
How Different Groups Prioritize Ethical Values for Responsible AI Maurice Jakesch Zana Buçinca Saleema Amershi Alexandra Olteanu 37 95 0 16 May 2022
What Do We Want From Explainable Artificial Intelligence (XAI)? -- A Stakeholder Perspective on XAI and a Conceptual Model Guiding Interdisciplinary XAI Research Markus Langer Daniel Oster Timo Speith Holger Hermanns Lena Kästner Eva Schmidt Andreas Sesing Kevin Baum XAI 43 415 0 15 Feb 2021
Formalizing Trust in Artificial Intelligence: Prerequisites, Causes and Goals of Human Trust in AI Alon Jacovi Ana Marasović Tim Miller Yoav Goldberg 244 425 0 15 Oct 2020