Principled Frameworks for Evaluating Ethics in NLP Systems

Shrimai Prabhumoye, Elijah Mayfield, Alan W Black

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.
Anthology ID:
W19-3637
Volume:
Proceedings of the 2019 Workshop on Widening NLP
Month:
August
Year:
2019
Address:
Florence, Italy
Editors:
Amittai Axelrod, Diyi Yang, Rossana Cunha, Samira Shaikh, Zeerak Waseem
Venue:
WiNLP
SIG:
Publisher:
Association for Computational Linguistics
Note:
Pages:
118–121
Language:
URL:
https://aclanthology.org/W19-3637
DOI:
Bibkey:
Cite (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.
Cite (Informal):
Principled Frameworks for Evaluating Ethics in NLP Systems (Prabhumoye et al., WiNLP 2019)
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