Keeping Community in the Loop: Understanding Wikipedia Stakeholder
Values for Machine Learning-Based Systems

Keeping Community in the Loop: Understanding Wikipedia Stakeholder Values for Machine Learning-Based Systems

14 January 2020

Anjali Srivastava

Aaron L Halfaker

Loren G. Terveen

Haiyi Zhu

Papers citing "Keeping Community in the Loop: Understanding Wikipedia Stakeholder Values for Machine Learning-Based Systems"

5 / 5 papers shown

Title
Summaries, Highlights, and Action items: Design, implementation and evaluation of an LLM-powered meeting recap system Sumit Asthana Sagi Hilleli Pengcheng He Aaron L Halfaker 62 11 0 28 Jul 2023
Improving Human-AI Partnerships in Child Welfare: Understanding Worker Practices, Challenges, and Desires for Algorithmic Decision Support Anna Kawakami Venkatesh Sivaraman H. Cheng Logan Stapleton Yanghuidi Cheng Diana Qing Adam Perer Zhiwei Steven Wu Haiyi Zhu Kenneth Holstein 48 109 0 05 Apr 2022
The Frontiers of Fairness in Machine Learning Alexandra Chouldechova Aaron Roth FaML 46 413 0 20 Oct 2018
A comparative study of fairness-enhancing interventions in machine learning Sorelle A. Friedler C. Scheidegger Suresh Venkatasubramanian Sonam Choudhary Evan P. Hamilton Derek Roth FaML 62 639 0 13 Feb 2018
Surviving an "Eternal September" - How an Online Community Managed a Surge of Newcomers C. Kiene Andrés Monroy-Hernández Benjamin Mako Hill 16 94 0 28 May 2016

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