General Information
Why we do research?
Driven by curiosity, we want to study the development of digital innovations and their intended and unintended consequences. We want to look beyond the hypes and actively engage with organizational professionals who are managing and developing technologies.
Why
We are a multi-disciplinary group of researchers with academic backgrounds in business administration, sociology, communication science, anthropology, philosophy, engineering, industrial design, and computer science. We study the development of digital innovations and the intended and unintended consequences of the use of digital technologies in organizations.
What research do we do?
Our research is concerned with the impact role of Artificial Intelligence in the domain of Medical Imaging. We research how AI changes the work of the radiologist, the development of AI applications in this domain and how at their clinical implementation.
What
How
How we do research?
Our hallmark of our way of working is that we do embedded research. We study the development and use of digital technologies within its context over longer periods of time and often through ethnographic methods of research, allowing us develop a deep understanding of the phenomenon under study.
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Future of work: Changing work and organizations in the digital age
In this project we want to understand radiologists’ and radiographers’ experiences with AI over time. We try to grasp how professionals perceive AI’s potential and actual impact on their work and profession, and to understand their strategies for coping with rapid developments of AI applications. So far, we have conducted interviews with more than 100 professionals from the field of medical imaging (primarily radiologists) from 28 countries with diverse backgrounds, work positions, and experiences on AI.
This research has been supported by Prof. Frans Feldberg and the European Society of Medical Imaging Informatics (EuSoMII)’s scientific and management boards, particularly Dr. Paul Algra, Dr. Erik Ranschaert, and Dr. Peter van Ooijen.
Maneuvering uncertainty and urgency in working with artificial intelligence
By: Kim, Bomi & Rezazade Mehrizi, Mohammad H.
AI@Work Conference Amsterdam
March 2020
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Narrow Intelligence: a socio-technical perspective of the narrowness of artificial intelligence at work
By: Rezazade Mehrizi, Mohammad H.
AI@Work Conference Amsterdam
March 2020
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By: Worringen Felix
Master Thesis, Vrije Universiteit
Amsterdam, 2019
Development of AI applications in the domain of medical imaging
With this project we aim to understand how startups and established firms develop and position their AI applications. We have studied all AI applications that are offered in the market in the medical imaging field. We analyzed all applications based on their features, functionalities, target body part, and modality. In addition, we examined the regulatory status of these applications (e.g., having FDA or CE approval).
We also looked into how these applications seek to impact the work of radiologists (e.g., automate, augment, or extend), in which form these applications are offered to work (e.g., on-premise, cloud-based), as well as integration issues with the workflow (e.g., integrated with PACS/RIS).
By: Homan, Milou
Master Thesis, Vrije Universiteit Amsterdam, School of Business and Economics, 2019
By: Dewi, Ayumindya Paramita
Master Thesis, Vrije Universiteit Amsterdam, School of Business and Economics, 2019
Clinical implementation of AI applications
In this project we aim to learn more about the actual clinical implementations of AI applications. For this purpose, we collaborate with two radiology departments that are considered to be leading examples of AI implementation in the Netherlands: North-West Ziekenhuis (NWZ) and Leiden University Medical Center (LUMC).
To understand how radiologists work with AI technologies, we conduct at-work observations complemented by interviews. We examine how various practices, processes, and organizational structures are reorganized in the department to support effective and fundamental implementation of AI solutions. Dr. Paul Algra is the key initiator and supporting figure of the research in NWZ. Professor Mark van Buchem is the head of the radiology department and key supporting figure of the study in LUMC.
By: Seibel, Heiko
Master Thesis, Vrije Universiteit Amsterdam, School of Business and Economics, 2021