La vulnérabilité comme ouverture à la contingence. Deux enquêtes situées

Haeringer, Anne-Sophie; Pecqueux, Anthony

doi:10.4000/sociologies.14011

sociologies

2020

DOI: 10.4000/sociologies.14011

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La vulnérabilité comme ouverture à la contingence. Deux enquêtes situées

Anne-Sophie Haeringer

Anthony Pecqueux

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Cited by 4 publications

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Assessing biases, relaxing moralism: On ground-truthing practices in machine learning design and application

Jaton

2021

Big Data & Society

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This theoretical paper considers the morality of machine learning algorithms and systems in the light of the biases that ground their correctness. It begins by presenting biases not as a priori negative entities but as contingent external referents—often gathered in benchmarked repositories called ground-truth datasets—that define what needs to be learned and allow for performance measures. I then argue that ground-truth datasets and their concomitant practices—that fundamentally involve establishing biases to enable learning procedures—can be described by their respective morality, here defined as the more or less accounted experience of hesitation when faced with what pragmatist philosopher William James called “genuine options”—that is, choices to be made in the heat of the moment that engage different possible futures. I then stress three constitutive dimensions of this pragmatist morality, as far as ground-truthing practices are concerned: (I) the definition of the problem to be solved (problematization), (II) the identification of the data to be collected and set up (databasing), and (III) the qualification of the targets to be learned (labeling). I finally suggest that this three-dimensional conceptual space can be used to map machine learning algorithmic projects in terms of the morality of their respective and constitutive ground-truthing practices. Such techno-moral graphs may, in turn, serve as equipment for greater governance of machine learning algorithms and systems.

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Assessing biases, relaxing moralism: On ground-truthing practices in machine learning design and application

Jaton

2021

Big Data & Society

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Das Manövrieren inmitten der zahlreichen Wendepunkte der STS

Paulos,

Riom

2023

rac

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Dieser Text ist eine spekulative Reflexion über die Abfassung eines internationalen Konferenzaufrufs – Call for Papers. Er spiegelt diese einzigartige Übung wider, sich zu einem bestimmten Thema an eine Gemeinschaft von Fachleuten zu wenden. Die Frage der materiellen Fragilität, der sich dieser Call for Papers widmet, wird in diesem Sinne nicht konzeptionell oder methodologisch, sondern aus einer forschungspraktischen Perspektive behandelt. In Form eines Briefwechsels wird berichtet, wie ein „Wendepunkt“ oder ein disziplinärer Moment die Art und Weise, wie Forschung betrieben und gedacht wird, initiiert, beeinflusst und lenkt.

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Manœuvrer au milieu des multiples tournants des STS

Paulos,

Riom

2023

rac

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Ce texte se propose de revenir de manière spéculative sur l’écriture d’un appel à communication pour une conférence internationale. Depuis les coulisses, il vise à réfléchir à cet exercice singulier qui consiste à s’adresser à une communauté de collègues autour d’une discipline et/ou d’une thématique particulière. La question des fragilités matérielles – à laquelle cet appel était consacré – y est envisagée de ce point de vue, c’est-à-dire non pas de façon conceptuelle ou méthodologique, mais à partir d’une expérience pratique de la recherche. Sous la forme d’un échange épistolaire, le texte rend compte de la façon dont un « tournant » ou un moment disciplinaire engage, fait faire et oriente des manières de mener et de penser des recherches.

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La vulnérabilité comme ouverture à la contingence. Deux enquêtes situées

Cited by 4 publications

References 11 publications

Assessing biases, relaxing moralism: On ground-truthing practices in machine learning design and application

Assessing biases, relaxing moralism: On ground-truthing practices in machine learning design and application

Das Manövrieren inmitten der zahlreichen Wendepunkte der STS

Manœuvrer au milieu des multiples tournants des STS

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