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How Meta-research Can Pave the Road Towards Trustworthy AI In Healthcare: Catalogue of Ideas and Roadmap for Future Research: Report for the Volkswagen Stiftung - University of Copenhagen Research Portal How Meta-research Can Pave the Road Towards Trustworthy AI In Healthcare: Catalogue of Ideas and Roadmap for Future Research: Report for the Volkswagen Stiftung Valerie Bürger * , Marlie Besouw, Jana Fehr, Riana Minocher, Emma Morhead, Isabel Velarde, Louis Agha-Mir-Salim, Julia Amann, Alexandra Bannach-Brown, David B.
Blumenthal, Kaitlyn Hair, Bert Heinrichs, Moritz Herrmann, Elizabeth Hofvenschiöld, Sune Hannibal Holm , Anne A. H. de Hond, Sara Kijewski, Stuart McLennan, Timo Minssen , Marco S.
Nobile Nico Pfeifer, Jessica L. Rohmann, Tony Ross-Hellauer, Marija Slavkovik, Karin Tafur, Eleonora Viganò, Magnus Westerlund, Tracey L. Weissgerber, Vince I.
Madai Show 9 more Show less * Corresponding author for this work Center for Advanced Studies in Bioscience Innovation Law Section for Consumption, Bioethics and Governance Research output : Book/Report › Report › Research Meta-research and Trustworthy AI (TAI) share common goals, namely improving evidence, robustness, and transparency, yet there is very little interplay between the two fields.
To investigate the potential benefits of closer collaboration between the domains of TAI in healthcare and meta-research, we convened an interdisciplinary workshop funded by the Volkswagen Foundation in February 2025. The workshop aimed to collaboratively examine key tensions in translating AI ethics principles into practice and to identify potential solutions informed by meta-research approaches.
A Design Thinking-informed co-creation approach was followed by an inductive descriptive analysis of the outputs. Our results demonstrate how meta-research can offer concrete contributions to address pressing challenges of TAI in healthcare.
These challenges include achieving robustness, reproducibility, and replicability; late-stage development and the integration of AI into clinical practice; the selection of appropriate evaluation metrics; specific AI-related challenges in preclinical and biomedical research; gaps of transparency in medical AI, as well as the need for improved conceptual clarity and AI literacy among stakeholders.
Finally, we offer a catalog of ideas and roadmap for future research to inform scholars in both fields on existing interconnections and serve as a foundation for guiding future interdisciplinary efforts. Original language English Publisher arXiv.
org Number of pages 24 Commissioning body Volkswagen Stiftung Publication status Published - 2026 Event VW Stiftung Scoping Workshop: From Principles to Practice: Innovating Trustworthy AI through meta-research Date: 19th – 21st of February 2025 Objective: To collaboratively address key tensions in operationalizing AI ethics (e.g., robustness vs. transparency), foster cross-disciplinary collaboration, and produce actionable outcomes, including a position paper.
- Conference Centre Herrenhausen Palace, Hannover, Hannover, Germany Duration: 19 Feb 2025 → 21 Feb 2025 https://www. volkswagenstiftung.
de/en/funding/funding-offer/scoping-workshops/volkswagen-foundation-workshop-weeks Workshop VW Stiftung Scoping Workshop: From Principles to Practice: Innovating Trustworthy AI through meta-research Date: 19th – 21st of February 2025 Objective: To collaboratively address key tensions in operationalizing AI ethics (e.g., robustness vs. transparency), foster cross-disciplinary collaboration, and produce actionable outcomes, including a position paper.
Location Conference Centre Herrenhausen Palace, Hannover Country/Territory Germany City Hannover Period 19/02/2025 → 21/02/2025 Internet address https://www. volkswagenstiftung. de/en/funding/funding-offer/scoping-workshops/volkswagen-foundation-workshop-weeks Detailed report summarizing the outcomes of a 2025 meeting in Hannover organized by the Charite Berlin with support of the Volkswagen Stiftung.
