Algorithmic IF … THEN rules and the conditions and consequences of power
By Daniel Neyland, Norma Möllers. 2017
74 citations recorded by the source corpus.
ABSTRACT The introduction to this special issue suggests we need to develop ‘a greater understanding of what might be thought of as the social power of algorithms'. In this paper, ‘social power’ will be critically scrutinised through a study of the entanglement of algorithmic rules with contemporary video-based surveillance technologies. The paper will begin with an analysis of algorithmic ‘IF … THEN’ rules and the conditions (IF) and consequences (THEN) that need to be accomplished for an algorithm to be said to succeed. The work of achieving conditions and consequences demonstrates that the form of ‘power’ in focus is not solely attributable to the algorithm as such, but operates through distributed agency and can be noted as a network effect. That is, the conditions and consequences of algorithmic rules only come into being through the careful plaiting of relatively unstable associations of people, things, processes, documents and resources. From this we can say that power is not primarily social in the sense that algorithms alone create an impact on society, but social in the sense of power being derived through algorithmic associations. The paper argues that this kind of power is most clearly visible in moments of breakdown, failure or other forms of trouble, whereby algorithmic conditions and consequences are not met and the careful plaiting of associations has to be brought to the fore and examined. It is through such examinations that the associational dependencies more than the social power of algorithms are made apparent.
Subfields: Safety Research, Sociology and Political Science
How researchers see this paper
The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.
In Safety Research
- Simon Schafheitle
- Ulrich Leicht‐Deobald
- Antoinette Weibel
- Isabelle Wildhaber
- Mike Ananny
- Thorsten Busch
- G. Kasper
- Kate Crawford
In Sociology and Political Science
- Maranke Wieringa
- Simon Schafheitle
- Ulrich Leicht‐Deobald
- Antoinette Weibel
- Isabelle Wildhaber
- Mike Ananny
- Thorsten Busch
- G. Kasper
Citations in the corpus
- What to account for when accounting for algorithms: a systematic literature review on algorithmic accountability (2020, background): “27 academic articles [8, 9, 17, 20, 22, 28, 35, 48, 52, 58, 61, 65, 86, 90, 93, 98, 106, 110, 111, 120, 124, 135, 139–141, 143, 144] which were found to be relevant to the topic prior to the start of the systematic review were assessed for their keywords.”
- The Challenges of Algorithm-Based HR Decision-Making for Personal Integrity (2019, background): “…issues regarding privacy (Martin and Nissenbaum 2016), accountability (Diakopoulos 2016; Neyland 2015), transparency (Ananny and Crawford 2018; Martin 2018; Stohl et al. 2016), power (Beer 2017; Neyland and Möllers 2017), and social control (Ajunwa et al. 2017; boyd and Crawford 2012; Zuboff 1988).”
- Seeing without knowing: Limitations of the transparency ideal and its application to algorithmic accountability (2018, background): “The power of these systems lies in the “careful plaiting of relatively unstable associations of people, things, processes, documents and resources” (Neyland and Möllers, 2016: 1)—but also as relationships without social articulation (Eslami et al., 2015), elite structuring masked as emergent…”