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Ethical Recommenders in the Public Library Sector

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Savvina DaniilAuthors Info & Claims

AIES '22: Proceedings of the 2022 AAAI/ACM Conference on AI, Ethics, and Society

Page 895

https://doi.org/10.1145/3514094.3539536

Published: 27 July 2022 Publication History

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Abstract

Recommender Systems as an algorithmic class hide lurking risks despite their prevalence in academic and commercial circles. My specific research revolves around tracking and mitigating potential risks specifically in the Public Library domain. In collaboration with the National Library of The Netherlands, I am working on investigating whether the incorporation of Recommenders in a library's loaning system serves their social responsibility and purpose, with securing inclusivity being the main point of interest.

References

[1]

Himan Abdollahpouri, Masoud Mansoury, Robin Burke, and Bamshad Mobasher. 2019. The Unfairness of Popularity Bias in Recommendation. RecSys Workshop on Recommendation in Multistakeholder Environments (RMSE); Conference date: 20-09--2019.

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Dominik Kowald, Markus Schedl, and Elisabeth Lex. 2020. The Unfairness of Popularity Bias in Music Recommendation: A Reproducibility Study. In Advances in Information Retrieval, Joemon M. Jose, Emine Yilmaz, Jo ao Magalh aes, Pablo Castells, Nicola Ferro, Mário J. Silva, and Flávio Martins (Eds.). Springer International Publishing, Cham, 35--42.

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Silvia Milano, Mariarosaria Taddeo, and Luciano Floridi. 2020. Recommender systems and their ethical challenges. Ai & Society, Vol. 35, 4 (2020), 957--967.

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Mohammadmehdi Naghiaei, Hossein A. Rahmani, and Mahdi Dehghan. 2022. The Unfairness of Popularity Bias in Book Recommendation. https://doi.org/10.48550/ARXIV.2202.13446

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Jan Willem Van Wessel. 2020. AI in Libraries: Seven Principles. (May 2020). https://doi.org/10.5281/zenodo.3865344

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Cai-Nicolas Ziegler, Sean M McNee, Joseph A Konstan, and Georg Lausen. 2005. Improving recommendation lists through topic diversification. In Proceedings of the 14th international conference on World Wide Web. 22--32.

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Published In

AIES '22: Proceedings of the 2022 AAAI/ACM Conference on AI, Ethics, and Society

July 2022

939 pages

ISBN:9781450392471

DOI:10.1145/3514094

General Chairs:
Vincent Conitzer
Duke University & University of Oxford
,
John Tasioulas
University of Oxford
,
Program Chairs:
Matthias Scheutz
Tufts University
,
Ryan Calo
University of Washington
,
Martina Mara
Johannes Kepler University Linz
,
Annette Zimmermann
University of York

Permission to make digital or hard copies of part or all of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for third-party components of this work must be honored. For all other uses, contact the Owner/Author.

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Association for Computing Machinery

New York, NY, United States

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Published: 27 July 2022

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AIES '22

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SIGAI

AIES '22: AAAI/ACM Conference on AI, Ethics, and Society

May 19 - 21, 2021

Oxford, United Kingdom

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Recommendations

Ethical Governance of Emerging Digital Technologies in the Public Sector: Insights from Dutch Digital Ethics Commissions

The Public Library's Role in Enabling E-Government: A View of Two Countries in the English-Speaking Caribbean

Technology adoption in the public sector: an exploratory study of e-government in Malaysia

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