Trained Judgements Artificial Intelligence, Epistemic Tensions and the Production of Scientific Objectivity
Dados Bibliográficos
| ID | 5337548 |
|---|---|
| Autores | G Anichini (0000-0003-2727-5912, CERMES3, autor correspondente), Baptiste Kotras (0000-0003-3323-8392, Laboratoire Interdisciplinaire Sciences Innovations Sociétés (LISIS), Paris, France) |
| Ano | 2024 |
| Volume | 51 |
| Fascículo | 3 |
| Páginas | 631-663 |
| Data de publicação | 2024-07-31 |
| Peer Reviewed | Sim |
| Open Access | Sim |
| Tipo | ARTICLE |
| Periódico | Science Technology & Human Values (JOURNAL) |
| Identificadores do periódico | ISSN: 0162-2439 • E-ISSN: 1552-8251 |
| Editora | SAGE Publications Inc (PUBLISHER) |
| DOI | 10.1177/01622439241262854 |
| OpenAlex | W4401228635 |
| Idioma | EN |
| Citações recebidas | 1 |
| Referências citadas | 62 |
In this paper, we investigate uses of AI (Artificial intelligence) in two distinct fields: radiology and prehistoric archaeology. We examine the normative tensions between the scripts encapsulated within the technology and pre-existing professional and epistemic cultures, as well as the situations in which mechanical objectivity fits with local norms. Through ethnographic observation and interviews in French field sites, we show how in radiology a specific definition of "normal" bodies, embedded within detection tools, conflicts with medical practice, and the way in which non-consensual knowledge in archaeology can challenge the prediction of soil occupation in a prehistoric site. We also highlight the conditions under which AI tools can adhere to certain epistemic norms and become part of professional practices in radiology and prehistoric archaeology. While in radiology AI is judged by its ability to close uncertainties without imposing binary categories, in prehistoric archaeology, its epistemic validity depends on mobilizing exogenous scientific data to increase researchers' reflexivity about their practices and knowledge, suggesting new clues and explanatory paths. This article demonstrates the effectiveness of AI technologies is shaped by local constraints, and why their objectivity is not a given property but an emergent feature arising from specific contexts of use
Archaeology · Epistemology · Field (mathematics) · Normative · Objectivity (philosophy) · Prehistory · Reflexivity · Sociology · Anthropology · Forensic Anthropology and Bioarchaeology Studies · History · Mathematics · Paleopathology and ancient diseases · Philosophy · Pleistocene-Era Hominins and Archaeology · Psychology
Science in action
The System of Professions
Pour une sociologie historique de la quantification
The Relevance of Algorithms
What we talk about when we talk about context
The Relevance of Algorithms
Knowing Algorithms
Medical students' attitude towards artificial intelligence
The TEA Set
Science Observed
The social power of algorithms
Big data
Artifictional intelligence
The Shape of Actions
Sorting Things Out
Social Dynamics of Expectations and Expertise
From daguerreotypes to algorithms
Trust in Numbers
On being “actionable”
The science of artificial intelligence and its critics
Tacit Knowledge, Trust and the Q of Sapphire
Cancer clinical trials in the era of genomic signatures
Voxels in the Brain
Caring for data
We get the algorithms of our ground truths
BRCA Patients and Clinical Collectives
Développement, modes de gouvernance et normes pratiques (une approche socio-anthropologique)
Studying Those Who Study Us
Décision et jugement médicaux en situation de forte incertitude
The nice thing about context is that everyone has it
Perspectives on algorithmic normativities
Mass personalization
The ethics of algorithms
Algorithms as culture
Algorithms in practice
Algorithms as folding
Opening the black box of data-based school monitoring
Quand prédire, c'est gérer
La revanche des neurones
Choose and Book
The Image of Objectivity
The Ethnography of Infrastructure
Epistemic Cultures
Le champ scientifique
Professional Vision
The Society of Algorithms
Technologies of Crime Prediction
| Obras citantes distintas | 1 |
|---|---|
| Citações por ano | 1 |
| Intervalo de citações | 2026 - 2026 (1) |
| Velocidade de citação | current |
| Altamente citado | Não |
| Tipos de citação | Neutras: 1 |