Netflix & Big Data: The Strategic Ambivalence of an Entertainment Company

Netflix actively fueled what is known as the myth of big data, promoting their recommender system and data-driven production as cutting-edge, all-seeing, and all-knowing. Today, however, the company is increasingly acknowledging the role of human expertise and creativity. In this paper I explore the strategic repositioning of Netflix from technology company to entertainment company, enabling them to be understood as both “data” and “gut.” This transformation is discussed as motivated by the increasing public criticism of data and algorithms and the company’s foray into original programing. More specifically, I examine how Netflix, in public-facing materials, discusses big data and how those ideas are taken up in public discourse. These sources disclose an assumption of opposing characteristics between data and human expertise and creativity. As a point of a larger critique, I comment on the limitations of this data and human opposition for thinking about Netflix and technologies at large

Unpacking tool criticism as practice, in practice

Thanks to easy-to-use data analysis tools and digital infrastructures, even those humanities scholars who lack programming skills can work with large-scale empirical datasets in order to disclose patterns and correlations within them. Although empirical research trends have existed throughout the history of the humanities [Bod 2013], these recently emergent possibilities have revived an empiricist attitude among humanities scholars schooled in more critical and interpretive traditions. Replying to calls for a critical digital humanities [Berry and Fagerjord 2017] [Dobson 2019], this paper explores “tool criticism” [Van Es et al. 2018] – a critical attitude required of digital humanities scholars when working with computational tools and digital infrastructures. First, it explores tool criticism as a response to instrumentalism in the digital humanities and proposes it to be part of what a critical digital humanities does. Second, it analyses tool criticism as practice, in practice. Concretely, it discusses two critical making– inspired workshops in which participants explored the affordances of digital tools and infrastructures and their underlying assumptions and values. The first workshop focused on “games-as-tools” [Werning 2020]. Participants in the workshop engaged with the constraints, material and mechanical, of a card game by making modifications to it. In the second workshop, drawing on the concept of “digital infrapuncture” [Verhoeven 2016], participants examined digital infrastructure in terms of capacity and care. After first identifying “hurt” in a chat environment, they then designed bots to intervene in that hurt and offer relief

Pluralising critical technical practice

In this special issue, we turn to ideas of and approaches to critical technical practices (CTPs) as entry points to doing critique and doing things critically in digitally mediated cultures and societies. We explore the pluralisation of ‘critical technical practice’, starting from its early formulations in the context of AI research and development (Agre, 1997a, 1997b) to the many ways in which it has resonated and been taken up by different publications, projects, groups, and communities of practice, and what is has come to mean. Agre defined CTP as a situational, practical, and constructive way of working: ‘a technical practice for which critical reflection upon the practice is part of the practice itself’ (1997a: XII). Communities of practice in which the notion has been adopted, adapted, and put to use range from human–computer interaction (HCI) to media art and pedagogy, from science and technology studies (STS) and computer-supported cooperative work (CSCW) to digital humanities, media studies and data studies. This special issue affirms the pluralisation of CTP, and serves as an invitation to (re)consider what it means to use this notion drawing on a wider body of work, including beyond Agre. In this introduction, we review and discuss CTPs according to (1) Agre, (2) indexed research, and (3) contributors to this special issue. We conclude with some questions and considerations for those interested in working with this notion

Situating Data: Inquiries in Algorithmic Culture

Taking up the challenges of the datafication of culture, as well as of the scholarship of cultural inquiry itself, this collection contributes to the critical debate about data and algorithms. How can we understand the quality and significance of current socio-technical transformations that result from datafication and algorithmization? How can we explore the changing conditions and contours for living within such new and changing frameworks? How can, or should we, think and act within, but also in response to these conditions? This collection brings together various perspectives on the datafication and algorithmization of culture from debates and disciplines within the field of cultural inquiry, specifically (new) media studies, game studies, urban studies, screen studies, and gender and postcolonial studies. It proposes conceptual and methodological directions for exploring where, when, and how data and algorithms (re)shape cultural practices, create (in)justice, and (co)produce knowledge

Interstitial Data: Tracing Metadata in Archival Search Systems

Metadata do not merely give explicit information about records in the archive but can also be considered a source of information about the (historical) context in which they are created. This chapter combines the insights of critical data studies and archival studies to formulate a hands-on approach to tracing metadata in archival search systems. The approach, which builds further on Loukissas’s local reading strategies, consists of two distinct phases: an exploration phase to trace and select and an analysis phase to trace and compare. The author concludes that a lot of data necessary to understanding metadata in search systems is hidden—dif ferent forms of what can be considered “interstitial data.

