Technologies for Trustworthy Machine Learning: A Survey in a Socio-Technical Context

17 July 2020

Papers citing "Technologies for Trustworthy Machine Learning: A Survey in a Socio-Technical Context"

9 / 9 papers shown

Title
Trust in AI and Implications for the AEC Research: A Literature Analysis Newsha Emaminejad Alexander North Reza Akhavian 13 14 0 08 Mar 2022
A Survey on AI Assurance Feras A. Batarseh Laura J. Freeman 29 65 0 15 Nov 2021
A Survey on Bias and Fairness in Machine Learning Ninareh Mehrabi Fred Morstatter N. Saxena Kristina Lerman Aram Galstyan SyDa FaML 323 4,203 0 23 Aug 2019
Improving fairness in machine learning systems: What do industry practitioners need? Kenneth Holstein Jennifer Wortman Vaughan Hal Daumé Miroslav Dudík Hanna M. Wallach FaML HAI 192 742 0 13 Dec 2018
Methods for Interpreting and Understanding Deep Neural Networks G. Montavon Wojciech Samek K. Müller FaML 234 2,238 0 24 Jun 2017
Towards A Rigorous Science of Interpretable Machine Learning Finale Doshi-Velez Been Kim XAI FaML 251 3,683 0 28 Feb 2017
A statistical framework for fair predictive algorithms K. Lum J. Johndrow FaML 177 104 0 25 Oct 2016
Fair prediction with disparate impact: A study of bias in recidivism prediction instruments Alexandra Chouldechova FaML 207 2,082 0 24 Oct 2016
Adversarial examples in the physical world Alexey Kurakin Ian Goodfellow Samy Bengio SILM AAML 284 5,835 0 08 Jul 2016