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    <abstract>We critique recent work on ethics in natural language processing. Those discussions have focused on data collection, experimental design, and interventions in modeling. But we argue that we ought to first understand the frameworks of ethics that are being used to evaluate the fairness and justice of algorithmic systems. Here, we begin that discussion by outlining deontological and consequentialist ethics, and make predictions on the research agenda prioritized by each.</abstract>
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%0 Conference Proceedings
%T Principled Frameworks for Evaluating Ethics in NLP Systems
%A Prabhumoye, Shrimai
%A Mayfield, Elijah
%A Black, Alan W.
%Y Axelrod, Amittai
%Y Yang, Diyi
%Y Cunha, Rossana
%Y Shaikh, Samira
%Y Waseem, Zeerak
%S Proceedings of the 2019 Workshop on Widening NLP
%D 2019
%8 August
%I Association for Computational Linguistics
%C Florence, Italy
%F prabhumoye-etal-2019-principled
%X We critique recent work on ethics in natural language processing. Those discussions have focused on data collection, experimental design, and interventions in modeling. But we argue that we ought to first understand the frameworks of ethics that are being used to evaluate the fairness and justice of algorithmic systems. Here, we begin that discussion by outlining deontological and consequentialist ethics, and make predictions on the research agenda prioritized by each.
%U https://aclanthology.org/W19-3637/
%P 118-121

Markdown (Informal)

[Principled Frameworks for Evaluating Ethics in NLP Systems](https://aclanthology.org/W19-3637/) (Prabhumoye et al., WiNLP 2019)

• Principled Frameworks for Evaluating Ethics in NLP Systems (Prabhumoye et al., WiNLP 2019)

ACL

• Shrimai Prabhumoye, Elijah Mayfield, and Alan W Black. 2019. Principled Frameworks for Evaluating Ethics in NLP Systems. In Proceedings of the 2019 Workshop on Widening NLP, pages 118–121, Florence, Italy. Association for Computational Linguistics.