1,721,008 research outputs found
Why data is not enough: Digital traces as control of self and self-control
As an alternative to the seemingly natural objectivity and self-evidence of "data," this paper builds on recent francophone literature by developing a critical conceptualization of "digital traces." Underlining the materiality and discursiveness of traces allows us to understand and articulate both the technical and sociopolitical implications of digital technology. The philosophies of Gilbert Simondon and Michel Foucault give strong ontological and epistemological groundings for interpreting the relationships between technology and processes of subjectification. In this light, digital traces are framed as objects and products of eteronomous interventions, the logics of which can be traced through the programs and algorithms deployed. Through the empirical examples of "Predictive Policing" and "Quantified Self" digital traces are contrasted with the premises and dreams of Big Data. While the later claims to algorithmically correlative, predict and preempt the future by reducing it to a "what-is-tocome," the digital trace paradigm offers a new perspective on how forms of self-control and control of the self are interdependent facets of "algorithmic governmentality.". © The author(s), 2014.SCOPUS: ar.jinfo:eu-repo/semantics/publishe
Recommender Systems as Techniques of the Self?
This paper aims to give a renewed perspective on the normative stakes involved in the algorithmic recommendation of cultural content. Two prevalent framings of technological normativity and transparency need to be overcome. First, algorithmic design seems convinced that accessing the behavioral level of interaction is coincidental with a greater level of truth and authenticity, as if the subject were incapable of speaking honestly of itself. Conversely, critics of the 'black-box' normativity imagine that being able to access the code, the written structure of the algorithm, we will unveil something of its essence. By reading Foucault's notion of techniques of the self, as exposed in L'Herméneutique du sujet, together with the cybernetic theory of feed-back and Simondon's philosophy of individuation, the author claims that users do not need to see through the algorithm nor see the actual workings of the algorithm, but that they need to be able to see themselves when using the algorithm
Going Beyond Counting First Authors in Author Co-citation Analysis
The present study examines one of the fundamental aspects of author co-citation analysis (ACA) - the way co-citation
counts are defined. Co-citation counting provides the data on which all subsequent statistical analyses and mappings
are based, and we compare ACA results based on two different types of co-citation counting - the traditional type that
only counts the first one among a cited work's authors on the one hand and a non-traditional type that takes into
account the first 5 authors of a cited work on the other hand. Results indicate that the picture produced through this non-traditional author co-citation counting contains more coherent author groups and is therefore considerably clearer. However, this picture represents fewer specialties in the research field being studied than that produced through the traditional first-author co-citation counting when the same number of top-ranked authors is selected and analyzed. Reasons for these effects are discussed
La prédiction algorithmique comme activité sociale
International audienceÀ l’heure du machine learning les algorithmes sont de plus en plus observés et analysés en termes comportementaux. Plus encore, l’apprentissage algorithmique est généralement présenté comme l’automatisation du caractère prédictif de nos comportements. En se confrontant à ce problème, cette proposition met en lumière son arrière-fond cybernétique tout en proposant une alternative à la fois épistémologique et sociale qui passe par une réactivation de la philosophie de Gilbert Simondon. Il s’agira plus particulièrement de penser l’apprentissage algorithmique à l’aune de sa théorie du cycle de l’image, et ce afin d’élaborer un cadre conceptuel à partir duquel il est possible de problématiser celui-ci comme une activité sociale au sein de laquelle comportements machiniques et organiques, automatiques et inventifs ne se distribuent pas selon un partage ontologique préétabli, mais s’informent activement. Ce cadre nous permettra, en outre, de jeter les bases de nouvelles perspectives sociologiques sur l’apprentissage algorithmique
Se démarquer et se fondre dans la masse : deux modes de relation entre individus et foules
International audienc
Les affections du corps en milieu numérique :Matérialité et discursivité des traces
info:eu-repo/semantics/publishe
Why data is not enough: Digital traces as control of self and self-control
International audienceAs an alternative to the seemingly natural objectivity and self-evidence of “data,” this paper builds on recent francophone literature by developing a critical conceptualization of “digital traces.” Underlining the materiality and discursiveness of traces allows us to understand and articulate both the technical and sociopolitical implications of digital technology. The philosophies of Gilbert Simondon and Michel Foucault give strong ontological and epistemological groundings for interpreting the relationships between technology and processes of subjectification. In this light, digital traces are framed as objects and products of heteronomous interventions, the logics of which can be traced through the programs and algorithms deployed. Through the empirical examples of “Predictive Policing” and “Quantified Self” digital traces are contrasted with the premises and dreams of Big Data. While the later claims to algorithmically correlative, predict and preempt the future by reducing it to a “what-is-to-come,” the digital trace paradigm offers a new perspective on how forms of self-control and control of the self are interdependent facets of “algorithmic governmentality.
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