Authors: Valerie Bürger, Marlie Besouw, Jana Fehr, Riana Minocher, Emma Moorhead, Isabel Velarde, Louis Agha-Mir-Salim, Julia Amann, Alexandra Bannach-Brown, David B. Blumenthal6, Kaitlyn Hair, Bert Heinrichs, Moritz Herrmann, Elizabeth Hofvenschiöld, Sune Holm, Anne A. H.
de Hond, Sara Kijewski, Stuart McLennan, Timo Minssen, Marco S. Nobile, Nico Pfeifer, Jessica L. Rohmann, Tony Ross-Hellauer, Marija Slavkovik, Karin Tafur, Eleonora Viganò, Magnus Westerlund, Tracey Weissgerber & Vince I.
Madai https://arxiv. org/pdf/2603. 13286 Licence: Unspecified Check availability at the Royal Danish Library Bürger, V.
, Besouw, M. , Fehr, J. , Minocher, R.
, Morhead, E. , Velarde, I. , Agha-Mir-Salim, L.
, Amann, J. , Bannach-Brown, A. , Blumenthal, D.
B. , Hair, K. , Heinrichs, B.
, Herrmann, M. , Hofvenschiöld, E. , Holm, S.
H. , de Hond, A. A.
H. , Kijewski, S. , McLennan, S.
, Minssen, T. , ... Madai, V.
I. (2026). How Meta-research Can Pave the Road Towards Trustworthy AI In Healthcare: Catalogue of Ideas and Roadmap for Future Research: Report for the Volkswagen Stiftung .
arXiv. org. https://arxiv.
org/pdf/2603. 13286 How Meta-research Can Pave the Road Towards Trustworthy AI In Healthcare: Catalogue of Ideas and Roadmap for Future Research: Report for the Volkswagen Stiftung. / Bürger, Valerie ; Besouw, Marlie; Fehr, Jana et al.
arXiv. org, 2026. 24 p.
Research output : Book/Report › Report › Research Bürger, V, Besouw, M, Fehr, J, Minocher, R, Morhead, E, Velarde, I, Agha-Mir-Salim, L, Amann, J, Bannach-Brown, A, Blumenthal, DB, Hair, K, Heinrichs, B, Herrmann, M, Hofvenschiöld, E , Holm, SH , de Hond, AAH, Kijewski, S, McLennan, S , Minssen, T , Nobile, MS, Pfeifer, N, Rohmann, JL, Ross-Hellauer, T, Slavkovik, M, Tafur, K, Viganò, E, Westerlund, M, Weissgerber, TL & Madai, VI 2026, How Meta-research Can Pave the Road Towards Trustworthy AI In Healthcare: Catalogue of Ideas and Roadmap for Future Research: Report for the Volkswagen Stiftung .
arXiv. org. < https://arxiv.
org/pdf/2603. 13286 > Bürger V, Besouw M, Fehr J, Minocher R, Morhead E, Velarde I et al. How Meta-research Can Pave the Road Towards Trustworthy AI In Healthcare: Catalogue of Ideas and Roadmap for Future Research: Report for the Volkswagen Stiftung .
arXiv. org, 2026. 24 p.
Bürger, Valerie ; Besouw, Marlie ; Fehr, Jana et al. / How Meta-research Can Pave the Road Towards Trustworthy AI In Healthcare: Catalogue of Ideas and Roadmap for Future Research : Report for the Volkswagen Stiftung . arXiv.
org, 2026. 24 p. @book{bd0c855584e24f7aada459152b4a8f3d, title = "How Meta-research Can Pave the Road Towards Trustworthy AI In Healthcare: Catalogue of Ideas and Roadmap for Future Research: Report for the Volkswagen Stiftung", abstract = "Meta-research and Trustworthy AI (TAI) share common goals, namely improving evidence, robustness, and transparency, yet there is very little interplay between the two fields.
