Marthe Stevens
Biographic Data
| ID | 3583079 |
|---|---|
| NAME | Marthe Stevens |
| GIVEN NAMES | Marthe |
| FAMILY NAME | Stevens |
| SIGNATURE | STEVENS M |
| AFFILIATIONS | Erasmus University Rotterdam |
| ORCID | 0000-0003-0135-0523 |
| VERIFIED | Yes |
| TOTAL WORKS | 8 |
| TOTAL CITATIONS | 20 |
| AUTHOR COUNT | 8 |
| EDITOR COUNT | 0 |
| FIRST PUBLICATION YEAR | 2018 |
| LATEST PUBLICATION YEAR | 2024 |
| H-INDEX | 3 |
Sphere transgressions
A careful approach to artificial intelligence
Machine learning approaches are being developed to contribute to the treatment of patients and the organisation of care. These new approaches are created in complex environments that include data and computational models as well as new practices, roles and competencies. In such settings, individualised conceptions of agents bearing responsibility need rethinking. In response, we elaborate on the concept of epistemic responsibility based on De la …
Sphere transgressions in medical research
In the last decade, large technology companies have started many initiatives to stimulate and innovate in the sphere of medical research. A prominent example is the ResearchKit software framework launched by tech giant Apple in 2015. This software framework enables medical researchers to develop research apps on the iPhone that collect and access diverse types of research data. The 'sphere transgressions' theoretical lens (Sharon, 2021a; 2021b) d…
The European health data space
Ethics as Discursive Work
The allure of a "data-driven" future healthcare system continues to seduce many. Increasingly, work in Science & Technology Studies and related fields started to interrogate the saliency of this promissory rhetoric by raising ethical questions concerning epistemology, bias, surveillance, security, and opacity. Less visible is how ethical arguments are used as part of discursive work by various practitioners engaged in data-driven initiatives in h…
Why Personal Dreams Matter
Recent buzzes around big data, data science and artificial intelligence portray a data-driven future for healthcare. As a response, Europe's key players have stimulated the use of big data technologies to make healthcare more efficient and effective. Critical Data Studies and Science and Technology Studies have developed many concepts to reflect on such overly positive narratives and conduct critical policy evaluations. In this study, we argue th…
Epistemic virtues and data-driven dreams
Data science and psychiatry have diverse epistemic cultures that come together in data-driven initiatives (e.g., big data, machine learning). The literature on these initiatives seems to either downplay or overemphasize epistemic differences between the fields. In this paper, we study the convergence and divergence of the epistemic cultures of data science and psychiatry. This approach is more likely to capture where and how the cultures differ a…
Conceptualizations of Big Data and their epistemological claims in healthcare
In recent years, the healthcare field welcomed an emerging field of practices captured under the umbrella term 'Big Data'. This term is surrounded with positive rhetoric and promises about the ability to analyse real-world data quickly and comprehensively. Such rhetoric is highly consequential in shaping debates on Big Data. While the fields of Science and Technology Studies and Critical Data Studies have been instrumental in elaborating the negl…
Conceptualizations of Big Data and their epistemological claims in healthcare
In recent years, the healthcare field welcomed an emerging field of practices captured under the umbrella term 'Big Data'. This term is surrounded with positive rhetoric and promises about the ability to analyse real-world data quickly and comprehensively. Such rhetoric is highly consequential in shaping debates on Big Data. While the fields of Science and Technology Studies and Critical Data Studies have been instrumental in elaborating the negl…
Epistemic virtues and data-driven dreams
Data science and psychiatry have diverse epistemic cultures that come together in data-driven initiatives (e.g., big data, machine learning). The literature on these initiatives seems to either downplay or overemphasize epistemic differences between the fields. In this paper, we study the convergence and divergence of the epistemic cultures of data science and psychiatry. This approach is more likely to capture where and how the cultures differ a…
Why Personal Dreams Matter
Recent buzzes around big data, data science and artificial intelligence portray a data-driven future for healthcare. As a response, Europe's key players have stimulated the use of big data technologies to make healthcare more efficient and effective. Critical Data Studies and Science and Technology Studies have developed many concepts to reflect on such overly positive narratives and conduct critical policy evaluations. In this study, we argue th…
Ethics as Discursive Work
The allure of a "data-driven" future healthcare system continues to seduce many. Increasingly, work in Science & Technology Studies and related fields started to interrogate the saliency of this promissory rhetoric by raising ethical questions concerning epistemology, bias, surveillance, security, and opacity. Less visible is how ethical arguments are used as part of discursive work by various practitioners engaged in data-driven initiatives in h…
Conceptualizations of Big Data and their epistemological claims in healthcare
In recent years, the healthcare field welcomed an emerging field of practices captured under the umbrella term 'Big Data'. This term is surrounded with positive rhetoric and promises about the ability to analyse real-world data quickly and comprehensively. Such rhetoric is highly consequential in shaping debates on Big Data. While the fields of Science and Technology Studies and Critical Data Studies have been instrumental in elaborating the negl…
Epistemic virtues and data-driven dreams
Data science and psychiatry have diverse epistemic cultures that come together in data-driven initiatives (e.g., big data, machine learning). The literature on these initiatives seems to either downplay or overemphasize epistemic differences between the fields. In this paper, we study the convergence and divergence of the epistemic cultures of data science and psychiatry. This approach is more likely to capture where and how the cultures differ a…
Why Personal Dreams Matter
Recent buzzes around big data, data science and artificial intelligence portray a data-driven future for healthcare. As a response, Europe's key players have stimulated the use of big data technologies to make healthcare more efficient and effective. Critical Data Studies and Science and Technology Studies have developed many concepts to reflect on such overly positive narratives and conduct critical policy evaluations. In this study, we argue th…
The European health data space
Ethics as Discursive Work
The allure of a "data-driven" future healthcare system continues to seduce many. Increasingly, work in Science & Technology Studies and related fields started to interrogate the saliency of this promissory rhetoric by raising ethical questions concerning epistemology, bias, surveillance, security, and opacity. Less visible is how ethical arguments are used as part of discursive work by various practitioners engaged in data-driven initiatives in h…
Sphere transgressions
A careful approach to artificial intelligence
Machine learning approaches are being developed to contribute to the treatment of patients and the organisation of care. These new approaches are created in complex environments that include data and computational models as well as new practices, roles and competencies. In such settings, individualised conceptions of agents bearing responsibility need rethinking. In response, we elaborate on the concept of epistemic responsibility based on De la …
Sphere transgressions in medical research
In the last decade, large technology companies have started many initiatives to stimulate and innovate in the sphere of medical research. A prominent example is the ResearchKit software framework launched by tech giant Apple in 2015. This software framework enables medical researchers to develop research apps on the iPhone that collect and access diverse types of research data. The 'sphere transgressions' theoretical lens (Sharon, 2021a; 2021b) d…
Political science (6 works) · Sociology (6 works) · Ethics and Social Impacts of AI (5 works) · Ethics in Clinical Research (5 works) · Law (5 works) · Computer Science (4 works) · Engineering ethics (4 works) · Epistemology (4 works) · Health care (4 works) · Big data (3 works)