'End to End' Towards a Framework for Reducing Biases and Promoting Transparency of Algorithmic Systems

Avital Shulner Tal; Khuyagbaatar Batsuren; Veronika Bogina; Fausto Giunchiglia; Alan Hartman; Styliani Kleanthous Loizou; Tsvi Kuflik; Jahna Otterbacher

doi:10.1109/SMAP.2019.8864914

'End to End' Towards a Framework for Reducing Biases and Promoting Transparency of Algorithmic Systems

Avital Shulner Tal, Khuyagbaatar Batsuren, Veronika Bogina, Fausto Giunchiglia, Alan Hartman, Styliani Kleanthous Loizou, Tsvi Kuflik, Jahna Otterbacher

Department of Information Systems

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

Abstract

Algorithms play an increasing role in our everyday lives. Recently, the harmful potential of biased algorithms has been recognized by researchers and practitioners. We have also witnessed a growing interest in ensuring the fairness and transparency of algorithmic systems. However, so far there is no agreed upon solution and not even an agreed terminology. The proposed research defines the problem space, solution space and a prototype of comprehensive framework for the detection and reducing biases in algorithmic systems.

Original language	English
Title of host publication	2019 14th International Workshop on Semantic and Social Media Adaptation and Personalization, SMAP 2019
Publisher	Institute of Electrical and Electronics Engineers Inc.
ISBN (Electronic)	9781728136349
DOIs	https://doi.org/10.1109/SMAP.2019.8864914
State	Published - Jun 2019
Event	14th International Workshop on Semantic and Social Media Adaptation and Personalization, SMAP 2019 - Larnaka, Cyprus Duration: 9 Jun 2019 → 10 Jun 2019

Publication series

Name	2019 14th International Workshop on Semantic and Social Media Adaptation and Personalization, SMAP 2019

Conference

Conference	14th International Workshop on Semantic and Social Media Adaptation and Personalization, SMAP 2019
Country/Territory	Cyprus
City	Larnaka
Period	9/06/19 → 10/06/19

Bibliographical note

Publisher Copyright:
© 2019 IEEE.

Keywords

Algorithmic Systems
Bias
Diversity
Fairness
Transparency

ASJC Scopus subject areas

Media Technology
Social Sciences (miscellaneous)
Communication
Computer Networks and Communications

Access to Document

10.1109/SMAP.2019.8864914

Cite this

Tal, A. S., Batsuren, K., Bogina, V., Giunchiglia, F., Hartman, A., Loizou, S. K., Kuflik, T., & Otterbacher, J. (2019). 'End to End' Towards a Framework for Reducing Biases and Promoting Transparency of Algorithmic Systems. In 2019 14th International Workshop on Semantic and Social Media Adaptation and Personalization, SMAP 2019 Article 8864914 (2019 14th International Workshop on Semantic and Social Media Adaptation and Personalization, SMAP 2019). Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.1109/SMAP.2019.8864914

Tal, Avital Shulner ; Batsuren, Khuyagbaatar ; Bogina, Veronika et al. / 'End to End' Towards a Framework for Reducing Biases and Promoting Transparency of Algorithmic Systems. 2019 14th International Workshop on Semantic and Social Media Adaptation and Personalization, SMAP 2019. Institute of Electrical and Electronics Engineers Inc., 2019. (2019 14th International Workshop on Semantic and Social Media Adaptation and Personalization, SMAP 2019).

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title = "'End to End' Towards a Framework for Reducing Biases and Promoting Transparency of Algorithmic Systems",

abstract = "Algorithms play an increasing role in our everyday lives. Recently, the harmful potential of biased algorithms has been recognized by researchers and practitioners. We have also witnessed a growing interest in ensuring the fairness and transparency of algorithmic systems. However, so far there is no agreed upon solution and not even an agreed terminology. The proposed research defines the problem space, solution space and a prototype of comprehensive framework for the detection and reducing biases in algorithmic systems.",

keywords = "Algorithmic Systems, Bias, Diversity, Fairness, Transparency",

author = "Tal, {Avital Shulner} and Khuyagbaatar Batsuren and Veronika Bogina and Fausto Giunchiglia and Alan Hartman and Loizou, {Styliani Kleanthous} and Tsvi Kuflik and Jahna Otterbacher",

note = "Publisher Copyright: {\textcopyright} 2019 IEEE.; 14th International Workshop on Semantic and Social Media Adaptation and Personalization, SMAP 2019 ; Conference date: 09-06-2019 Through 10-06-2019",

year = "2019",

month = jun,

doi = "10.1109/SMAP.2019.8864914",

language = "English",

series = "2019 14th International Workshop on Semantic and Social Media Adaptation and Personalization, SMAP 2019",

publisher = "Institute of Electrical and Electronics Engineers Inc.",

booktitle = "2019 14th International Workshop on Semantic and Social Media Adaptation and Personalization, SMAP 2019",

address = "United States",

}

Tal, AS, Batsuren, K, Bogina, V, Giunchiglia, F, Hartman, A, Loizou, SK, Kuflik, T & Otterbacher, J 2019, 'End to End' Towards a Framework for Reducing Biases and Promoting Transparency of Algorithmic Systems. in 2019 14th International Workshop on Semantic and Social Media Adaptation and Personalization, SMAP 2019., 8864914, 2019 14th International Workshop on Semantic and Social Media Adaptation and Personalization, SMAP 2019, Institute of Electrical and Electronics Engineers Inc., 14th International Workshop on Semantic and Social Media Adaptation and Personalization, SMAP 2019, Larnaka, Cyprus, 9/06/19. https://doi.org/10.1109/SMAP.2019.8864914

'End to End' Towards a Framework for Reducing Biases and Promoting Transparency of Algorithmic Systems. / Tal, Avital Shulner; Batsuren, Khuyagbaatar; Bogina, Veronika et al.
2019 14th International Workshop on Semantic and Social Media Adaptation and Personalization, SMAP 2019. Institute of Electrical and Electronics Engineers Inc., 2019. 8864914 (2019 14th International Workshop on Semantic and Social Media Adaptation and Personalization, SMAP 2019).

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

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AU - Giunchiglia, Fausto

AU - Hartman, Alan

AU - Loizou, Styliani Kleanthous

AU - Kuflik, Tsvi

AU - Otterbacher, Jahna

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AB - Algorithms play an increasing role in our everyday lives. Recently, the harmful potential of biased algorithms has been recognized by researchers and practitioners. We have also witnessed a growing interest in ensuring the fairness and transparency of algorithmic systems. However, so far there is no agreed upon solution and not even an agreed terminology. The proposed research defines the problem space, solution space and a prototype of comprehensive framework for the detection and reducing biases in algorithmic systems.

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Tal AS, Batsuren K, Bogina V, Giunchiglia F, Hartman A, Loizou SK et al. 'End to End' Towards a Framework for Reducing Biases and Promoting Transparency of Algorithmic Systems. In 2019 14th International Workshop on Semantic and Social Media Adaptation and Personalization, SMAP 2019. Institute of Electrical and Electronics Engineers Inc. 2019. 8864914. (2019 14th International Workshop on Semantic and Social Media Adaptation and Personalization, SMAP 2019). doi: 10.1109/SMAP.2019.8864914

'End to End' Towards a Framework for Reducing Biases and Promoting Transparency of Algorithmic Systems

Abstract

Publication series

Conference

Bibliographical note

Keywords

ASJC Scopus subject areas

Access to Document

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