Health-AI

The ‘HEALTH-AI’ team consists of anthropologists, social geographers, an expert in E-governance and an ethicist. Together, we ethnographically explore the evolving revolution in global healthcare systems, fueled by Artificial Intelligence (AI). Our team conducts a multi-sited ethnography to uncover the future of ethical AI-informed healthcare, and in this endeavour we work closely with clinicians and nurses from all over the world.

We’re investigating how AI systems are designed and used in various organizations, and try to understand when professional caretakers intervene or resist AI; when AI is useful, and when it is not. We’re studying different national settings with different governmental frameworks and organizational contexts to develop a comprehensive theory on the contextual and organizational factors that shape ethical AI. Our innovative approach includes novel methods, which combines anthropology, futures-thinking, artistic expression, and AI expertise.

Meet the team

Dr. Roanne van Voorst

Principal investogator and supervisor

Prof. Jeanette Pols

Supervisor

Guo Zongtian

Postdoctoral researcher

Albina Abzalova

Phd Researcher

Ismail Umar

Phd Researcher

Rod Mena

Ethical advisor

Michiel Baas

Ethical advisor

Selection of public events & research reports

Please note that this list is incomplete and often behind reality. We work according to the principles of deep, or socalled slow academia, meaning that we prioritize fieldwork, reading and writing over digital updates. A more updated list of academic publications and activities can be found below.

Health-AI

Together with my team of PhDs and Postdocs, I am currently undertaking a multi-sited ethnography of the evolving revolution in global health systems: AI (Artificial Intelligence)-informed healthcare. As health data is increasingly viewed as countries’ ‘future oil’, concerns about ‘algorithmic ethics’ are emerging among scholars and the public. Previous research has shown that datasets in AI (re)produce social biases, discriminate and limit personal autonomy. Nevertheless, such literature has mainly focused on AI design and institutional frameworks, examining the subject via legal, technocratic and philosophical perspectives, while disregarding the socio-cultural context in which AI systems operate, especially in organizations where human agents collaborate with Algorithms. This limitation is problematic because frameworks for ‘ethical AI’ currently regard human oversight as crucial, assuming that humans will correct or resist AI when needed. However, empirical evidence for this assumption is scarce. Little is known about when and why people intervene or resist AI. Previous research is confined to single, primarily Western studies, which precludes generalisation of findings. Our research is innovative on four fronts: 

1. To empirically analyze decisive moments in which data-analysts follow or deviate AI – moments that are deeply impacting national health policies and individual human lives.
2. To do research in six national settings with various governmental frameworks and in different organizational contexts, enabling us to contrast findings, eventually leading to a theory on the contextual and organizational factors underlying ethical AI.
3. To use innovative anthropological methods of future-scenarioing, which will enrich the anthropological discipline by developing and finetuning future-focused research. For this methodology we collaborate with data-scientists, programmers, artists, AI experts, social scientists and physicians.
4. To connect our anthropological insights with the expertise of AI-developers, and partners with relevant health decision-makers and policy-institutions, allowing to both analyze and contribute to fair AI.

Meet the team

  • Dr. Roanne van Voorst, principal investogator and supervisor
  • Prof. Jeanette Pols, supervisor
  • Guo Zudong, postdoctoral researcher
  • Albina Abzalova, Phd Researcher
  • Ismail Umar, PhD Researcher
  • Rod Mena, ethical advisor
  • Michiel Baas, ethical advisor
 

Selection of public events & research reports

Please note that this list is incomplete and often behind reality. We work according to the principles of deep, or socalled slow academia, meaning that we prioritize fieldwork, reading and writing over digital updates. A more updated list of academic publications and activities can be found here.

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