research-article

"I had no idea this was a thing": on the importance of understanding the user experience of personalized transparency tools

Authors:

Jessica StaddonAuthors Info & Claims

STAST '16: Proceedings of the 6th Workshop on Socio-Technical Aspects in Security and Trust

Pages 79 - 86

https://doi.org/10.1145/3046055.3046062

Published: 05 December 2016 Publication History

Abstract

Personalization has the potential to improve the effectiveness of "generic" privacy notices and policies, however, little is known about the user impact of the personalized transparency tools available today. While regulators consistently endorse transparency, the popular press often couches existing tools in negative and cautionary tones. In a pilot study of two personalized online transparency tools, Google's My Activity and Google Ads Settings, we find the user experience of these tools is difficult to study due to low user-awareness and limited user data accessible to the tools. However, for those users with sufficient data accessible to the tools, we find no evidence that these tools are harmful to user trust and privacy attitudes.

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Cited By

Reitinger NWen BMazurek MUr BKnijnenburg BPapadimitratos P(2023)Analysis of Google Ads Settings Over Time: Updated, Individualized, Accurate, and FilteredProceedings of the 22nd Workshop on Privacy in the Electronic Society10.1145/3603216.3624968(167-172)Online publication date: 26-Nov-2023
https://dl.acm.org/doi/10.1145/3603216.3624968
Sun YSong QGui XMa FWang T(2023)AutoML in The Wild: Obstacles, Workarounds, and ExpectationsProceedings of the 2023 CHI Conference on Human Factors in Computing Systems10.1145/3544548.3581082(1-15)Online publication date: 19-Apr-2023
https://dl.acm.org/doi/10.1145/3544548.3581082
Goray CSchoenebeck S(2022)Youths' Perceptions of Data Collection in Online Advertising and Social MediaProceedings of the ACM on Human-Computer Interaction10.1145/35555766:CSCW2(1-27)Online publication date: 11-Nov-2022
https://dl.acm.org/doi/10.1145/3555576
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cover image ACM Other conferences

STAST '16: Proceedings of the 6th Workshop on Socio-Technical Aspects in Security and Trust

December 2016

101 pages

ISBN:9781450348263

DOI:10.1145/3046055

General Chairs:
Gabriele Lenzini
SnT/University of Luxembourg, LU
,
Giampaolo Bella
University of Catania, IT
,
Program Chairs:
Zinaida Benenson
University of Erlangen-Nuremberg
,
Carrie Gates

Copyright © 2016 ACM.

Permission to make digital or hard copies of all or part 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 components of this work owned by others than ACM must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from [email protected]

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Association for Computing Machinery

New York, NY, United States

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Published: 05 December 2016

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STAST '16

STAST '16: Socio-Technical Aspects in Security and Trust

December 5, 2016

California, Los Angeles

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Cited By

Reitinger NWen BMazurek MUr BKnijnenburg BPapadimitratos P(2023)Analysis of Google Ads Settings Over Time: Updated, Individualized, Accurate, and FilteredProceedings of the 22nd Workshop on Privacy in the Electronic Society10.1145/3603216.3624968(167-172)Online publication date: 26-Nov-2023
https://dl.acm.org/doi/10.1145/3603216.3624968
Sun YSong QGui XMa FWang T(2023)AutoML in The Wild: Obstacles, Workarounds, and ExpectationsProceedings of the 2023 CHI Conference on Human Factors in Computing Systems10.1145/3544548.3581082(1-15)Online publication date: 19-Apr-2023
https://dl.acm.org/doi/10.1145/3544548.3581082
Goray CSchoenebeck S(2022)Youths' Perceptions of Data Collection in Online Advertising and Social MediaProceedings of the ACM on Human-Computer Interaction10.1145/35555766:CSCW2(1-27)Online publication date: 11-Nov-2022
https://dl.acm.org/doi/10.1145/3555576
Yurrita MMurray-Rust DBalayn ABozzon A(2022)Towards a multi-stakeholder value-based assessment framework for algorithmic systemsProceedings of the 2022 ACM Conference on Fairness, Accountability, and Transparency10.1145/3531146.3533118(535-563)Online publication date: 21-Jun-2022
https://dl.acm.org/doi/10.1145/3531146.3533118

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