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Investigating Google dashboard's explainability to support individual privacy decision making

Published: 22 October 2019 Publication History

Abstract

Advances in information technology often overwhelm users with complex privacy and security decisions. They make the collection and use of personal data quite invisible. In the current scenario, this data collection can introduce risks, manipulate and influence the decision making process. This research is based on concepts from an emerging field of study called Human Data Interaction (HDI), which proposes to include the human at the center of the data stream, providing mechanisms for citizens to interact explicitly with the collected data. We explored the explanation as a promising mechanism for transparency in automated systems. In the first step, we apply the Semiotic Inspection Method (SIM) longitudinally to investigate how using explanations as an interactive feature can help or prevent users from making privacy decisions on Google services. In the second step, we conducted an empirical study in which users are able to analyze whether these explanations are satisfactory and feel (un) secure in the decision making process. And by comparing the results of the two steps, we find that even in a large company like Google, the right to explanation is not guaranteed. Google does not make its data processing transparent to users, nor does it provide satisfactory explanations of how its services use individual data. Consequently, the lack of coherent, detailed and transparent explanations hamper users to make good and safe decisions.

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Cited By

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  • (2023)Encouraging learners to seek and explain communicability issues about Consent RequestProceedings of the XXII Brazilian Symposium on Human Factors in Computing Systems10.1145/3638067.3638097(1-11)Online publication date: 16-Oct-2023
  • (2020)Systemic view of human-data interactionProceedings of the 19th Brazilian Symposium on Human Factors in Computing Systems10.1145/3424953.3426655(1-6)Online publication date: 26-Oct-2020

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      cover image ACM Other conferences
      IHC '19: Proceedings of the 18th Brazilian Symposium on Human Factors in Computing Systems
      October 2019
      679 pages
      ISBN:9781450369718
      DOI:10.1145/3357155
      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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      Publication History

      Published: 22 October 2019

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      Author Tags

      1. data control
      2. decision making
      3. explanation
      4. privacy

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      IHC '19
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      IHC '19: XVIII Brazilian Symposium on Human Factors in Computing Systems
      October 22 - 25, 2019
      Espírito Santo, Vitória, Brazil

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      IHC '19 Paper Acceptance Rate 56 of 165 submissions, 34%;
      Overall Acceptance Rate 331 of 973 submissions, 34%

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      View all
      • (2023)Encouraging learners to seek and explain communicability issues about Consent RequestProceedings of the XXII Brazilian Symposium on Human Factors in Computing Systems10.1145/3638067.3638097(1-11)Online publication date: 16-Oct-2023
      • (2020)Systemic view of human-data interactionProceedings of the 19th Brazilian Symposium on Human Factors in Computing Systems10.1145/3424953.3426655(1-6)Online publication date: 26-Oct-2020

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