Pluralising Critical Technical Practice

In this special issue, we turn to ideas of and approaches to critical technical practices (CTPs) as entry points to doing critique and doing things critically in digitally mediated cultures and societies. We explore the pluralisation of ‘critical technical practice’, starting from its early formulations in the context of AI research and development (Agre, 1997a, 1997b) to the many ways in which it has resonated and been taken up by different publications, projects, groups, and communities of practice, and what it has come to mean. Agre defined CTP as a situational, practical, and constructive way of working: ‘a technical practice for which critical reflection upon the practice is part of the practice itself’ (1997a: XII). Communities of practice in which the notion has been adopted, adapted, and put to use range from human–computer interaction (HCI) to media art and pedagogy, from science and technology studies (STS) and computer-supported cooperative work (CSCW) to digital humanities, media studies and data studies. This special issue affirms the pluralisation of CTP, and serves as an invitation to (re)consider what it means to use this notion drawing on a wider body of work, including beyond Agre. In this introduction, we review and discuss CTPs according to (1) Agre, (2) indexed research, and (3) contributors to this special issue. We conclude with some questions and considerations for those interested in working with this notion

The Datafication of Racialization and the Pursuit of Equality: The Case of the “Barometer Culturele Diversiteit”

In this chapter, I show how the investigation of racialization in datafied applications can be done through an instrumental, epistemological, and ontological approach to datafication and that the results of each approach do not necessarily match. By analyzing the attempted implementation of a tool aimed at measuring the composition of personnel in terms of migration background called Barometer Culturele Diversiteit (BCD) at Utrecht University in the Netherlands, I show how the tool is using ideas about race (instrumental), shaping knowledge through colonial politics (epistemological), and producing race (ontological) simultaneously. Aided by this analysis, I will advocate for an understanding of the use of raceethnic data for affirmative purposes in terms of strategic essentialism, making epistemic imperfection regarding race warranted only in antiracist data systems working toward their own obsolescence

Schooled by Dashboards?: Learning Platforms’ Performance-Centered Pedagogy and Its Impact on Teaching

Personalized learning is rapidly becoming a reality in classrooms worldwide through platformization. At the classroom level, digital platforms shape learning toward personal needs through pedagogies encoded into their design—their algorithms, but also into dashboard interfaces teachers increasingly employ as part of their educational toolkit. This study investigates how dashboards can impact teaching in primary school classrooms by examining how their data visualizations configure particular views on learning, which educators increasingly depend on to make pedagogical decisions. It will address two research questions: What are the pedagogical underpinnings of learning dashboards integrated in personalized learning technologies? How may pedagogies encoded into these dashboards affect teaching? To answer these questions, the chapter will start by setting out a theoretical perspective on platform pedagogy. Subsequently, it will describe teaching and learning relationships encoded in the teaching dashboard of the Dutch adaptive learning platform Snappet and argue that its pedagogy of performativity may disempower teachers’ control over learning. The concluding section will discuss actions needed to strengthen schools’ and teachers’ control over the pedagogical dimensions of learning platforms

The Agricultural Data Imaginary: Precision farming’s reinforcement of the productivist approach to agriculture

Big Data come with the promise of a better future. In the agricultural discourse on smart technologies and data-based applications in farming, so-called “precision farming” is envisioned as a “revolution” of traditional agricultural mass production of crops and livestock. Big Data are imagined as making the agrifood industry more efficient, more profitable, and more sustainable. Drawing on David Beer’s concept of the “data imaginary” (2019), this chapter examines discourses on precision farming in corporate advertisements, lobbyist agricultural journals, and review articles in academic journals in the field of agriculture and computing. It argues that data-based agrifood production is seen as the next technological fix of the broken system of traditional industrial farming, while it in fact reinforces the devastating environmental and social damages that traditional industrial farming has caused. Keywords: big data, smart farming, data imaginary, productivist agriculture, technological solutionis