@inproceedings{leidner-plachouras-2017-ethical,
title = "Ethical by Design: Ethics Best Practices for Natural Language Processing",
author = "Leidner, Jochen L. and
Plachouras, Vassilis",
editor = "Hovy, Dirk and
Spruit, Shannon and
Mitchell, Margaret and
Bender, Emily M. and
Strube, Michael and
Wallach, Hanna",
booktitle = "Proceedings of the First {ACL} Workshop on Ethics in Natural Language Processing",
month = apr,
year = "2017",
address = "Valencia, Spain",
publisher = "Association for Computational Linguistics",
url = "https://aclanthology.org/W17-1604",
doi = "10.18653/v1/W17-1604",
pages = "30--40",
abstract = "Natural language processing (NLP) systems analyze and/or generate human language, typically on users{'} behalf. One natural and necessary question that needs to be addressed in this context, both in research projects and in production settings, is the question how ethical the work is, both regarding the process and its outcome. Towards this end, we articulate a set of issues, propose a set of best practices, notably a process featuring an ethics review board, and sketch and how they could be meaningfully applied. Our main argument is that ethical outcomes ought to be achieved by design, i.e. by following a process aligned by ethical values. We also offer some response options for those facing ethics issues. While a number of previous works exist that discuss ethical issues, in particular around big data and machine learning, to the authors{'} knowledge this is the first account of NLP and ethics from the perspective of a principled process.",
}
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<abstract>Natural language processing (NLP) systems analyze and/or generate human language, typically on users’ behalf. One natural and necessary question that needs to be addressed in this context, both in research projects and in production settings, is the question how ethical the work is, both regarding the process and its outcome. Towards this end, we articulate a set of issues, propose a set of best practices, notably a process featuring an ethics review board, and sketch and how they could be meaningfully applied. Our main argument is that ethical outcomes ought to be achieved by design, i.e. by following a process aligned by ethical values. We also offer some response options for those facing ethics issues. While a number of previous works exist that discuss ethical issues, in particular around big data and machine learning, to the authors’ knowledge this is the first account of NLP and ethics from the perspective of a principled process.</abstract>
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%0 Conference Proceedings
%T Ethical by Design: Ethics Best Practices for Natural Language Processing
%A Leidner, Jochen L.
%A Plachouras, Vassilis
%Y Hovy, Dirk
%Y Spruit, Shannon
%Y Mitchell, Margaret
%Y Bender, Emily M.
%Y Strube, Michael
%Y Wallach, Hanna
%S Proceedings of the First ACL Workshop on Ethics in Natural Language Processing
%D 2017
%8 April
%I Association for Computational Linguistics
%C Valencia, Spain
%F leidner-plachouras-2017-ethical
%X Natural language processing (NLP) systems analyze and/or generate human language, typically on users’ behalf. One natural and necessary question that needs to be addressed in this context, both in research projects and in production settings, is the question how ethical the work is, both regarding the process and its outcome. Towards this end, we articulate a set of issues, propose a set of best practices, notably a process featuring an ethics review board, and sketch and how they could be meaningfully applied. Our main argument is that ethical outcomes ought to be achieved by design, i.e. by following a process aligned by ethical values. We also offer some response options for those facing ethics issues. While a number of previous works exist that discuss ethical issues, in particular around big data and machine learning, to the authors’ knowledge this is the first account of NLP and ethics from the perspective of a principled process.
%R 10.18653/v1/W17-1604
%U https://aclanthology.org/W17-1604
%U https://doi.org/10.18653/v1/W17-1604
%P 30-40
Markdown (Informal)
[Ethical by Design: Ethics Best Practices for Natural Language Processing](https://aclanthology.org/W17-1604) (Leidner & Plachouras, EthNLP 2017)
ACL