Guiding Principles for Participatory Design-inspired Natural Language Processing

Tommaso Caselli, Roberto Cibin, Costanza Conforti, Enrique Encinas, Maurizio Teli


Abstract
We introduce 9 guiding principles to integrate Participatory Design (PD) methods in the development of Natural Language Processing (NLP) systems. The adoption of PD methods by NLP will help to alleviate issues concerning the development of more democratic, fairer, less-biased technologies to process natural language data. This short paper is the outcome of an ongoing dialogue between designers and NLP experts and adopts a non-standard format following previous work by Traum (2000); Bender (2013); Abzianidze and Bos (2019). Every section is a guiding principle. While principles 1–3 illustrate assumptions and methods that inform community-based PD practices, we used two fictional design scenarios (Encinas and Blythe, 2018), which build on top of situations familiar to the authors, to elicit the identification of the other 6. Principles 4–6 describes the impact of PD methods on the design of NLP systems, targeting two critical aspects: data collection & annotation, and the deployment & evaluation. Finally, principles 7–9 guide a new reflexivity of the NLP research with respect to its context, actors and participants, and aims. We hope this guide will offer inspiration and a road-map to develop a new generation of PD-inspired NLP.
Anthology ID:
2021.nlp4posimpact-1.4
Volume:
Proceedings of the 1st Workshop on NLP for Positive Impact
Month:
August
Year:
2021
Address:
Online
Editors:
Anjalie Field, Shrimai Prabhumoye, Maarten Sap, Zhijing Jin, Jieyu Zhao, Chris Brockett
Venue:
NLP4PI
SIG:
Publisher:
Association for Computational Linguistics
Note:
Pages:
27–35
Language:
URL:
https://aclanthology.org/2021.nlp4posimpact-1.4
DOI:
10.18653/v1/2021.nlp4posimpact-1.4
Bibkey:
Cite (ACL):
Tommaso Caselli, Roberto Cibin, Costanza Conforti, Enrique Encinas, and Maurizio Teli. 2021. Guiding Principles for Participatory Design-inspired Natural Language Processing. In Proceedings of the 1st Workshop on NLP for Positive Impact, pages 27–35, Online. Association for Computational Linguistics.
Cite (Informal):
Guiding Principles for Participatory Design-inspired Natural Language Processing (Caselli et al., NLP4PI 2021)
Copy Citation:
PDF:
https://aclanthology.org/2021.nlp4posimpact-1.4.pdf