Human-centered design of artificial-intelligence-assisted work systems in healthcare: Findings from multi-stakeholder dialogues
DOI:
https://doi.org/10.14512/tatup.7226Keywords:
artificial intelligence, healthcare, human-centered work design, participatory technology assessmentAbstract
Artificial intelligence (AI)-assisted technologies, such as decision support and monitoring systems, hold the potential to significantly improve efficiency and quality of care in the health sector. However, given the impact that such technologies can also have on work requirements and the moral agency of healthcare personnel, it is imperative – from an occupational safety and health perspective – to incorporate established criteria for human-centered work design and ethical design criteria into technology development throughout the entire life cycle. Existing AI guidelines and regulations such as the EU’s AI Act address this imperative; however, suitable approaches for effectively integrating corresponding criteria into risk assessment and compliance processes are still lacking. This article presents the methodological approach and key findings from two multi-stakeholder dialogues, which identify starting points for the human-centered development of AI-assisted healthcare technologies.
References
AI HLEG – High-level Expert Group on AI (2019): Ethics guidelines for trustworthy AI. Brussels: European Commission. Available online at https://ec.europa.eu/newsroom/dae/document.cfm?doc_id=60419, last accessed on 25.09.2025.
BAuA – Bundesanstalt für Arbeitsschutz und Arbeitsmedizin (n.d.): KI-basierte Systeme im Gesundheitswesen. Werkstattgespräche zur Entwicklung eines multidisziplinären und gemeinwohlorientierten Gestaltungsansatzes aus Perspektive des Arbeitsschutzes. Available online at https://baua.de/DE/Forschung/Forschungsprojekte/f2574, last accessed on 25.09.2025.
Beauchamp, Tom; Childress, James (2019): Principles of biomedical ethics. Oxford: Oxford University Press.
Corrêa, Nicholas et al. (2023): Worldwide AI ethics. A review of 200 guidelines and recommendations for AI governance. In: Patterns 4 (10), p. 100857. https://doi.org/10.1016/j.patter.2023.100857 DOI: https://doi.org/10.1016/j.patter.2023.100857
EU – European Union (2024): Regulation (EU) 2024/1689 of the European parliament and of the council of 13 June 2024 laying down harmonised rules on artificial intelligence and amending regulations (EC) No 300/2008, (EU) No 167/2013, (EU) No 168/2013, (EU) 2018/858, (EU) 2018/1139 and (EU) 2019/2144 and directives 2014/90/EU, (EU) 2016/797 and (EU) 2020/1828 (artificial intelligence act). In: Official Journal of the European Union 2024/1689. Available online at https://eur-lex.europa.eu/eli/reg/2024/1689, last accessed on 25.09.2025.
Gilbert, Stephen; Adler, Rasmus; Holoyad, Taras; Weicken, Eva (2025): Could transparent model cards with layered accessible information drive trust and safety in health AI? In: npj Digital Medicine 8 (1), p. 124. https://doi.org/10.1038/s41746-025-01482-9 DOI: https://doi.org/10.1038/s41746-025-01482-9
Grobe, Antje (2021): Partizipative TA in Transformationsprozessen. Analoge und digitale Ansätze inklusiver, prospektiver Verfahrungen der Beteiligung. In: Stefan Böschen, Armin Grunwald, Bettina-Johanna Krings and Christine Rösch (eds.): Technikfolgenabschätzung. Handbuch für Wissenschaft und Praxis. Baden-Baden: Nomos, pp. 352–373. https://doi.org/10.5771/9783748901990-352 DOI: https://doi.org/10.5771/9783748901990-352
Grunwald, Armin (2018): Technology assessment in practice and theory. New York, NY: Routledge. https://doi.org/10.4324/9780429442643 DOI: https://doi.org/10.4324/9780429442643
Mittelstadt, Brent (2019): Principles alone cannot guarantee ethical AI. In: Nature Machine Intelligence 1 (11), pp. 501–507. https://doi.org/10.1038/s42256-019-0114-4 DOI: https://doi.org/10.1038/s42256-019-0114-4
Moritz, Michael; Topol, Eeric; Rajpurkar, Pranav (2025). Coordinated AI agents for advancing healthcare. In: Nature Biomedical Engineering 9, pp. 432–438. https://doi.org/10.1038/s41551-025-01363-2 DOI: https://doi.org/10.1038/s41551-025-01363-2
OECD – Organisation for Economic Co-operation and Development (2019): Artificial intelligence in society. Paris: OECD Publishing. https://doi.org/10.1787/eedfee77-en DOI: https://doi.org/10.1787/eedfee77-en
