@inproceedings{parrish-etal-2024-picture,
title = "Is a picture of a bird a bird? A mixed-methods approach to understanding diverse human perspectives and ambiguity in machine vision models",
author = "Parrish, Alicia and
Hao, Susan and
Laszlo, Sarah and
Aroyo, Lora",
editor = "Abercrombie, Gavin and
Basile, Valerio and
Bernadi, Davide and
Dudy, Shiran and
Frenda, Simona and
Havens, Lucy and
Tonelli, Sara",
booktitle = "Proceedings of the 3rd Workshop on Perspectivist Approaches to NLP (NLPerspectives) @ LREC-COLING 2024",
month = may,
year = "2024",
address = "Torino, Italia",
publisher = "ELRA and ICCL",
url = "https://aclanthology.org/2024.nlperspectives-1.1",
pages = "1--18",
abstract = "Human experiences are complex and subjective. This subjectivity is reflected in the way people label images for machine vision models. While annotation tasks are often assumed to deliver objective results, this assumption does not allow for the subjectivity of human experience. This paper examines the implications of subjective human judgments in the behavioral task of labeling images used to train machine vision models. We identify three primary sources of ambiguity: (1) depictions of labels in the images can be simply ambiguous, (2) raters{'} backgrounds and experiences can influence their judgments and (3) the way the labeling task is defined can also influence raters{'} judgments. By taking steps to address these sources of ambiguity, we can create more robust and reliable machine vision models.",
}
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<abstract>Human experiences are complex and subjective. This subjectivity is reflected in the way people label images for machine vision models. While annotation tasks are often assumed to deliver objective results, this assumption does not allow for the subjectivity of human experience. This paper examines the implications of subjective human judgments in the behavioral task of labeling images used to train machine vision models. We identify three primary sources of ambiguity: (1) depictions of labels in the images can be simply ambiguous, (2) raters’ backgrounds and experiences can influence their judgments and (3) the way the labeling task is defined can also influence raters’ judgments. By taking steps to address these sources of ambiguity, we can create more robust and reliable machine vision models.</abstract>
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%0 Conference Proceedings
%T Is a picture of a bird a bird? A mixed-methods approach to understanding diverse human perspectives and ambiguity in machine vision models
%A Parrish, Alicia
%A Hao, Susan
%A Laszlo, Sarah
%A Aroyo, Lora
%Y Abercrombie, Gavin
%Y Basile, Valerio
%Y Bernadi, Davide
%Y Dudy, Shiran
%Y Frenda, Simona
%Y Havens, Lucy
%Y Tonelli, Sara
%S Proceedings of the 3rd Workshop on Perspectivist Approaches to NLP (NLPerspectives) @ LREC-COLING 2024
%D 2024
%8 May
%I ELRA and ICCL
%C Torino, Italia
%F parrish-etal-2024-picture
%X Human experiences are complex and subjective. This subjectivity is reflected in the way people label images for machine vision models. While annotation tasks are often assumed to deliver objective results, this assumption does not allow for the subjectivity of human experience. This paper examines the implications of subjective human judgments in the behavioral task of labeling images used to train machine vision models. We identify three primary sources of ambiguity: (1) depictions of labels in the images can be simply ambiguous, (2) raters’ backgrounds and experiences can influence their judgments and (3) the way the labeling task is defined can also influence raters’ judgments. By taking steps to address these sources of ambiguity, we can create more robust and reliable machine vision models.
%U https://aclanthology.org/2024.nlperspectives-1.1
%P 1-18
Markdown (Informal)
[Is a picture of a bird a bird? A mixed-methods approach to understanding diverse human perspectives and ambiguity in machine vision models](https://aclanthology.org/2024.nlperspectives-1.1) (Parrish et al., NLPerspectives-WS 2024)
ACL