Algorithmic Culture

AoIR Selected Papers of Internet Research, 2021

How we imagine our place within the structure of sociotechnical-human relationships—specifically, in domains of life affected by data-analytics and the probabilistic bets institutions and people in power make on the future of our credit worthiness, political leanings, shopping habits etc.—is our “algorithmic imagination.” The purpose of this panel is to explore the “algorithmic imagination” as it manifests in particular scholarly, historical, socio-cultural, and technical contexts. The panelists prioritize how social actors, situated in distinct settings, go about constructing an “algorithmic imagination” in conversation/opposition with how computational systems have “imagined” them; they will also reflect critically and self-reflexively on the implications of an algorithmic imagination, so conceived. Collectively, the panelists demure from monolithic understandings of the “algorithmic imagination” while also embracing algorithmic intersectionality. The primary contention of this pa...

Algorithms, once obscure objects of technical art, have lately been subject to considerable popular and scholarly scrutiny. What does it mean to adopt the algorithm as an object of analytic attention? What is in view, and out of view, when we focus on the algorithm? Using Niklaus Wirth's 1975 formulation that ''algorithms þ data structures ¼ programs'' as a launching-off point, this paper examines how an algorithmic lens shapes the way in which we might inquire into contemporary digital culture.

The Datafied Society, 2017

Humans have long defined, assessed, analysed and calculated data as factors in how they navigate reality. Indeed, the rules for what constitute data, together with the logics of their assembly, make up a core component of culture. Whether they be omens or numbers, whether they are qualitative or quantitative, whether they involve heuristics, hermeneutics or the rules of mathematics, the dyad of data and their organizing schemes give cultural eras their specificity. Considering developments ranging from Mayan astronomical calendars to Copernicus's heliocentric observations, from seventeenth-century navigational charts to twentieth-century actuarial tables, one might say that this dyad underpins cultural possibility itself. 1 Data have never been more abundant than they are today. Their unprecedented quantity owes as much to the digital encoding of most traceable phenomena as to the production of data by actors beyond our species. Whereas in the past, human observation translated events in the world into data, today, networked non-human actors are capable of directly generating machine-readable data. But as in the past, all that data would be meaningless without an organizing scheme. Behind the quintillions of bytes, behind our computers' ever-growing processing power, is an organizing scheme in the form of the algorithm. Like data, algorithms can be human-or machine-generated. And although an ancient idea, the algorithm has-or so I will argue-reached a tipping point in terms of its cultural operations: it is now being deployed in ways that redefine long-held subjectobject relationships and, in so doing, it poses some rather fundamental epistemological questions. This change in the balance of things has produced its share of anxieties, as familiar ways of doing things seem superseded by 'the algorithm'. The recent explosion of headlines where the term 'algorithm' figures prominently and often apocalyptically suggests that we are re-enacting a familiar ritual in which 'new' technologies appear in the regalia of disruption. But the emerging algorithmic regime is more than 'just another' temporarily unruly 1 Portions of this essay first appeared as William Uricchio, 'Recommended for You: Prediction, Creation and the Cultural Work of Algorithms,'

This article responds to recent debates in critical algorithm studies about the significance of the term ''algorithm.'' Where some have suggested that critical scholars should align their use of the term with its common definition in professional computer science, I argue that we should instead approach algorithms as ''multiples''-unstable objects that are enacted through the varied practices that people use to engage with them, including the practices of ''outsider'' researchers. This approach builds on the work of Laura Devendorf, Elizabeth Goodman, and Annemarie Mol. Different ways of enacting algorithms foreground certain issues while occluding others: computer scientists enact algorithms as conceptual objects indifferent to implementation details, while calls for accountability enact algorithms as closed boxes to be opened. I propose that critical researchers might seek to enact algorithms ethnographically, seeing them as heterogeneous and diffuse sociotechnical systems, rather than rigidly constrained and procedural formulas. To do so, I suggest thinking of algorithms not ''in'' culture, as the event occasioning this essay was titled, but ''as'' culture: part of broad patterns of meaning and practice that can be engaged with empirically. I offer a set of practical tactics for the ethnographic enactment of algorithmic systems, which do not depend on pinning down a singular ''algorithm'' or achieving ''access,'' but which rather work from the partial and mobile position of an outsider.

2017

We commonly think of society as made of and by humans, but with the proliferation of machine learning and AI technologies, this is clearly no longer the case. Billions of automated systems tacitly contribute to the social construction of reality by drawing algorithmic distinctions between the visible and the invisible, the relevant and the irrelevant, the likely and the unlikely – on and beyond platforms. Drawing on the work of Pierre Bourdieu, this book develops an original sociology of algorithms as social agents, actively participating in social life. Through a wide range of examples, Massimo Airoldi shows how society shapes algorithmic code, and how this culture in the code guides the practical behaviour of the code in the culture, shaping society in turn. The ‘machine habitus’ is the generative mechanism at work throughout myriads of feedback loops linking humans with artificial social agents, in the context of digital infrastructures and pre-digital social structures. Machine Habitus will be of great interest to students and scholars in sociology, media and cultural studies, science and technology studies and information technology, and to anyone interested in the growing role of algorithms and AI in our social and cultural life.

Current Anthropology 54(6):716-739, 2013

This article argues that contemporary, computer-mediated, algorithmic forms of sociality problematize a long and major tradition in cultural anthropology, which has appropriated the notion of artistic style to theorize culture as a relatively distinct, coherent, and durable configuration of behavioral dispositions. The article’s ethnographic site is a lab in a major institute of technology in the United States, in which computer scientists develop computerized algorithms that are able to simulate the improvisation styles of past jazz masters and mix them with one another to create new styles of improvisation. The article argues that the technology that allows the scientists to simulate and mix styles is playing an increasingly important role in mediating contemporary forms of sociality over the Internet and that the anthropological tradition that has theorized culture as artistic style has to be reconfigured to account for the dynamic nature of these contemporary forms of sociality not as styles but as styles of styling styles.

Digital Keywords: A Vocabulary of Information Society and Culture

"Culture is a keyword among keywords for Raymond Williams, who contributed to the founding of cultural studies in the 1960s and 1970s. It is among the most common ways to talk about how we talk. In the essay below, one of Williams’ most careful readers, Ted Striphas, offers a sensitive update to Williams and a wide-ranging intellectual history, describing how culture has coevolved with the digital turn since the end of World War II. No longer an antithesis to technology, culture has recently interpenetrated with the computational (e.g., digital humanities, culturomics, and big-data-driven cultural studies). In fascinating conversation with Fred Turner’s prototype and Limor Shifman’s meme, in what sense do aspects of modern-day digital culture challenge and confirm Striphas’ observation about the dynamism and adaptability of culture—or, in Williams’ famous phrase, 'one of two or three most complicated words in the English language?'" [overview by Benjamin Peters]

How does algorithmic information processing affect the meaning of the word culture, and, by extension, cultural practice? We address this question by focusing on the Netflix Prize (2006–2009), a contest offering US$1m to the first individual or team to boost the accuracy of the company’s existing movie recommendation system by 10%. Although billed as a technical challenge intended for engineers, we argue that the Netflix Prize was equally an effort to reinterpret the meaning of culture in ways that overlapped with, but also diverged in important respects from, the three dominant senses of the term assayed by Raymond Williams. Thus, this essay explores the conceptual and semantic work required to render algorithmic information processing systems legible as forms of cultural decision making. It also then represents an effort to add depth and dimension to the concept of “algorithmic culture.”

2009