ORCID: https://orcid.org/0000-0003-1419-7425; Khamis, Mohamed
ORCID: https://orcid.org/0000-0001-7051-5200; Mathis, Florian
ORCID: https://orcid.org/0000-0002-1690-3410; Irmscher, Diana
ORCID: https://orcid.org/0000-0002-0641-5835; Sood, Ekta
ORCID: https://orcid.org/0000-0002-6267-7151; Bulling, Andreas
ORCID: https://orcid.org/0000-0001-6317-7303 und Schmidt, Albrecht
ORCID: https://orcid.org/0000-0003-3890-1990
(2023):
Impact of Privacy Protection Methods of Lifelogs on Remembered Memories.
CHI conference on Human Factors in Computing Systems (CHI), Hamburg, Germany, 23. - 28. April 2023.
Schmidt, Albrecht
ORCID: https://orcid.org/0000-0003-3890-1990 (Hrsg.):
In: Proceedings of the 2023 CHI Conference on Human Factors in Computing Systems,
508
New York: Association for Computing Machinery. S. 1-10
Abstract
Lifelogging is traditionally used for memory augmentation. However, recent research shows that users’ trust in the completeness and accuracy of lifelogs might skew their memories. Privacy-protection alterations such as body blurring and content deletion are commonly applied to photos to circumvent capturing sensitive information. However, their impact on how users remember memories remain unclear. To this end, we conduct a white-hat memory attack and report on an iterative experiment (N=21) to compare the impact of viewing 1) unaltered lifelogs, 2) blurred lifelogs, and 3) a subset of the lifelogs after deleting private ones, on confidently remembering memories. Findings indicate that all the privacy methods impact memories’ quality similarly and that users tend to change their answers in recognition more than recall scenarios. Results also show that users have high confidence in their remembered content across all privacy methods. Our work raises awareness about the mindful designing of technological interventions.
Dokumententyp: | Konferenzbeitrag (Paper) |
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Fakultät: | Mathematik, Informatik und Statistik > Informatik |
Themengebiete: | 000 Informatik, Informationswissenschaft, allgemeine Werke > 004 Informatik |
ISBN: | 978-1-4503-9421-5 |
Ort: | New York |
Sprache: | Englisch |
Dokumenten ID: | 123738 |
Datum der Veröffentlichung auf Open Access LMU: | 17. Feb. 2025 11:41 |
Letzte Änderungen: | 17. Feb. 2025 11:41 |