Algorithms (and the) everyday

By Michele A. Willson. 2017

194 citations recorded by the source corpus.

ABSTRACT Our everyday practices are increasingly mediated through online technologies, entailing the navigation and also oft-simultaneous creation of large quantities of information and communication data. The scale and types of activities being undertaken, the data that are being created and engaged with, and the possibilities for analysis, archiving and distribution are now so extensive that technical constructs are necessarily required as a way to manage, interpret and distribute these. These constructs include the platforms, the software, the codes and the algorithms. This paper explores the place of the algorithm in shaping and engaging with the contemporary everyday. It does this via an exploration of some particular instances of algorithmic sorting and presentation as well as considering some of the ways these contribute to shaping our everyday practices and understandings. In doing so, it raises questions about understandings of agency and power, shifting world views and our complex relationship with technologies.

Subfields: Computer Science Applications, Cultural Studies, Safety Research

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Citations in the corpus

Experiencing Algorithms: How Young People Understand, Feel About, and Engage With Algorithmic News Selection on Social Media (2021, background): “While numerous conceptual studies have explored how algorithms shape everyday life (e.g., Beer, 2017; Diakopoulos, 2015; Willson, 2017), these typically take a technological perspective to uncover how algorithms exert power.”
Algorithmic Folk Theories and Identity: How TikTok Users Co-Produce Knowledge of Identity and Engage in Algorithmic Resistance (2021, background): “The proprietary secretive nature of these algorithms and the technical knowledge required to understand them presents challenges when investigating social media sites’ impacts on individuals, particularly those with marginalized identities [82].”
Managing visibility on YouTube through algorithmic gossip (2019, background): “This article addresses growing concerns about how cultural producers navigate the increasingly algorithmic nature of content distribution (Hallinan and Striphas, 2016; Willson, 2017).”
Fair, Transparent, and Accountable Algorithmic Decision-making Processes (2017, background): “…streams of data are available to train algorithms which, combined with increased analytical and technical capabilities, are enabling researchers, companies, governments and other public sector actors to resort to data-driven machine learning-based algorithms to tackle complex problems [26,67].”
The Challenges of Algorithm-Based HR Decision-Making for Personal Integrity (2019, methodology): “Against this background, scholars in the fields of business ethics (Martin and Freeman 2003), critical algo-rithm studies (Ananny 2016; Kitchin 2017; Willson 2017), workplace monitoring (Ball 2001), and management (Bern-stein 2017) have discussed the use of algorithm-based decision-making,…”
Where fairness fails: data, algorithms, and the limits of antidiscrimination discourse (2019, background): “certain discursive frames over others (e.g., Bivens & Hoque, 2018; Sweeney, 2016; Willson, 2017).”
Playing the visibility game: How digital influencers and algorithms negotiate influence on Instagram (2018, background): “…that when engineers operationalize concepts like content users “care about the most” (Instagram, 2016) or “meaningful interactions” (Zuckerberg, 2018) through algorithms, they can impose certain valuations, meanings, and relationships to objects and actors with which we interact (Willson, 2017).”
Towards Algorithmic Experience: Initial Efforts for Social Media Contexts (2018, background): “delegate everyday tasks [30], and further argues that”