Front matter
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pages |
A Quantitative Study of Data in the NLP community Margot Mieskes
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pp. 1–7 |
Ethical by Design: Ethics Best Practices for Natural Language Processing Jochen L. Leidner and Vassilis Plachouras
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pp. 8–18 |
These are not the Stereotypes You are Looking For: Bias and Fairness in Authorial Gender Attribution Corina Koolen and Andreas van Cranenburgh
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pp. 19–29 |
Gender as a Variable in Natural-Language Processing: Ethical Considerations Brian Larson
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pp. 30–40 |
Building Better Open-Source Tools to Support Fairness in Automated Scoring Nitin Madnani, Anastassia Loukina, Alina von Davier, Jill Burstein and Aoife Cahill
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pp. 41–52 |
Gender and Dialect Bias in YouTube’s Automatic Captions Rachael Tatman
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pp. 53–59 |
Integrating the Management of Personal Data Protection and Open Science with Research Ethics Dave Lewis, Joss Moorkens and Kaniz Fatema
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pp. 60–65 |
Ethical Considerations in NLP Shared Tasks Carla Parra Escartín, Wessel Reijers, Teresa Lynn, Joss Moorkens, Andy Way and Chao-Hong Liu
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pp. 66–73 |
Social Bias in Elicited Natural Language Inferences Rachel Rudinger, Chandler May and Benjamin Van Durme
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pp. 74–79 |
A Short Review of Ethical Challenges in Clinical Natural Language Processing Simon Suster, Stephan Tulkens and Walter Daelemans
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pp. 80–87 |
Goal-Oriented Design for Ethical Machine Learning and NLP Tyler Schnoebelen
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pp. 88–93 |
Ethical Research Protocols for Social Media Health Research Adrian Benton, Glen Coppersmith and Mark Dredze
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pp. 94–102 |
Say the Right Thing Right: Ethics Issues in Natural Language Generation Systems Charese Smiley, Frank Schilder, Vassilis Plachouras and Jochen L. Leidner
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pp. 103–108 |
Last modified on February 27, 2017, 10:53 p.m.