AI for/by the majority world: From technologies of dispossession to technologies of radical care
Notice bibliographique
Résumé
The dominant and celebratory discourse surrounding AI often fails to acknowledge the intricate dynamics and implications associated with the human, material, and environmental costs of technological development, particularly in the midst of a civilizational crisis [5]. Furthermore, hegemonic AI, primarily developed by large technology corporations, capitalizes on the resources, data, and labor of the majority world only to be deployed as a glamorous product that furthers the accumulation of privilege, wealth, and power by global elites. As a result, these hegemonic intelligent technologies originate from a predatory and violent world model that has been imposed as a universal paradigm of existence. These dominant technologies are intentionally designed to perpetuate power asymmetries. The so-called artificial intelligence, marketed as a revolutionary innovation, has proven to be the offspring of interconnected systems of oppression: a capitalist mode of production; a colonial system of epistemic, economic, social, racial, and cultural dominance; and a patriarchal order of violence that fulfills its own prophecy [10]. Artificial intelligence, driven by influential global actors with market-driven and war-driven interests, materializes as a socio-technical assemblage that optimizes capital accumulation through dispossession [3] and the exertion of violence over the territories and populations of the majority world [8]. Hegemonic AI technologies are fundamentally technologies of dispossession, appropriating the commons for their development. Their creation is governed by macro-structural forces guided by the market and powerful actors seeking control, as control is a prerequisite for wealth accumulation. Control encompasses natural resources (territory), knowledge (processing information and data), labor (productive force), bodies (labor and the capacity to produce knowledge), subjectivity (sensibility and identity), and intersubjective relations (ways of relating, living, and coexisting) [7]. Dispossession arises from the interconnections of violent systems operating at both micro and macro scales. Dispossession manifests throughout the entire lifecycle of AI, spanning from design and development to deployment, use, and disposal [6]. The human, material, and environmental costs associated with technological development are obscured by narratives emphasizing efficiency, optimization, and the automation of the world. Big capital, including finance, pharmaceuticals, agribusiness, mining, and technology, forms alliances to control global value chains and knowledge production systems, ensuring that the ultimate benefits remain concentrated in the hands of a few. Concentration of power, wealth, and knowledge widens the gaps between individuals, communities, countries, and regions, erasing them physically, socially, and epistemically. As the gap continues to widen due to the accelerating momentum of production and capitalist accumulation, the depletion of the planet’s resources and life-supporting systems draws nearer. To dismantle socio-technically mediated systems of violence, it is imperative to address power imbalances and rediscover the fundamental relational nature of existence. Alternative models of the world and dignified futures necessitate alternative models of technological development that are grounded in values associated with a radical ethics of care [1], communality [2], conviviality [4], and shared responsibility for the consequences of human impact on the planet [9].
Récupéré en direct depuis OpenAlex et désinversé. Les résumés ne sont pas conservés dans cette base de données : les index inversés représentent 8,6 Go des 9,3 Go de texte de la base, et le serveur dispose de 13 Go libres.
Comment cette classification a été obtenuedéplier
Prédiction machine sur la base complète
Imitation des enseignantsNi prévalence calibrée, ni vérité terrain. Validation humaine à venir. Le volet Gemma est une étiquette directe du modèle pour chaque travail de la base, lue sur la notice réduite au titre. Le volet Codex est un classifieur appris des 10 348 étiquettes directes de Codex et calibré sur les taux pondérés de l'échantillon; les champs sans appui suffisant ne portent aucun appel Codex. Le mode candidate est l'union des deux volets; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont pas des étiquettes humaines.
Scores du classifieur distillé par catégorie (deux têtes)
| Catégorie | Codex | Gemma |
|---|---|---|
| Métarecherche | 0,005 | 0,005 |
| Méta-épidémiologie (sens strict) | 0,001 | 0,000 |
| Méta-épidémiologie (sens large) | 0,000 | 0,000 |
| Bibliométrie | 0,002 | 0,001 |
| Études des sciences et des technologies | 0,006 | 0,048 |
| Communication savante | 0,015 | 0,021 |
| Science ouverte | 0,001 | 0,007 |
| Intégrité de la recherche | 0,004 | 0,006 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,006 | 0,001 |
Scores machine (provisoires)
Les deux têtes enseignantes du modèle étudiant, lues sur ce travail. Un score ordonne la base pour la relecture; il n'affirme jamais une catégorie, et le statut de validation accompagne chaque rangée tel quel.
Scores de référence d'un modèle non mature (critères de maturité non atteints, 7 itérations). Un score ordonne; il n'affirme jamais une catégorie.
score_only:v0-immature-baseline · tel quel depuis la passe de notation : score_only signifie que le nombre peut ordonner les travaux, et qu'aucune étiquette de catégorie n'en découleClassification
machine, non validéePrédiction automatique; un appel candidat d’une seule source (Gemma direct ou Codex distillé), pas un consensus.
Le détail, modèle par modèle et score par score, se trouve en fin de page sous « Comment cette classification a été obtenue ».