AI systems are getting an undeniable foothold in healthcare. From the use in diagnostics and patient data analysis to the use in hospital management, pharmaceutical design, preventive and personalized medicine; AI is transforming the way we organise and deliver healthcare. The use of AI technology is widely expected to lead to better care and lower costs.
However, AI technology in the healthcare domain will also lead to complex challenges and ethical questions with respect to the trustworthiness, reliability, responsibility, explainability and fairness of AI-based systems. Healthcare is a domain that is very much driven by human expertise and human communication. The widespread use of AI technology will require new policies, new governance, redesign of workflows in clinical practice, expansion of medical ethics to cover the ramifications of use of AI, AI system scrutiny and a heightened sense of professional awareness of healthcare workers
Projects
PhDs of EMC, PhDs of TU Delft and SAS working together.
The community is involved in:
- WHO Expert group of the Global Ethics and AI report: Ethics and governance of artificial intelligence for health
- Creation of a global curriculum for ethics & AI: Design for Values in AI for Medicine and Healthcar
SoBigData | ESFRI Roadmap 2021
Partners
SAS
SAS, a world leading software company with a Data Ethics Practice.
WHO
WHO, World Health Organization
Researchers & publications
Alessandro Bozzon
Faculty of Industrial Design Engineering
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- Sun, Zhu, et al. "Recurrent knowledge graph embedding for effective recommendation." Proceedings of the 12th ACM conference on recommender systems. 2018.
Stefan Buisman
Faculty of Technology Policy & Management
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- Buijsman, Stefan. "Defining explanation and explanatory depth in XAI." Minds and Machines 32.3 (2022): 563-584.
- Buijsman, Stefan, and Herman Veluwenkamp. "Spotting when algorithms are wrong." Minds and Machines (2022): 1-22.
Samantha Copeland
Faculty of Technology Policy & Management
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- Anjum, Rani Lill, Samantha Copeland, and Elena Rocca. Rethinking causality, complexity and evidence for the unique patient: a causehealth resource for healthcare professionals and the clinical encounter. Springer Nature, 2020.
Juan Duran
Faculty of Technology Policy & Management
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- Durán, Juan Manuel, and Karin Rolanda Jongsma. "Who is afraid of black box algorithms? On the epistemological and ethical basis of trust in medical AI." Journal of Medical Ethics 47.5 (2021): 329-335.
- Durán, Juan M., Martin Sand, and Karin Jongsma. "The ethics and epistemology of explanatory AI in medicine and healthcare." Ethics and Information Technology 24.4 (2022): 42.
- Durán, Juan M. "Dissecting scientific explanation in AI (sXAI): A case for medicine and healthcare." Artificial Intelligence 297 (2021): 103498.
Elisa Giaccardi
Faculty of Industrial Design Engineering
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- Coskun, Aykut, et al. "More-than-human Concepts, Methodologies, and Practices in HCI." CHI Conference on Human Factors in Computing Systems Extended Abstracts. 2022.
Jeroen van den Hoven
Faculty of Technology Policy & Management
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- Aizenberg, Evgeni, and Jeroen Van Den Hoven. "Designing for human rights in AI." Big Data & Society 7.2 (2020): 2053951720949566.
- Van den Hoven, Jeroen, Pieter E. Vermaas, and Ibo Van de Poel, eds. Handbook of ethics, values, and technological design: Sources, theory, values and application domains. Dordrecht: Springer Netherlands, 2015.
Olya Kudina
Faculty of Technology Policy & Management
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- Kudina, Olya, and Bas de Boer. "Co‐designing diagnosis: Towards a responsible integration of Machine Learning decision‐support systems in medical diagnostics." Journal of evaluation in clinical practice 27.3 (2021): 529-536.
- Van Brakel, Rosamunde, et al. "Bridging values: Finding a balance between privacy and control. The case of Corona apps in Belgium and the Netherlands." Journal of Contingencies and Crisis Management 30.1 (2022): 50-58.
- De Boer, Bas, and Olya Kudina. "What is morally at stake when using algorithms to make medical diagnoses? Expanding the discussion beyond risks and harms." Theoretical medicine and bioethics (2021): 1-22.
Jacobien Oosterhoff
Faculty of Technology Policy & Management
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- Oosterhoff, Jacobien HF, and Job N. Doornberg. "Artificial intelligence in orthopaedics: false hope or not? A narrative review along the line of Gartner’s hype cycle." EFORT Open Reviews 5.10 (2020): 593-603.
- Groot, Olivier Q., et al. "Availability and reporting quality of external validations of machine-learning prediction models with orthopedic surgical outcomes: a systematic review." Acta Orthopaedica 92.4 (2021): 385-393.
Giorgia Pozzi
Faculty of Technology Policy & Management
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- Pozzi, Giorgia. "Automated opioid risk scores: a case for machine learning-induced epistemic injustice in healthcare." Ethics and Information Technology 25.1 (2023): 3.
- Pozzi, Giorgia. "Testimonial injustice in medical machine learning." Journal of Medical Ethics (2023).
Martin Sand
Faculty of Technology Policy & Management
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- Sand, Martin, Juan Manuel Durán, and Karin Rolanda Jongsma. "Responsibility beyond design: Physicians’ requirements for ethical medical AI." Bioethics 36.2 (2022): 162-169.
- Durán, Juan M., Martin Sand, and Karin Jongsma. "The ethics and epistemology of explanatory AI in medicine and healthcare." Ethics and Information Technology 24.4 (2022): 42.
Helma Torkamaan
Faculty of Technology Policy & Management
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- Torkamaan, Helma, and Jürgen Ziegler. "Integrating behavior change and persuasive design theories into an example mobile health recommender system." Adjunct proceedings of the 2021 ACM international joint conference on pervasive and ubiquitous computing and proceedings of the 2021 ACM international symposium on wearable computers. 2021.Helma Torkamaan and Jürgen Ziegler. 2022.
- Torkamaan, Helma, and Jürgen Ziegler. "Recommendations as challenges: Estimating required effort and user ability for health behavior change recommendations." 27th International Conference on Intelligent User Interfaces. 2022.
- Hanna Schäfer, Santiago Hors-Fraile, Raghav Pavan Karumur, André Calero Valdez, Schäfer, Hanna, et al. "Towards health (aware) recommender systems." Proceedings of the 2017 international conference on digital health. 2017.
- Torkamaan, Helma, and Jürgen Ziegler. "Multi-Criteria Rating-Based Preference Elicitation in Health Recommender Systems." HealthRecSys@ RecSys. 2018.
- Elahi, Mehdi, et al. "Beyond algorithmic fairness in recommender systems." Adjunct proceedings of the 29th ACM conference on user modeling, adaptation and personalization. 2021.