Draft:Algorithmic Sabotage
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Algorithmic sabotage is the manipulation of algorithms—particularly those used in recommender systems, content moderation, gig economy platforms, and surveillance—to disrupt their intended functionality, protect user privacy, or protest corporate and state data collection.[1]
Unlike malicious hacking or cyberwarfare, algorithmic sabotage is typically practiced by everyday users, workers, or activists as a form of everyday resistance or digital civil disobedience.[2]
Methods and tactics
[edit]Tactics of algorithmic sabotage vary based on the target platform and the objective of the users:
- Data Poisoning and Noise Generation: Users intentionally feed false, contradictory, or overwhelming amounts of data into an algorithm to dilute its predictive power. An example includes "algorithmic obfuscation," where browser extensions automatically click random ads to destroy the accuracy of user tracking profiles.[3]
- Gig Worker Coordination: Rideshare and delivery drivers have been documented collectively turning off their applications simultaneously. This fools the platform's pricing algorithm into detecting an artificial shortage of drivers, thereby triggering surge pricing before the drivers log back on to claim the higher rates.[4]
- Algorithmic Flood Protests: Activists manipulate algorithmic recommendation engines by flooding specific hashtags or audio tracks with irrelevant information. For instance, in 2020, K-pop fans flooded white supremacist hashtags on Twitter with millions of fan videos, rendering the hate speech tracking algorithms and hashtags useless.[5]
Theoretical framework
[edit]In media studies and sociology, algorithmic sabotage is analyzed through the lens of power dynamics between human agency and automated governance. Scholars note that because algorithmic systems are inherently rigid and rely on predictable human behavior, they are uniquely vulnerable to collective, unpredictable human interventions.[2]
See also
[edit]References
[edit]- ^ Veliz, Carissa (2021). "Privacy Is Power: Why and How You Should Take Back Control of Your Data". Oxford University Press: 112–115.
- ^ a b Ferrari, Fabian; Graham, Mark (2021-03-15). "Frictional algorithmic governance: Feedbacks, resistance, and alternative futures". Big Data & Society. 8 (1). doi:10.1177/20539517211003166.
- ^ Brunton, Finn; Nissenbaum, Helen (2015). Obfuscation: A User's Guide for Privacy and Protest. Cambridge, Massachusetts: MIT Press. ISBN 9780262029070.
- ^ Siddiqui, Faiz (2019-05-08). "Uber and Lyft drivers are manipulating algorithms to force surge pricing". The Washington Post.
- ^ Coscarelli, Joe (2020-06-03). "How K-Pop Fans Became an Activist Force". The New York Times.
Category:Algorithmic culture Category:Digital rights Category:Civil disobedience Category:Privacy
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