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The willingness of crowds: cohort disclosure preferences for personally identifying information

The willingness of crowds: cohort disclosure preferences for personally identifying information
The willingness of crowds: cohort disclosure preferences for personally identifying information
Exploiting personal identifying information (PII) is critical for secure access to digital and web-based systems, it is also a significant element of the online social media business model. However, how this exploitation relates to users’ valuation of their PII is poorly understood as an individual’s willingness to disclose items of PII in different situations is unknown. For instance, an individual may delight in accessing their smart- phone using facial recognition, yet they may hesitate when accessing banking services or vice versa. Moreover, the actual cost of disclosure gets obfuscated within dense and lengthy policies in a manner designed to exploit additional data. Thus, an individual may not understand that systems such as facial recognition can be a gateway to infer further PII.

Even with respectful intentions, identity-dependent technologies face a myriad of challenges to transparently balance users’ sensitivities with their own need for high veracity PII. In a novel application of the ELO ranking algorithm, we de- tail a frugal and scalable method of capturing and combining some of these sensitivities. The design involves a set of 33 items of PII, and a cohort (N = 115) divided into three contexts: expression (35), transaction (40) and submission (40). The results indicate that while individuals may have many differences, as a cohort the personal utility of PII still collates and forms distinct clusters of PII that relate within and across contexts. This result means that technologies that treat PII as one amorphous group, and those transferring PII across contexts, risk failing to adhere to the sensitivities of the user. However, by working with these cohort-based clusters in mind, it is plausible that system designers and policymakers may better appropriate system needs with the wants of the individual.
2162-3449
01
358-368
AAAI Press
Marmion, Vincent, Joseph
ad75e553-1b07-4673-8e79-7ff268a9e59d
Millard, David
4f19bca5-80dc-4533-a101-89a5a0e3b372
Gerding, Enrico
d9e92ee5-1a8c-4467-a689-8363e7743362
Stevenage, Sarah
493f8c57-9af9-4783-b189-e06b8e958460
Marmion, Vincent, Joseph
ad75e553-1b07-4673-8e79-7ff268a9e59d
Millard, David
4f19bca5-80dc-4533-a101-89a5a0e3b372
Gerding, Enrico
d9e92ee5-1a8c-4467-a689-8363e7743362
Stevenage, Sarah
493f8c57-9af9-4783-b189-e06b8e958460

Marmion, Vincent, Joseph, Millard, David, Gerding, Enrico and Stevenage, Sarah (2019) The willingness of crowds: cohort disclosure preferences for personally identifying information. In Proceedings of the Thirteenth International Conference on Web and Social Media. vol. 13, AAAI Press. pp. 358-368 .

Record type: Conference or Workshop Item (Paper)

Abstract

Exploiting personal identifying information (PII) is critical for secure access to digital and web-based systems, it is also a significant element of the online social media business model. However, how this exploitation relates to users’ valuation of their PII is poorly understood as an individual’s willingness to disclose items of PII in different situations is unknown. For instance, an individual may delight in accessing their smart- phone using facial recognition, yet they may hesitate when accessing banking services or vice versa. Moreover, the actual cost of disclosure gets obfuscated within dense and lengthy policies in a manner designed to exploit additional data. Thus, an individual may not understand that systems such as facial recognition can be a gateway to infer further PII.

Even with respectful intentions, identity-dependent technologies face a myriad of challenges to transparently balance users’ sensitivities with their own need for high veracity PII. In a novel application of the ELO ranking algorithm, we de- tail a frugal and scalable method of capturing and combining some of these sensitivities. The design involves a set of 33 items of PII, and a cohort (N = 115) divided into three contexts: expression (35), transaction (40) and submission (40). The results indicate that while individuals may have many differences, as a cohort the personal utility of PII still collates and forms distinct clusters of PII that relate within and across contexts. This result means that technologies that treat PII as one amorphous group, and those transferring PII across contexts, risk failing to adhere to the sensitivities of the user. However, by working with these cohort-based clusters in mind, it is plausible that system designers and policymakers may better appropriate system needs with the wants of the individual.

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More information

Published date: 7 June 2019
Venue - Dates: International AAAI Conference on Web and Social Media, , Munich, Germany, 2019-06-11 - 2019-06-14

Identifiers

Local EPrints ID: 431893
URI: http://eprints.soton.ac.uk/id/eprint/431893
ISSN: 2162-3449
PURE UUID: 9c1f7145-0195-4c9d-a55c-cd1317455e97
ORCID for David Millard: ORCID iD orcid.org/0000-0002-7512-2710
ORCID for Enrico Gerding: ORCID iD orcid.org/0000-0001-7200-552X
ORCID for Sarah Stevenage: ORCID iD orcid.org/0000-0003-4155-2939

Catalogue record

Date deposited: 20 Jun 2019 16:30
Last modified: 17 Mar 2024 03:03

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Contributors

Author: Vincent, Joseph Marmion
Author: David Millard ORCID iD
Author: Enrico Gerding ORCID iD
Author: Sarah Stevenage ORCID iD

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