From digital activism to algorithmic resistance

Treré, Emiliano

doi:10.4324/9781315475059-39

Cited by 25 publications

(23 citation statements)

References 5 publications

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“…The emergence of a growing field of critical studies on data epistemologies (boyd and Crawford 2012; Couldry and Mejias 2019; Kitchin 2014) and resistance (Milan and Gutiérrez 2015; Milan and Treré 2017; Milan and van der Velden 2016; Treré 2018) demonstrates the urgency of addressing the data-centric regime from a perspective that considers their growing complexity, dynamism, and the relevance of situated contexts. Research on data activism (Milan and Gutiérrez 2015; Milan and van der Velden 2016), algorithmic resistance (Treré 2017, 2018), data justice (Dencik et al 2016), algorithmic accountability (Ananny and Crawford 2018; Diakopoulos 2016) explores resistance practices and challenges for activists around the globe. We need more research on the specificities of these practices across cultures: Do existing data resistance practices consider other forms of oppression?…”

Section: Resisting Data Colonizationmentioning

confidence: 99%

Data Epistemologies, The Coloniality of Power, and Resistance

Quijano

2019

Television & New Media

175

107

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Data assemblages amplify historical forms of colonization through a complex arrangement of practices, materialities, territories, bodies, and subjectivities. Data-centric epistemologies should be understood as an expression of the coloniality of power manifested as the violent imposition of ways of being, thinking, and feeling that leads to the expulsion of human beings from the social order, denies the existence of alternative worlds and epistemologies, and threatens life on Earth. This article develops a theoretical model to analyze the coloniality of power through data and explores the multiple dimensions of coloniality as a framework for identifying ways of resisting data colonization. Finally, this article suggests possible alternative data epistemologies that are respectful of populations, cultural diversity, and environments.

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Section: Resisting Data Colonizationmentioning

confidence: 99%

Data Epistemologies, The Coloniality of Power, and Resistance

Quijano

2019

Television & New Media

175

107

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“…At the heart of the material-discursive compositions of Facebook’s embedded AI, then, is a tension—what AI can do versus what Facebook wants the public to think AI can do. Accounts of how algorithms are part of larger ecologies emphasize how algorithmic processes can be used to spread propaganda (Treré 2018 ), but one must wonder how much Facebook’s algorithmic transparency initiatives and statements border on platform propaganda. Or, put another way, there is a chiasmus between the technocratic veneer of how Facebook positions AI as solution to the maligned social media platform’s failings versus the very real limitations of Facebook’s use of AI for the purposes of selection, advertisement, recommendation, and moderation.…”

Section: Case Study: Facebook Transparency Reports and Initiativesmentioning

confidence: 99%

Examining embedded apparatuses of AI in Facebook and TikTok

Grandinetti

2021

AI & Soc

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In popular discussions, the nuances of AI are often abridged as “the algorithm”, as the specific arrangements of machine learning (ML), deep learning (DL) and automated decision-making on social media platforms are typically shrouded in proprietary secrecy punctuated by press releases and transparency initiatives. What is clear, however, is that AI embedded on social media functions to recommend content, personalize ads, aggregate news stories, and moderate problematic material. It is also increasingly apparent that individuals are concerned with the uses, implications, and fairness of algorithmic systems. Perhaps in response to concerns about “the algorithm” by individuals and governments, social media platforms utilize transparency initiatives and official statements, in part, to deflect official regulation. In the following paper, I draw from transparency initiatives and statements from representatives of Facebook and TikTok as case studies of how AI is embedded in these platforms, with attention to the promotion of AI content moderation as a solution to the circulation of problematic material and misinformation. This examination considers the complexity of embedded AI as a material-discursive apparatus, predicated on discursive techniques—what is seeable, sayable, knowable in a given time period—as well as the material arrangements—algorithms, datasets, users, platforms, infrastructures, moderators, etc. As such, the use of AI as part of the immensely popular platforms Facebook and TikTok demonstrates that AI does not exist in isolation, instead functioning as human–machine ensemble reliant on strategies of acceptance via discursive techniques and the changing material arrangements of everyday embeddedness.

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“…Conforme discutimos nas seções anteriores, a comunicação entre os trabalhadores como formas de solidariedades emergentes (Soriano e Cabanes, 2019) é uma prática que molda a dinâmica desses grupos on-line. São táticas e estratégicas de trabalhadores em suas vidas cotidianas no "chão de fábrica da inteligência artificial", enquanto "fissuras algorítmicas" (Ferrari e Graham, 2021) ou "resistências algorítmicas" (Treré, 2018). Isso revela que não há inevitabilidade por parte dos processos programados pelas plataformas de IA, mas modos de organização e comunicação por parte dos trabalhadores, os quais atuam a partir das brechas.…”

Section: Estratégias Dos Trabalhadoresunclassified

O chão de fábrica (brasileiro) da inteligência artificial: a produção de dados e o papel da comunicação entre trabalhadores de Appen e Lionbridge

Grohmann

Araújo

2021

Pacla

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O artigo analisa, por meio de uma pesquisa exploratória, o trabalho de brasileiros em plataformas globais de inteligência artificial (IA), especialmente Appen e Lionbridge, no sentido de destacar o papel da comunicação e da produção de dados para a IA, delineando condições e complexidades do trabalho, enquanto um “chão de fábrica da inteligência artificial”. Para isso, a partir de entrevistas com trabalhadores e observações em grupos de WhatsApp e Facebook, chegamos a cinco categorias predominantes: processos de contratação, acompanhamento do tempo e dificuldades na comprovação das horas trabalhadas, falta de confiabilidade da infraestrutura, estratégias de trabalho e definição de trabalho, e compreensão da IA. Com base na análise, sustentamos que, ao contrário de um universalismo, há uma geopolítica no trabalho em plataformas de IA, em um colonialismo por meio da IA. Destacamos as condições materiais de produção de dados e o papel da comunicação entre trabalhadores como solidariedades emergentes e complexas, enquanto fissuras e brechas, a fim de construir estratégias para lidar com o trabalho em plataformas de IA.

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From digital activism to algorithmic resistance

Cited by 25 publications

References 5 publications

Data Epistemologies, The Coloniality of Power, and Resistance

Data Epistemologies, The Coloniality of Power, and Resistance

Examining embedded apparatuses of AI in Facebook and TikTok

O chão de fábrica (brasileiro) da inteligência artificial: a produção de dados e o papel da comunicação entre trabalhadores de Appen e Lionbridge

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