Algorithmic Cultures

Seyfert, Robert; Roberge, Jonathan

doi:10.4324/9781315658698

Cited by 38 publications

(13 citation statements)

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“…Sometimes, algorithms cause harm when they fail to connect information in ways people find meaningful: ‘Unstable negotiations, slippage, fragility, and a proneness to failure are in fact important features of algorithmic cultures’ (Seyfert and Roberge, 2016: 26). The expectation that algorithms use all kinds of data about individuals to personalise their online experience can result in confusion or disappointment when people are shown content or advertisements that don’t match their demographic or personal information: Bucher (2016b) reports seeing tweets that lament, ‘I feel like the Facebook algorithm doesn’t know me at all!’ (p. 81) Profiles derived from algorithmic connections are not necessarily comprehensive or accurate – but this article is about what happens when algorithms do work.…”

Section: Forced Connections and Their Consequencesmentioning

confidence: 99%

“…But this is not easily done. The inner workings of algorithms are often deliberately opaque, as they are trade secrets for companies like Facebook, Google and Amazon (Seyfert and Roberge, 2016), or simply because they can be unavoidably complex (Hamilton et al, 2014). Helen Kennedy (2016) reminds us that access to data and algorithms, and the skills to comprehend and work with them, are uneven, leading to new divides in knowledge.…”

Section: How Algorithms Are Understood and How They Really Workmentioning

confidence: 99%

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‘Networks that work too well’: intervening in algorithmic connections

Nagel

2018

Media International Australia

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Within the emerging field of critical algorithm studies, this article theorises that forced connections happen when algorithms exacerbate human actions in connecting otherwise disparate data points on digitally networked platforms to the subject of the data’s detriment. Although social media users may not have a comprehensive understanding of how algorithms work to make some content visible, when users form their own explanatory theories about these algorithms, they often intervene in these connections. Drawing on Michel de Certeau’s notion of strategies as the manipulations in which platforms engage to profile and control their users, and tactics as everyday acts of resistance, this article investigates two tactics within algorithmic cultures – Voldemorting, or not mentioning words or names in order to avoid a forced connection; and screenshotting, or making content visible without sending its website traffic – to demonstrate users’ understandings of the algorithms that seek to connect individuals to other people, platforms, content and advertisers, and their efforts to wrest back control.

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Section: Forced Connections and Their Consequencesmentioning

confidence: 99%

Section: How Algorithms Are Understood and How They Really Workmentioning

confidence: 99%

‘Networks that work too well’: intervening in algorithmic connections

Nagel

2018

Media International Australia

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“…O saber preditivo dos algoritmos define, deste modo, os perfis de alvos específicos para sugestão de conteúdos diferenciados no momento e no contexto apropriados para influenciar, de forma personalizada e em tempo real, o comportamento dos usuários (INTRONA, 2016). legitimadas por um discurso de comodidade que promete oferecer conteúdos, serviços e produtos ultrapersonalizados e "relevantes" aos interesses dos usuários, estas ferramentas de captura irrestrita e extensiva de informações são, entretanto, entendidas pelo marketing digital como meios de explorar vulnerabilidade cognitivas e emocionais a fim de influenciar o processo de tomada de decisão e o comportamento dos usuários.…”

Section: /21unclassified

Economia psíquica dos algoritmos e laboratório de plataforma: mercado, ciência e modulação do comportamento

Bruno

Bentes

Faltay

2019

Rev. Famecos (Online)

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O extensivo e ininterrupto monitoramento de nossas ações online integram as engrenagens de um investimento econômico que direciona imensos volumes de dados para aplicação de estratégias de modificação do comportamento humano. Nesse contexto, observamos um aumento do interesse tecnocientífico, econômico e social em processos algorítmicos de extração e utilização de dados psíquicos e emocionais. Este artigo tem como objetivo apresentar reflexões sobre essa Economia Psíquica dos Algoritmos, enfatizando sua inquietante dimensão laboratorial. Analisando casos recentes e aspectos da arquitetura das plataformas digitais, mostraremos como o uso desses dados articula três camadas: a econômica; a epistemológica; e a de gestão e controle comportamental. Notaremos que o cruzamento dessas camadas tornam as fronteiras entre o laboratório e a vida social extremamente tênues, o que nos convoca a recolocar o problema das relações entre ciência, tecnologia e sociedade nesse novo cenário.

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“…Scholars have been reluctant to describe algorithms as agentic beings––Reichertz (2013) described algorithms as “nothing but instruments of human agency” (Reichertz [2013], cited by Seyfert and Roberge [2016]); Neff and colleagues (2012) have referred to algorithms’ power as a “not-quite, but ‘technically’, agency” (p. 305); and Klinger and Svensson (2018) recently argued that algorithms do not (yet) have the evaluative and reflexive elements of human agency. Others have highlighted algorithms’ opacity and orderliness (Lessig 1999), or their seeming objectivity, accuracy, and impartiality (Gillespie 2014, 180), to describe them as institutional factors (Napoli 2014), and yet others have used the term “computational agency” to describe algorithms’ automation and stealth (Tufekci 2015).…”

Section: Introductionmentioning

confidence: 99%

Who Gets to Choose? On the Socio-algorithmic Construction of Choice

Kotliar

2020

Science, Technology, & Human Values

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This article deals with choice-inducing algorithms––algorithms that are explicitly designed to affect people’s choices. Based on an ethnographic account of three Israeli data analytics companies, I explore how algorithms are being designed to drive people into choice-making and examine their co-constitution by an assemblage of specifically positioned human and nonhuman agents. I show that the functioning, logic, and even ethics of choice-inducing algorithms are deeply influenced by the epistemologies, meaning systems, and practices of the individuals who devise and use them and that such algorithms are similarly affected by interorganizational relationships, various nonhuman agents, and changing geopolitical contexts. I conclude by discussing the flexibility of choice-inducing algorithms and by arguing that such algorithms are not programmed to induce specific choices but to more generally convert people into choosers, and thus, to algorithmically (re)create the modern need to choose. This article contributes to the growing literature on algorithms and culture and to our understanding of choice-making in contemporary life. At the same time, it provides a new vocabulary that offers to critically engage with algorithms and their power without losing sight of the often very specific contexts from which they arise.

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Algorithmic Cultures

Cited by 38 publications

References 0 publications

‘Networks that work too well’: intervening in algorithmic connections

‘Networks that work too well’: intervening in algorithmic connections

Economia psíquica dos algoritmos e laboratório de plataforma: mercado, ciência e modulação do comportamento

Who Gets to Choose? On the Socio-algorithmic Construction of Choice

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