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Towards a Non-Ideal Methodological Framework for Responsible ML

Towards a Non-Ideal Methodological Framework for Responsible ML

20 January 2024
Ramaravind Kommiya Mothilal
Shion Guha
Syed Ishtiaque Ahmed
ArXivPDFHTML

Papers citing "Towards a Non-Ideal Methodological Framework for Responsible ML"

11 / 11 papers shown
Title
From plane crashes to algorithmic harm: applicability of safety
  engineering frameworks for responsible ML
From plane crashes to algorithmic harm: applicability of safety engineering frameworks for responsible ML
Shalaleh Rismani
Renee Shelby
A. Smart
Edgar W. Jatho
Joshua A. Kroll
AJung Moon
Negar Rostamzadeh
27
36
0
06 Oct 2022
How Different Groups Prioritize Ethical Values for Responsible AI
How Different Groups Prioritize Ethical Values for Responsible AI
Maurice Jakesch
Zana Buçinca
Saleema Amershi
Alexandra Olteanu
37
94
0
16 May 2022
Exploring How Machine Learning Practitioners (Try To) Use Fairness
  Toolkits
Exploring How Machine Learning Practitioners (Try To) Use Fairness Toolkits
Wesley Hanwen Deng
Manish Nagireddy
M. S. Lee
Jatinder Singh
Zhiwei Steven Wu
Kenneth Holstein
Haiyi Zhu
31
85
0
13 May 2022
Whose AI Dream? In search of the aspiration in data annotation
Whose AI Dream? In search of the aspiration in data annotation
Ding-wen Wang
Shantanu Prabhat
Nithya Sambasivan
166
56
0
21 Mar 2022
Fairness-aware Class Imbalanced Learning
Fairness-aware Class Imbalanced Learning
Shivashankar Subramanian
Afshin Rahimi
Timothy Baldwin
Trevor Cohn
Lea Frermann
FaML
99
28
0
21 Sep 2021
Whither AutoML? Understanding the Role of Automation in Machine Learning
  Workflows
Whither AutoML? Understanding the Role of Automation in Machine Learning Workflows
Doris Xin
Eva Yiwei Wu
D. Lee
Niloufar Salehi
Aditya G. Parameswaran
46
91
0
13 Jan 2021
A Human-Centered Review of the Algorithms used within the U.S. Child
  Welfare System
A Human-Centered Review of the Algorithms used within the U.S. Child Welfare System
Devansh Saxena
Karla A. Badillo-Urquiola
Pamela J. Wisniewski
Shion Guha
51
104
0
07 Mar 2020
Trust in Data Science: Collaboration, Translation, and Accountability in
  Corporate Data Science Projects
Trust in Data Science: Collaboration, Translation, and Accountability in Corporate Data Science Projects
Samir Passi
S. Jackson
157
108
0
09 Feb 2020
Data Vision: Learning to See Through Algorithmic Abstraction
Data Vision: Learning to See Through Algorithmic Abstraction
Samir Passi
S. Jackson
127
110
0
09 Feb 2020
Human-AI Collaboration in Data Science: Exploring Data Scientists'
  Perceptions of Automated AI
Human-AI Collaboration in Data Science: Exploring Data Scientists' Perceptions of Automated AI
Dakuo Wang
Justin D. Weisz
Michael J. Muller
Parikshit Ram
Werner Geyer
Casey Dugan
Y. Tausczik
Horst Samulowitz
Alexander G. Gray
162
312
0
05 Sep 2019
Improving fairness in machine learning systems: What do industry
  practitioners need?
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
730
0
13 Dec 2018
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