Dario Rodighiero

Most of the existing studies on Bourdieu and the digital regards the social and class distinctions in the use of digital technologies, thus presupposing a certain transparency of technologies themselves. Our proposal is to refer to this attitude as “Bourdieu outside the digital.” Yet in this paper, another perspective called “Bourdieu inside the digital” is developed, which moves the focus on the effects of some emerging technologies on social distinctions and discrimination. The main hypothesis is that algorithms of machine learning are producers and reproducers of habitus. Although their results present a greater granularity with respect to the standard techniques of the past, these algorithms still reduce individuals to categories, general trends, classes, and behaviors. Such a reduction has flattening effects on the individuals’ self-understanding, especially in terms of identity and interaction with the social world. This is the phenomenon described in the article as the “personalization without personality,” whose consequences are both existential and social-political. This idea will be illustrated through qualitative and comparative analysis between the correspondence analysis and the multiple correspondence analysis used by Bourdieu in his works and some of those techniques that are performed today in big data analytics.

Self-recognition is an intimate act performed by people. Inspired by Paul Ricoeur, we reflect upon the action of self-recognition, especially when data visualization represents the observer itself. Along the article, the reader is invited to think about this specific relationship through concepts like the personal identity stored in information systems, the truthfulness at the core of self-recognition, and the mutual-recognition among community members. In the context of highly interdisciplinary research, we unveil two protagonists in data visualization: the designer and the observer - the designer as the creator and the observer as the viewer of a visualization. This article deals with some theoretical aspects behind data visualization, a discipline more complex than normally expected. We believe that data visualization deserves a conceptual framework, and this investigation pursues this intention. For this reason, we look at the designer as not just a technician in the visualization production, but as a contemporary ethnologist - the designer as a professional working in a social environment to comprehend the context and formulate a specific inquiry with the help of appropriate visual languages.

This article explores how readers recognize their personal identities represented through data visualizations. The recognition is investigated starting from three definitions captured by the philosopher Paul Ricoeur: the identification with the visualization, the recognition of someone in the visualization, and the mutual recognition that happens between readers. Whereas these notions were initially applied to study the role of the book reader, two further concepts complete the shift to data visualization: the digital identity stays for the present-day passport of human actions and the promise is the intimate reflection that projects readers towards their own future. This article reflects on the delicate meaning of digital identity and the way of representing it according to this structure: From Personal Identity to Media is a historical introduction to self-recognition, Data Visualization for Representing Identities moves the focus to visual representation, and The Course of Recognition breaks the self-recognition in through the five concepts above just before the Conclusion.

In this article, we show how postphenomenology can be used to analyze the Affinity Map: a data visualization that reveals the hidden dynamics that exist between individuals within large organizations. We make use of the Affinity Map to expand the classic postphenomenology that privileges a ‘linear’ understanding of technological mediations and introduce the notions of ‘iterativity’ and ‘collectivity.’ In the first section of the paper, we discuss both classic and more recent descriptions of human-technology-world relations in order to transcendentally approach the discipline of data visualization. In the second section, we use the Affinity Map case study to consider three elements: 1) the collection of data and the design process; 2) the visual grammar of the data visualization, and 3) the process of self-recognition for the map ‘reader.’ In the third section, we introduce the hermeneutic circle of data visualization. Finally, we suggest that the Affinity Map, because of its ethical and political multistability, might be seen as a material encounter between postphenomenology, actor-network theory (ANT), and hermeneutics.