Deep Culture - Living with Difference in the Age of Deep Learning
DEEP CULTURE aims to critically explore the intersection of deep learning and cultural production through an interdisciplinary framework, fostering new methodologies and public engagement.
Projectdetails
In 2022, the world appeared transformed by a new consumer artificial intelligence (AI), which has dazzled observers with the ability to generate text, images or music. This transformation has been brought about not by general AI but by deep learning, a specific subset of machine learning that has come to dominate AI scientifically and commercially. This has given rise to an emergent ‘deep culture’, which is produced with universal data extraction and on an industrial scale. While these developments have led to much public anxiety, we lack an understanding of the fundamental shift in cultural relations through deep learning, and what this means for cultural production and analysis.
Introduction to DEEP CULTURE
DEEP CULTURE is the first project to develop ‘deep culture’ as an object of study as well as a method and capacity to attend to this historical moment. It claims that the relations between culture and deep learning can be reconfigured if humanistic ideas are included, which address the complexities of culture and values of difference.
Objectives of the Project
To this end, the project advances a radical interdisciplinary framework at the intersection of digital humanities, cultural studies, and computer science. DEEP CULTURE has three main objectives:
- To develop a critical inquiry about deep culture through epistemic translations of keywords and practices in deep learning.
- To advance methodologies for a critical inquiry with deep culture by reconfiguring current deep learning techniques and practices through humanistic ideas and values.
- To promote productive, critical relationships with and beyond deep culture by collectively contesting deep learning’s cultural enactments and co-producing new ones with diverse publics.
Empirical Context
Empirically, the project is situated at three archival sites: historical, real-time, and incidental archives.
Leadership and Location
Based in Amsterdam, DEEP CULTURE is led by the first Distinguished University Professor in AI and Humanities and an expert on interdisciplinary research collaborations.
Financiële details & Tijdlijn
Financiële details
Subsidiebedrag | € 2.500.000 |
Totale projectbegroting | € 2.500.000 |
Tijdlijn
Startdatum | 1-12-2024 |
Einddatum | 30-11-2029 |
Subsidiejaar | 2024 |
Partners & Locaties
Projectpartners
- UNIVERSITEIT VAN AMSTERDAMpenvoerder
Land(en)
Vergelijkbare projecten binnen European Research Council
Project | Regeling | Bedrag | Jaar | Actie |
---|---|---|---|---|
The Culture of Algorithmic Models: Advancing the Historical Epistemology of Artificial IntelligenceThis project aims to develop a new epistemology and history of AI by tracing its origins in algorithmic modeling, impacting fields like digital humanities and AI ethics. | ERC Consolid... | € 1.927.573 | 2024 | Details |
Machine learning in science and society: A dangerous toy?This project evaluates the epistemic strengths and risks of deep learning models as "toy models" to enhance understanding and trust in their application across science and society. | ERC Starting... | € 1.500.000 | 2025 | Details |
Human collaboration with AI agents in national health governance: organizational circumstances under which data analysts and medical experts follow or deviate from AI.This project aims to explore the socio-cultural dynamics of AI in health governance across six countries to develop a theory on ethical AI intervention and its impact on national health policies. | ERC Starting... | € 1.499.961 | 2023 | Details |
Natural Language Understanding for non-standard languages and dialectsDIALECT aims to enhance Natural Language Understanding by developing algorithms that integrate dialectal variation and reduce bias in data and labels for fairer, more accurate language models. | ERC Consolid... | € 1.997.815 | 2022 | Details |
Reading Minds and MachinesThe project aims to decode training data from Deep Neural Networks and brain activity, enhancing data privacy and communication for locked-in patients while improving insights in both fields. | ERC Advanced... | € 2.499.333 | 2024 | Details |
The Culture of Algorithmic Models: Advancing the Historical Epistemology of Artificial Intelligence
This project aims to develop a new epistemology and history of AI by tracing its origins in algorithmic modeling, impacting fields like digital humanities and AI ethics.
Machine learning in science and society: A dangerous toy?
This project evaluates the epistemic strengths and risks of deep learning models as "toy models" to enhance understanding and trust in their application across science and society.
Human collaboration with AI agents in national health governance: organizational circumstances under which data analysts and medical experts follow or deviate from AI.
This project aims to explore the socio-cultural dynamics of AI in health governance across six countries to develop a theory on ethical AI intervention and its impact on national health policies.
Natural Language Understanding for non-standard languages and dialects
DIALECT aims to enhance Natural Language Understanding by developing algorithms that integrate dialectal variation and reduce bias in data and labels for fairer, more accurate language models.
Reading Minds and Machines
The project aims to decode training data from Deep Neural Networks and brain activity, enhancing data privacy and communication for locked-in patients while improving insights in both fields.
Vergelijkbare projecten uit andere regelingen
Project | Regeling | Bedrag | Jaar | Actie |
---|---|---|---|---|
Een standaard voor productiewaardige Deep Learning systemenHet project richt zich op het verbeteren van audio- en video-analyse systemen door samenwerking tussen Media Distillery, NovoLanguage en een partner, met als doel hogere kwaliteit en snellere ontwikkeling via gedeelde technologieën. | Mkb-innovati... | € 104.061 | 2016 | Details |
DeepDetectIDHet project ontwikkelt DeepDetectID, een schaalbaar AI-platform voor het detecteren van deepfakes in audio, video en foto's ter ondersteuning van identiteitsverificatie en veiligheid. | Mkb-innovati... | € 200.000 | 2021 | Details |
Improving social competences of virtual agents through artificial consciousness based on the Attention Schema TheoryASTOUND aims to develop an AI architecture for artificial consciousness using Attention Schema Theory to enhance social interaction and natural language understanding in machines. | EIC Pathfinder | € 3.330.897 | 2022 | Details |
Project HominisHet project richt zich op het ontwikkelen van een ethisch AI-systeem voor natuurlijke taalverwerking dat vooroordelen minimaliseert en technische, economische en regelgevingsrisico's beheert. | Mkb-innovati... | € 20.000 | 2022 | Details |
Een standaard voor productiewaardige Deep Learning systemen
Het project richt zich op het verbeteren van audio- en video-analyse systemen door samenwerking tussen Media Distillery, NovoLanguage en een partner, met als doel hogere kwaliteit en snellere ontwikkeling via gedeelde technologieën.
DeepDetectID
Het project ontwikkelt DeepDetectID, een schaalbaar AI-platform voor het detecteren van deepfakes in audio, video en foto's ter ondersteuning van identiteitsverificatie en veiligheid.
Improving social competences of virtual agents through artificial consciousness based on the Attention Schema Theory
ASTOUND aims to develop an AI architecture for artificial consciousness using Attention Schema Theory to enhance social interaction and natural language understanding in machines.
Project Hominis
Het project richt zich op het ontwikkelen van een ethisch AI-systeem voor natuurlijke taalverwerking dat vooroordelen minimaliseert en technische, economische en regelgevingsrisico's beheert.