The end(s) of critique: data behaviourism versus due process
Abstract
Operations of collection, processing and structuration of data for purposes 1 of data mining and profi ling, helping individuals and organisations to cope with circumstances of uncertainty or relieving them from the burden of interpreting events and taking decisions in routine, trivial situations have become crucial to public and private sector activities in domains as various as crime prevention, health management, marketing or even entertainment.2
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Algorithms can be undermined by data-behaviorism, where users adjust behavior to obtain the best possible algorithmic evaluation.
“Also, the algorithms can be underminde due to the so-called data-behaviorism (Rouvroy, 2013) by adjusting behavior accordingly to obtain the best possible algorithmic evaluation.”
From Trust-Building in Peer-to-Peer Carsharing: Design Case Study for Algorithm-Based Reputation Systems (2024) · cites this paper as Rouvroy, 2013
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Cited by 138
- Venue
- Privacy, Due Process and the Computational Turn
- Publisher
- Routledge
- Published
- 2013-06-03
- Pages
- 157-182
- OpenAlex
- W168593401
- Cited by
- 138
- References
- 0
- Citations by year
- 2025: 8 · 2024: 12 · 2023: 31 · 2022: 12 · 2021: 20 · 2020: 8 · 2019: 16 · 2018: 9 · 2017: 1 · 2016: 11 · 2015: 4 · 2014: 2 · 2013: 2 · 2012: 1
- FWCI
- 34.88
- Type
- book chapter
- Language
- en
- Open access
- closed
- Locations
- Routledge eBooks (publishedVersion)
- Topics
- Social Sciences › Safety Research › Ethics and Social Impacts of AI
- Social Sciences › Law › Digitalization, Law, and Regulation
- Social Sciences › Business, Management and Accounting › Industrial relations › Legal and Labor Studies
- Keywords
- due process, data mining, profiling, data collection, data processing, uncertainty, decision-making, public sector data use
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