Dieuwertje Luitse
Biographic Data
| ID | 2744527 |
|---|---|
| NAME | Dieuwertje Luitse |
| GIVEN NAMES | Dieuwertje |
| FAMILY NAME | Luitse |
| SIGNATURE | LUITSE D |
| AFFILIATIONS | University of Amsterdam |
| ORCID | 0000-0003-0652-3315 |
| VERIFIED | Yes |
| TOTAL WORKS | 7 |
| TOTAL CITATIONS | 11 |
| AUTHOR COUNT | 7 |
| EDITOR COUNT | 0 |
| FIRST PUBLICATION YEAR | 2021 |
| LATEST PUBLICATION YEAR | 2026 |
| H-INDEX | 1 |
Zones of (un)certainty: Studying the temporal stabilization of ground truths for medical AI
Medical data annotation is a critical yet contingent process that (re)configures ambiguous medical decisions and data representations into ground truths for artificial intelligence (AI). Extending critical data, AI, and STS research on uncertainty in data annotation, this article develops the concept of zones of (un)certainty to capture the epistemic time-spaces through which annotators transform uncertainty and dissonance into stabilized ground-…
The Politics of Machine-Learning Evaluation: From Lab to Industry
Artificial Intelligence (AI) applications are today implemented across various societal sectors, ranging from health care and security to taking part in shaping the media environment we encounter online. In the last decade there has been a significant shift in the field of AI, as the development of AI applications is no longer confined to the laboratory, but rather widely used and tested in and on societies. With this rapid industrialisation of A…
The Political Economy of Ai as Platform: Infrastructures, Power, and the Ai Industry
The artificial intelligence (AI) sector is experiencing rapid growth, with a projected market size of $1.3 trillion by 2032 according to industry reports. The landscape shifted significantly with the launch of ChatGPT in late 2022, prompting major players like Google, Amazon, Microsoft, and Meta, alongside popular apps such as TikTok and Snapchat, to make substantial investments in AI. There has been an influx of new AI products and updates, resh…
AI competitions as infrastructures of power in medical imaging
This article examines how platform-based AI competitions structure power relations in medical imaging research. It focuses on two leading platforms, Kaggle and Grand Challenge, which provide organisational as well as infrastructural support to run AI competitions. In dialogue with critical AI and platform studies research, we investigate how such competitions are organised – under which infrastructural conditions and by whom – and how this shapes…
Platform power in AI: The evolution of cloud infrastructures in the political economy of artificial intelligence
This paper empirically explores how AWS, Microsoft Azure, and Google Cloud strategically attempt to operationalise infrastructural power in AI development and implementation through their ecosystems for cloud AI
Ai Competitions as Infrastructures: Examining Power Relations on Kaggle and Grand Challenge in Ai-Driven Medical Imaging
Artificial Intelligence (AI) is quickly being taken-up across scientific disciplines, medical imaging is no exception. To stimulate development and facilitate the scientific evaluation of new approaches, AI-based research in medical imaging is increasingly organised in a competitive manner through digital machine-learning development platforms such as Kaggle and Grand Challenge—two of the leading platforms in the field. For medical image analysis…
The great Transformer: Examining the role of large language models in the political economy of AI
In recent years, AI research has become more and more computationally demanding. In natural language processing (NLP), this tendency is reflected in the emergence of large language models (LLMs) like GPT-3. These powerful neural network-based models can be used for a range of NLP tasks and their language generation capacities have become so sophisticated that it can be very difficult to distinguish their outputs from human language. LLMs have rai…
The great Transformer: Examining the role of large language models in the political economy of AI
In recent years, AI research has become more and more computationally demanding. In natural language processing (NLP), this tendency is reflected in the emergence of large language models (LLMs) like GPT-3. These powerful neural network-based models can be used for a range of NLP tasks and their language generation capacities have become so sophisticated that it can be very difficult to distinguish their outputs from human language. LLMs have rai…
The great Transformer: Examining the role of large language models in the political economy of AI
In recent years, AI research has become more and more computationally demanding. In natural language processing (NLP), this tendency is reflected in the emergence of large language models (LLMs) like GPT-3. These powerful neural network-based models can be used for a range of NLP tasks and their language generation capacities have become so sophisticated that it can be very difficult to distinguish their outputs from human language. LLMs have rai…
Ai Competitions as Infrastructures: Examining Power Relations on Kaggle and Grand Challenge in Ai-Driven Medical Imaging
Artificial Intelligence (AI) is quickly being taken-up across scientific disciplines, medical imaging is no exception. To stimulate development and facilitate the scientific evaluation of new approaches, AI-based research in medical imaging is increasingly organised in a competitive manner through digital machine-learning development platforms such as Kaggle and Grand Challenge—two of the leading platforms in the field. For medical image analysis…
Platform power in AI: The evolution of cloud infrastructures in the political economy of artificial intelligence
This paper empirically explores how AWS, Microsoft Azure, and Google Cloud strategically attempt to operationalise infrastructural power in AI development and implementation through their ecosystems for cloud AI
The Politics of Machine-Learning Evaluation: From Lab to Industry
Artificial Intelligence (AI) applications are today implemented across various societal sectors, ranging from health care and security to taking part in shaping the media environment we encounter online. In the last decade there has been a significant shift in the field of AI, as the development of AI applications is no longer confined to the laboratory, but rather widely used and tested in and on societies. With this rapid industrialisation of A…
The Political Economy of Ai as Platform: Infrastructures, Power, and the Ai Industry
The artificial intelligence (AI) sector is experiencing rapid growth, with a projected market size of $1.3 trillion by 2032 according to industry reports. The landscape shifted significantly with the launch of ChatGPT in late 2022, prompting major players like Google, Amazon, Microsoft, and Meta, alongside popular apps such as TikTok and Snapchat, to make substantial investments in AI. There has been an influx of new AI products and updates, resh…
AI competitions as infrastructures of power in medical imaging
This article examines how platform-based AI competitions structure power relations in medical imaging research. It focuses on two leading platforms, Kaggle and Grand Challenge, which provide organisational as well as infrastructural support to run AI competitions. In dialogue with critical AI and platform studies research, we investigate how such competitions are organised – under which infrastructural conditions and by whom – and how this shapes…
Zones of (un)certainty: Studying the temporal stabilization of ground truths for medical AI
Medical data annotation is a critical yet contingent process that (re)configures ambiguous medical decisions and data representations into ground truths for artificial intelligence (AI). Extending critical data, AI, and STS research on uncertainty in data annotation, this article develops the concept of zones of (un)certainty to capture the epistemic time-spaces through which annotators transform uncertainty and dissonance into stabilized ground-…
Computer Science (4 works) · Political science (4 works) · Politics (4 works) · Artificial Intelligence (3 works) · Artificial Intelligence in Healthcare and Education (3 works) · Business (3 works) · Economics (3 works) · Biomedical and Engineering Education (2 works) · Data science (2 works) · Economic system (2 works)