Virginia Eubanks (2018) Automating Inequality: How High-Tech Tools Profile, Police, and Punish the Poor. New York: Picador, St Martin’s Press

Gordon, Faith

doi:10.5204/lthj.v1i0.1386

Cited by 24 publications

(2 citation statements)

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“…This is not to belittle the inequalities that algorithms create for people's lives, nor do we wish to downplay the effects of automation and automated decision-making on major domains of social life such as welfare, policing, border management, etc. (Eubanks 2018;Benjamin 2019;Kaufman and Leese 2018). Rather, we wish to complement prevailing critiques by emphasising the ways in which the 'rule making' (Katzenbach and Ulbricht 2019, 2) principle of algorithms is influenced by different operational, legislative, and sociocultural contexts.…”

Section: The Emerging Field Of Critical Algorithm Studiesmentioning

confidence: 99%

Assessing Creditworthiness in the Age of Big Data

Hohnen¹,

Ulfstjerne

Krabbe

2021

JEA

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The purpose of this article is twofold: first, we show how algorithms have become increasingly central to financial credit scoring; second, we draw on this to further develop the anthropological study of algorithmic governance. As such, we describe the literature on credit scoring and then discuss ethnographic examples from two regulatory and commercial contexts: the US and Denmark. From these empirical cases, we carve out main developments of algorithmic governance in credit scoring and elucidate social and cultural logics behind algorithmic governance tools. Our analytical framework builds on critical algorithm studies and anthropological studies where money and payment infrastructures are viewed as embedded in their specific cultural contexts (Bloch and Parry 1989; Maurer 2015). The comparative analysis shows how algorithmic credit scoring takes different forms hence raising different issues in the two cases. Danish banks seem to have developed a system of intensive, yet hidden credit scoring based on surveillance and harvesting of behavioural data, which, however, due to GDPR takes place in restricted silos. Credit scores are hidden to customers, and therefore there has been virtually no public debate regarding the algorithmic models behind scores. In the US, fewer legal restrictions on data trading combined with both widespread and visible credit scoring has led to the development of a credit data market and widespread use of credit scoring by ‘affiliation’ on the one hand, but also to increasing public and political critique on scoring models on the other.

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Section: The Emerging Field Of Critical Algorithm Studiesmentioning

confidence: 99%

Assessing Creditworthiness in the Age of Big Data

Hohnen¹,

Ulfstjerne

Krabbe

2021

JEA

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“…Psychobiographies of journalists (Kõuts-Klemm, 2019), designers of algorithms (Svensson, forthcoming) and editors and media makers (Diakopoulos, 2019) are known to orient their data practices. A literature is emerging that documents the biases inscribed in algorithms (Noble, 2018), for instance, as designed by and for white people or men (Eubanks, 2017). There is also a literature showing how media actors may lack the skills to interpret user data.…”

Section: Vignette 4 Participating On Goodreadsmentioning

confidence: 99%

Data loop of media and audience

Mathieu¹,

Vengerfeldt

2020

MedieKultur

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As our digital footprints are collected and analysed by the media and fed backat us as new experiences, providing more data to collect, data circulates in a loopfrom audiences to media and back. This data loop is for media studies an occasionto revisit the media–audience nexus in an age of datafication. We argue that anaudience perspective is needed in order to break with the structure–agency linearityin current understanding of datafication. In this article, we develop a modelof the data loop that first presents the fundamentals of data circulation betweensocial actors and digital interfaces, then the moments of agency between actorsin a relation of mutual dependence. The article closes with a discussion of previousmodels within media and communication that have addressed similar ideas, suchas audience feedback, mutuality and circularity.

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