Ortega-Bolaños, Ricardo; Bernal-Salcedo, Joshua; Germán Ortiz, Mariana; Galeano, Julian; Ruz, Gonzalo; Tabares-Soto, Reinel (2024): Applying the ethics of AI. A systematic review of tools for developing and assessing AI-based systems. In: Artificial Intelligence Review 57 (5), p. 110. https://doi.org/10.1007/s10462-024-10740-3 DOI: https://doi.org/10.1007/s10462-024-10740-3
Poszler, Franziska; Portmann, Edy; Lütge, Christoph (2024): Formalizing ethical principles within AI systems. Experts’ opinions on why (not) and how to do it. In: AI & Ethics 5 (2), pp. 937–965. https://doi.org/10.1007/s43681-024-00425-6 DOI: https://doi.org/10.1007/s43681-024-00425-6
Prem, Erich (2023). From ethical AI frameworks to tools. A review of approaches. In: AI & Ethics 3 (3), pp. 699–716. https://doi.org/10.1007/s43681-023-00258-9 DOI: https://doi.org/10.1007/s43681-023-00258-9
Sanderson, Conrad et al. (2023): AI ethics principles in practice. Perspectives of designers and developers. In: IEEE Transactions on Technology and Society 4 (2), pp. 171–187. https://doi.org/10.1109/TTS.2023.3257303 DOI: https://doi.org/10.1109/TTS.2023.3257303
Schmager, Stefan; Pappas, Ilias; Vassilakopoulou, Polyxeni (2025): Understanding human-centred AI. A review of its defining elements and a research agenda. In: Behaviour & Information Technology 44 (15), pp. 3771–3810. https://doi.org/10.1080/0144929X.2024.2448719 DOI: https://doi.org/10.1080/0144929X.2024.2448719
Schönfelder, Anett et al. (2025): Collaborative and cooperative hospital digital transformation in the AI age. A framework compatible with European values. In: JMIR Preprints. https://doi.org/10.2196/preprints.80754 DOI: https://doi.org/10.2196/preprints.80754
Sharma, Malvika; Savage, Carl; Nair, Monika; Larsson, Ingrid; Svedberg, Petra; Nygren, Jens (2022): Artificial intelligence applications in health care practice. Scoping review. In: Journal of Medical Internet Research 24 (10), p. 40238. https://doi.org/10.2196/40238 DOI: https://doi.org/10.2196/40238
Siedel, Georg; Voß, Stefan; Vock, Silvia (2021): An overview of the research landscape in the field of safe machine learning. In: Proceedings of the ASME 2021 International Mechanical Engineering Congress and Exposition. Volume 13: Safety Engineering, Risk, and Reliability Analysis. New York, NY: The American Society of Mechanical Engineers, p. V013T14A045. https://doi.org/10.1115/IMECE2021-69390 DOI: https://doi.org/10.1115/IMECE2021-69390
Tidjon, Lionel; Khomh, Foutse (2022): The different faces of ai ethics across the world. A principle-implementation gap analysis. In: arXiv. https://doi.org/10.48550/arXiv.2206.03225
Ulich, Eberhard (2011): Arbeitspsychologie. Stuttgart: Schäffer-Poeschel.
Vakkuri, Ville; Kemell, Kai-Kristian; Kultanen, Joni; Abrahamsson, Pekka (2020): The current state of industrial practice in artificial intelligence ethics. In: IEEE Software 37 (4), pp. 50–57. https://doi.org/10.1109/MS.2020.2985621 DOI: https://doi.org/10.1109/MS.2020.2985621
Weber, Karsten (2015): MEESTAR. Ein Modell zur ethischen Evaluierung sozio-technischer Arrangements in der Pflege- und Gesundheitsversorgung. In: Karsten Weber, Debora Frommeld, Arne Manzeschke and Heiner Fangerau (eds.): Technisierung des Alltags. Beitrag für ein gutes Leben? Stuttgart: Steiner, pp. 247–262. DOI: https://doi.org/10.25162/9783515110099
WHO – World Health Organization (2023): Regulatory considerations on artificial intelligence for health. Geneva: World Health Organization.
Yakusheva, Olga; Bouvier, Monique; Hagopian, Chelsea (2025): How artificial intelligence is altering the nursing workforce. In: Nursing Outlook 73 (1), p. 102300. https://doi.org/10.1016/j.outlook.2024.102300 DOI: https://doi.org/10.1016/j.outlook.2024.102300
Yelne, Seema; Chaudhary, Minakshi; Dod, Karishma; Sayyad, Akhtaribano; Sharma, Ranjana (2023): Harnessing the power of AI. A comprehensive review of its impact and challenges in nursing science and healthcare. In: Cureus 15 (11), p. e49252. https://doi.org/10.7759/cureus.49252 DOI: https://doi.org/10.7759/cureus.49252
Published
Issue
Section
License
Copyright (c) 2025 Larissa Schlicht
This work is licensed under a Creative Commons Attribution 4.0 International License.
How to Cite
