Algorithmic culture

By Ted Striphas. 2015

Over the last 30 years or so, human beings have been delegating the work of culture – the sorting, classifying and hierarchizing of people, places, objects and ideas – increasingly to computational processes. Such a shift significantly alters how the category culture has long been practiced, experienced and understood, giving rise to what, following Alexander Galloway, I am calling ‘algorithmic culture’. The purpose of this essay is to trace some of the conceptual conditions out of which algorithmic culture has emerged and, in doing so, to offer a preliminary treatment on what it is. In the vein of Raymond Williams’ Keywords, I single out three terms whose bearing on the meaning of the word culture seems to have been unusually strong during the period in question: information, crowd and algorithm. My claim is that the offloading of cultural work onto computers, databases and other types of digital technologies has prompted a reshuffling of some of the words most closely associated with culture, giving rise to new senses of the term that may be experientially available but have yet to be well named, documented or recorded. This essay, though largely historical, concludes by connecting the dots critically to the present day. What is at stake in algorithmic culture is the gradual abandonment of culture’s publicness and the emergence of a strange new breed of elite culture purporting to be its opposite.

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Citations in the corpus

When the algorithm itself is a racist: Diagnosing ethical harm in the basic Components of Software (2016, methodology): “The word algorithm has a long history (Striphas, 2015), but why was it imported into computing?”
Towards Transparency by Design for Artificial Intelligence (2020, background): “As Ted Striphas (2015) points out, with reference to the impact of Amazon’s recommendation system on the visibility of LGBT literature, the dimension of culture also needs to be recognised in analyses of algorithms, insofar as cultural work is increasingly being offloaded onto frequently privatised…”
Algorithms as culture: Some tactics for the ethnography of algorithmic systems (2017, background): “This vision of algorithms as culture diﬀers from the notion of ‘‘algorithmic culture’’ (Striphas, 2015), which posits algorithms as an transformative force, exogenous to culture.”
The Challenges of Algorithm-Based HR Decision-Making for Personal Integrity (2019, background): “An additional reason why racial and gender stereotypes may persist is that the predominant code of algorithms tends to reflect the cultural background of its developer(s) (Lowrie 2017; Seaver 2017; Striphas 2015).”
Algorithmic Cultures : Essays on Meaning, Performance and New Technologies (2016, background): “We should also examine the way these algorithmic techniques themselves become cultural objects, get taken up in our thinking about culture and the public to which it is addressed, and get contested both for what they do and what they reveal (Striphas 2015).”
Critical Data Studies: A dialog on data and space (2016, background): “…Studies calls attention to subject formation within these data regimes, for a critical examination of where the interpellation of the individual emerges in algorithmic culture (Striphas, 2015) and, through that, where the cracks and seams, the spaces for resistance and alternatives, might be found.”
Securing with algorithms: Knowledge, decision, sovereignty (2017, background): “The algorithm is an integral part of human action and culture (Striphas, 2015).”
Seeing without knowing: Limitations of the transparency ideal and its application to algorithmic accountability (2018, background): “…2016: 1)—but also as relationships without social articulation (Eslami et al., 2015), elite structuring masked as emergent sociality (Mackenzie, 2015; Striphas, 2015), automated media circulation (Hallinan and Striphas, 2014; Napoli, 2014), optimized labor (Kushner, 2013) and financial markets…”
The social power of algorithms (2017, background): “There is a desire to see how ‘algorithmic culture’ (Striphas, 2015) is experienced and how ‘algorithmic life’ (Amoore & Piotukh, 2016) is lived.”