| Challenge: | aaron carroll: two thirds of NLP research is devoted to developing technology for speakers of English . carroll says this bias feeds into consumer technologies to widen existing inequality gaps . he says we need to consider more concrete measures to mitigate climate change . |
| Approach: | a new paper argues that NLP is contributing to global inequalities through a digital language divide . a carbon tax, cap-and-trade and car-free Sundays are examples of measures to mitigate climate change . |
| Outcome: | a new paper argues that NLP is contributing to global inequalities through a digital language divide . a carbon tax, cap-and-trade and car-free Sundays are examples of measures to mitigate climate change . |
Similar Papers
NLP Needs Diversity outside of ‘Diversity’ (2025.findings-emnlp)
Copied to clipboard
| Challenge: | a new position paper argues that diversity in NLP is concentrated on a small number of areas surrounding fairness . |
| Approach: | a new position paper argues that diversity in NLP is disproportionately concentrated on fairness areas. |
| Outcome: | a new position paper argues that diversity in NLP is disproportionately concentrated on fairness areas. |
Some Languages are More Equal than Others: Probing Deeper into the Linguistic Disparity in the NLP World (2022.aacl-main)
Copied to clipboard
| Challenge: | Linguistic disparity in the NLP world is widely acknowledged, but the reasons behind it are rarely discussed within the field. |
| Approach: | They propose to categorise languages based on speaker population and vitality . they also analyse the distribution of language data resources and amount of NLP/CL research . |
| Outcome: | The proposed model identifies the reasons for the disparity and suggests ways to overcome it. |
Systematic Inequalities in Language Technology Performance across the World’s Languages (2022.acl-long)
Copied to clipboard
| Challenge: | Recent studies have revealed that NLP is limited to a subset of the world’s 6,500 languages. |
| Approach: | They propose a framework for estimating the global utility of language technologies as revealed in a comprehensive snapshot of recent publications in NLP. |
| Outcome: | The proposed framework estimates the global utility of language technologies as revealed in a comprehensive snapshot of recent publications in NLP. |
Bias and Fairness in Natural Language Processing (D19-2)
Copied to clipboard
| Challenge: | a tutorial will review the history of bias and fairness studies in machine learning and language processing . |
| Approach: | This tutorial reviews the history of bias and fairness studies in machine learning and language processing . it presents recent community effort to quantify and mitigat bias in natural language processing models . |
| Outcome: | This tutorial reviews the history of bias and fairness studies in machine learning and language processing . it aims to quantify and mitigate bias in natural language processing models for a wide spectrum of tasks . |
Language (Technology) is Power: A Critical Survey of “Bias” in NLP (2020.acl-main)
Copied to clipboard
| Challenge: | 146 papers analyzing "bias" in NLP systems lack normative reasoning, we find . authors propose three recommendations for work analyzing “bias” in Nlp systems . |
| Approach: | They propose three recommendations for analyzing "bias" in NLP systems . they propose to focus on what kinds of system behaviors are harmful, in what ways, to whom, and why . |
| Outcome: | The proposed methods for measuring or mitigating “bias” are poorly matched to their motivations and do not engage critically with literature outside of NLP. |
Is NLP Ready for Standardization? (2022.findings-emnlp)
Copied to clipboard
| Challenge: | a number of scientific fields, including telecommunications, networks and multimedia, lack standards in the field of NLP. |
| Approach: | They propose to examine how NLP lacks standards and how that can impact society, industry and regulations. |
| Outcome: | The proposed standards examine the needs of NLP researchers and industry . they argue that the lack of standards can impact the field, society and industry. |
Fairness in Language Models Beyond English: Gaps and Challenges (2023.findings-eacl)
Copied to clipboard
| Challenge: | Language models are inequitable at encoding and re-presentation, but there is much to be studied and criticism for the existing research that remains to be addressed. |
| Approach: | They propose to survey fairness in multilingual and non-English contexts . they argue that it is infeasible to achieve comprehensive coverage in terms of fairness datasets based on English . |
| Outcome: | The proposed methods are infeasible to scale across languages and cultures, the authors argue . they argue that the current methods are too narrowly focused on specific dimensions and types of biases and cannot scale across cultures. |
A Major Obstacle for NLP Research: Let’s Talk about Time Allocation! (2022.emnlp-main)
Copied to clipboard
| Challenge: | Subpar time allocation has been a major obstacle for natural language processing research in recent years, argues a new position paper . |
| Approach: | They propose to identify the biggest traps the NLP community falls into and suggest solutions to solve them. |
| Outcome: | The authors outline multiple concrete problems together with their negative consequences and suggest remedies to improve the status quo. |
On the Gap between Adoption and Understanding in NLP (2021.findings-acl)
Copied to clipboard
| Challenge: | a recent paper argues that current publications foster a gap between adoption and understanding of models . it also makes it easier to meet publication demands with method papers, argues the paper . |
| Approach: | They argue that current NLP publication models foster a gap between adoption and understanding of models . they argue that everlarger models make it harder to explain how our methods work . |
| Outcome: | The authors argue that current publications foster a gap between adoption and understanding of models . they argue that the rise of everlarger models makes it harder to explain how our methods work . |
The glass ceiling in NLP (D18-1)
Copied to clipboard
| Challenge: | a glass ceiling exists within the field of NLP, but no study has examined this issue . female representation in Computer Science is lower than the average STEM field . |
| Approach: | They propose to use a mathematical model to show that a glass ceiling exists in NLP . they find that there is a growing mentor gender gap and a disparity between mentors . |
| Outcome: | The proposed model shows that a glass ceiling exists within the field of NLP since the mid 2000s. |