Work

Should We Ban English NLP for a Year?

Year: 2022

Type: conference-paper

Abstract: Around two thirds of NLP research at top venues is devoted exclusively to developing technology for speakers of English, most speech data comes from young urban speakers, and most texts used to train language models come from male writers.These biases feed into consumer technologies to widen existing inequality gaps, not only within, but also across, societies.Many have argued that it is almost impossible to mitigate inequality amplification.I argue that, on the contrary, it is quite simple to do so, and that counter-measures would have little-to-no negative impact, except for, perhaps, in the very short term.

Source: Conference on Empirical Methods in Natural Language Processing (EMNLP)

DOI: 10.18653/v1/2022.emnlp-main.351

Author: Anders Søgaard

Institution: University of Copenhagen

Language: English

Topic: Ethics and Social Impacts of AI

Subfield: Safety Research

Field: Social Sciences

Domain: Social Sciences

SDG: Reduced inequalities

Open Access status: hybrid

OpenAlex ID: W4385573554