Algorithmic Intrusion: The Erosion of Personal Privacy in Digital Age

Authors

  • Shuqi Chen

DOI:

https://doi.org/10.54097/8y3u8ddj

Keywords:

Data economy, Algorithms, Privacy erosion, Data collection

Abstract

In the era of global electronicization, the digital transformation of communication technology has led to the widespread collection and storage of personal information in the databases of online services, raising concerns about personal privacy. Companies use algorithms to collect and analyze this data and effectively predict user behavior to optimize services and drive profit growth. However, with the rapid development of the data economy and the increase in the scale of data collection, it has become increasingly difficult for the media to manage privacy, the boundaries of personal privacy have gradually blurred, and the public's concerns about privacy have also increased. This paper will take algorithms, the primary driving force of the data economy, as the starting point to analyze how algorithms invade personal privacy through recommender systems, advertising target, and social media functions, and how they use this private data to influence users' perceptions and behaviors.

References

Ariadna Matamoros-Fernández, Joanne E. Gray, Louisa Bartolo, Jean Burgess, & Nicolas Suzor. (2021). What’s “Up Next”? Investigating Algorithmic Recommendations on YouTube Across Issues and Over Time. Media and Communication, 9(4), 234–249.

https://doi.org/10.17645/mac.v9i4.4184.

Balleys, C., & Coll, S. (2017). Being publicly intimate: teenagers managing online privacy. Media, Culture and Society, 39(6), 885–901.

https://doi.org/10.1177/0163443716679033.

Bartlett, M. (2021). Beyond Privacy: Protecting Data Interests in the Age of Artificial Intelligence. Law, Technology and Humans, 3(Issue 1), 96–108.

Bucher, T. (2017). The algorithmic imaginary: exploring the ordinary affects of Facebook algorithms. Information Communication and Society, 20(1), 30–44.

https://doi.org/10.1080/1369118X.2016.1154086.

Carpentieri, B., Castiglione, A., De Santis, A., Palmieri, F., & Pizzolante, R. (2022). Privacy-preserving Secure Media Streaming for Multi-user Smart Environments. ACM Transactions on Internet Technology, 22(2).

https://doi.org/10.1145/3423047.

Coll, S. (2014). Power, knowledge, and the subjects of privacy: Understanding privacy as the ally of surveillance. Information Communication and Society, 17(10), 1250–1263.

https://doi.org/10.1080/1369118X.2014.918636.

DW.com. (2019, July 13). US regulators approve $5 billion Facebook fine. Deutsche Welle.

https://www.dw.com/en/facebook-faces-5-billion-fine-over-privacy-violations/a-49575702.

Elvy, S.-A. (2017). Paying for Privacy and the Personal Data Economy. Columbia Law Review, 117(Issue 6), 1369–1460.

Ghosh, I., & Singh, V. (2022). “Not all my friends are friends”: Audience‐group‐based nudges for managing location privacy. Journal of the Association for Information Science & Technology, 73(6), 797–810.

https://doi.org/10.1002/asi.24580.

Imana, B., Korolova, A., & Heidemann, J. (2022). Having your Privacy Cake and Eating it Too: Platform-supported Auditing of Social Media Algorithms for Public Interest. Proceedings of the ACM on Human-Computer Interaction 7, CSCW1, Article 134 (April 2023), 33 Pages.

https://doi.org/10.1145/3579610.

Klinger, U., & Svensson, J. (2018). The End of Media Logics? On Algorithms and Agency. New Media and Society, 20(12), 4653–4670.

https://doi.org/10.1177/1461444818779750.

Khoo, O. (2023). Picturing Diversity: Netflix’s Inclusion Strategy and the Netflix Recommender Algorithm (NRA). TELEVISION & NEW MEDIA, 24(3), 281–297.

https://doi.org/10.1177/15274764221102864.

Lovink, G. (2008). The society of the query and the Googlization of our lives: a tribute to Joseph Weizenbaum. Karlsruhe institute of technology.

Liu, Y., Tse, W. K., Kwok, P. Y., & Chiu, Y. H. (2022). Impact of Social Media Behavior on Privacy Information Security Based on Analytic Hierarchy Process. Information (2078-2489), 13(6), 280.

https://doi.org/10.3390/info13060280.

Miao, R., & Li, B. (2022). A user-portraits-based recommendation algorithm for traditional short video industry and security management of user privacy in social networks. Technological Forecasting & Social Change, 185.

https://doi.org/10.1016/j.techfore.2022.122103.

Pajkovic, N. (2022). Algorithms and taste-making: Exposing the Netflix Recommender System’s operational logics. Convergence, 28(1), 214–235.

https://doi.org/10.1177/13548565211014464.

Rauhofer, J. (2008). Privacy Is Dead, Get over It: Information Privacy and the Dream of a Risk-Free Society. Information & Communications Technology Law, 17(Issue 3), 185–198.

Westin, A. F. (2003). Social and Political Dimensions of Privacy. Journal of Social Issues, 59(2), 431–453.

https://doi.org/10.1111/1540-4560.00072.

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Published

29-07-2024

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Section

Articles

How to Cite

Chen, S. (2024). Algorithmic Intrusion: The Erosion of Personal Privacy in Digital Age. Journal of Computing and Electronic Information Management, 13(3), 4-7. https://doi.org/10.54097/8y3u8ddj