research-article

What Makes an Image Tagger Fair?

Authors:

Styliani Kleanthous,

Kyriakos Kyriakou,

Jahna OtterbacherAuthors Info & Claims

UMAP '19: Proceedings of the 27th ACM Conference on User Modeling, Adaptation and Personalization

Pages 95 - 103

https://doi.org/10.1145/3320435.3320442

Published: 07 June 2019 Publication History

Abstract

Image analysis algorithms have been a boon to personalization in digital systems and are now widely available via easy-to-use APIs. However, it is important to ensure that they behave fairly in applications that involve processing images of people, such as dating apps. We conduct an experiment to shed light on the factors influencing the perception of "fairness." Participants are shown a photo along with two descriptions (human- and algorithm-generated). They are then asked to indicate which is "more fair" in the context of a dating site, and explain their reasoning. We vary a number of factors, including the gender, race and attractiveness of the person in the photo. While participants generally found human-generated tags to be more fair, API tags were judged as being more fair in one setting - where the image depicted an "attractive," white individual. In their explanations, participants often mention accuracy, as well as the objectivity/subjectivity of the tags in the description. We relate our work to the ongoing conversation about fairness in opaque tools like image tagging APIs, and their potential to result in harm.

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Cited By

Pinney CRaj AHanna AEkstrand M(2023)Much Ado About GenderProceedings of the 2023 Conference on Human Information Interaction and Retrieval10.1145/3576840.3578316(269-279)Online publication date: 19-Mar-2023
https://dl.acm.org/doi/10.1145/3576840.3578316
Alexandropoulou CPanagiotopoulos IKleanthous SDimitrakopoulos GConstantinou IPoliti ENtalaperas DPapageorgiou XStylianides CIoannides NPalazis LPattichis CPanayides A(2023)AI-Enabled Solutions, Explainability and Ethical Concerns for Predicting Sepsis in ICUs: A Systematic Review2023 IEEE 19th International Conference on e-Science (e-Science)10.1109/e-Science58273.2023.10254863(1-9)Online publication date: 9-Oct-2023
https://doi.org/10.1109/e-Science58273.2023.10254863
Narayanan DNagpal MMcGuire JSchweitzer SDe Cremer D(2023)Fairness Perceptions of Artificial Intelligence: A Review and Path ForwardInternational Journal of Human–Computer Interaction10.1080/10447318.2023.221089040:1(4-23)Online publication date: 26-May-2023
https://doi.org/10.1080/10447318.2023.2210890
Show More Cited By

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What Makes an Image Tagger Fair?

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cover image ACM Conferences

UMAP '19: Proceedings of the 27th ACM Conference on User Modeling, Adaptation and Personalization

June 2019

377 pages

ISBN:9781450360210

DOI:10.1145/3320435

General Chairs:
George Angelos Papadopoulos
University of Cyprus, Cyprus
,
George Samaras
University of Cyprus, Cyprus
,
Stephan Weibelzahl
PFH Private University of Applied Sciences Göttingen, Germany
,
Program Chairs:
Dietmar Jannach
Alpen-Adria-Universität Klagenfurt, Austria
,
Olga C. Santos
aDeNu Research Group - UNED, Spain

Copyright © 2019 ACM.

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Published: 07 June 2019

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UMAP '19: 27th Conference on User Modeling, Adaptation and Personalization

June 9 - 12, 2019

Larnaca, Cyprus

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UMAP '19 Paper Acceptance Rate 30 of 122 submissions, 25%;

Overall Acceptance Rate 162 of 633 submissions, 26%

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Cited By

Pinney CRaj AHanna AEkstrand M(2023)Much Ado About GenderProceedings of the 2023 Conference on Human Information Interaction and Retrieval10.1145/3576840.3578316(269-279)Online publication date: 19-Mar-2023
https://dl.acm.org/doi/10.1145/3576840.3578316
Alexandropoulou CPanagiotopoulos IKleanthous SDimitrakopoulos GConstantinou IPoliti ENtalaperas DPapageorgiou XStylianides CIoannides NPalazis LPattichis CPanayides A(2023)AI-Enabled Solutions, Explainability and Ethical Concerns for Predicting Sepsis in ICUs: A Systematic Review2023 IEEE 19th International Conference on e-Science (e-Science)10.1109/e-Science58273.2023.10254863(1-9)Online publication date: 9-Oct-2023
https://doi.org/10.1109/e-Science58273.2023.10254863
Narayanan DNagpal MMcGuire JSchweitzer SDe Cremer D(2023)Fairness Perceptions of Artificial Intelligence: A Review and Path ForwardInternational Journal of Human–Computer Interaction10.1080/10447318.2023.221089040:1(4-23)Online publication date: 26-May-2023
https://doi.org/10.1080/10447318.2023.2210890
Orphanou KOtterbacher JKleanthous SBatsuren KGiunchiglia FBogina VTal AHartman AKuflik T(2022)Mitigating Bias in Algorithmic Systems—A Fish-eye ViewACM Computing Surveys10.1145/352715255:5(1-37)Online publication date: 3-Dec-2022
https://dl.acm.org/doi/10.1145/3527152
Oosterhuis H(2021)Learning from user interactions with rankingsACM SIGIR Forum10.1145/3483382.348340254:2(1-2)Online publication date: 20-Aug-2021
https://dl.acm.org/doi/10.1145/3483382.3483402
Li D(2021)Effective collection construction for information retrieval evaluation and optimizationACM SIGIR Forum10.1145/3483382.348340154:2(1-2)Online publication date: 20-Aug-2021
https://dl.acm.org/doi/10.1145/3483382.3483401
Roitero K(2021)Cheap IR evaluationACM SIGIR Forum10.1145/3483382.348340054:2(1-2)Online publication date: 20-Aug-2021
https://dl.acm.org/doi/10.1145/3483382.3483400
Bauer C(2021)Report on the ISMIR 2020 special sessionACM SIGIR Forum10.1145/3483382.348339854:2(1-7)Online publication date: 20-Aug-2021
https://dl.acm.org/doi/10.1145/3483382.3483398
Safavi TMeij EÖzcan FRedi MDemartini GXiong C(2021)Report on the first workshop on bias in automatic knowledge graph construction at AKBC 2020ACM SIGIR Forum10.1145/3483382.348339354:2(1-9)Online publication date: 20-Aug-2021
https://dl.acm.org/doi/10.1145/3483382.3483393
Landoni MPera MFails JMurgia EKucirkova NHuibers T(2021)4 KidRec - what does good look likeACM SIGIR Forum10.1145/3483382.348339154:2(1-7)Online publication date: 20-Aug-2021
https://dl.acm.org/doi/10.1145/3483382.3483391
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