To investigate the potential benefits of closer collaboration between the domains of TAI in healthcare and meta-research, we convened an interdisciplinary workshop funded by the Volkswagen Foundation in February 2025. The workshop aimed to collaboratively examine key tensions in translating AI ethics principles into practice and to identify potential solutions informed by meta-research approaches.
A Design Thinking-informed co-creation approach was followed by an inductive descriptive analysis of the outputs. Our results demonstrate how meta-research can offer concrete contributions to address pressing challenges of TAI in healthcare.
These challenges include achieving robustness, reproducibility, and replicability; late-stage development and the integration of AI into clinical practice; the selection of appropriate evaluation metrics; specific AI-related challenges in preclinical and biomedical research; gaps of transparency in medical AI, as well as the need for improved conceptual clarity and AI literacy among stakeholders.
Finally, we offer a catalog of ideas and roadmap for future research to inform scholars in both fields on existing interconnections and serve as a foundation for guiding future interdisciplinary efforts.
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Authors: Valerie B{\"u}rger, Marlie Besouw, Jana Fehr, Riana Minocher, Emma Moorhead, Isabel Velarde, Louis Agha-Mir-Salim, Julia Amann, Alexandra Bannach-Brown, David B. Blumenthal6, Kaitlyn Hair, Bert Heinrichs, Moritz Herrmann, Elizabeth Hofvenschi{\"o}ld, Sune Holm, Anne A. H.
de Hond, Sara Kijewski, Stuart McLennan, Timo Minssen, Marco S. Nobile, Nico Pfeifer, Jessica L. Rohmann, Tony Ross-Hellauer, Marija Slavkovik, Karin Tafur, Eleonora Vigan{\`o}, Magnus Westerlund, Tracey Weissgerber & Vince I.
Madai; VW Stiftung Scoping Workshop: From Principles to Practice: Innovating Trustworthy AI through meta-research Date: 19th – 21st of February 2025<br/>Place: Hanover, Germany<br/>Objective: To collaboratively address key tensions in operationalizing AI ethics (e.g., robustness vs. transparency), foster cross-disciplinary collaboration, and produce actionable outcomes, including a position paper.
; Conference date: 19-02-2025 Through 21-02-2025", url = "https://www. volkswagenstiftung.
de/en/funding/funding-offer/scoping-workshops/volkswagen-foundation-workshop-weeks", T1 - How Meta-research Can Pave the Road Towards Trustworthy AI In Healthcare: Catalogue of Ideas and Roadmap for Future Research T2 - VW Stiftung Scoping Workshop: From Principles to Practice: Innovating Trustworthy AI through meta-research Date: 19th – 21st of February 2025<br/>Place: Hanover, Germany<br/>Objective: To collaboratively address key tensions in operationalizing AI ethics (e.g., robustness vs. transparency), foster cross-disciplinary collaboration, and produce actionable outcomes, including a position paper.
AU - Agha-Mir-Salim, Louis AU - Bannach-Brown, Alexandra AU - Blumenthal, David B. AU - Hofvenschiöld, Elizabeth AU - Weissgerber, Tracey L. N1 - Detailed report summarizing the outcomes of a 2025 meeting in Hannover organized by the Charite Berlin with support of the Volkswagen Stiftung.
Authors: Valerie Bürger, Marlie Besouw, Jana Fehr, Riana Minocher, Emma Moorhead, Isabel Velarde, Louis Agha-Mir-Salim, Julia Amann, Alexandra Bannach-Brown, David B. Blumenthal6, Kaitlyn Hair, Bert Heinrichs, Moritz Herrmann, Elizabeth Hofvenschiöld, Sune Holm, Anne A. H.
de Hond, Sara Kijewski, Stuart McLennan, Timo Minssen, Marco S. Nobile, Nico Pfeifer, Jessica L. Rohmann, Tony Ross-Hellauer, Marija Slavkovik, Karin Tafur, Eleonora Viganò, Magnus Westerlund, Tracey Weissgerber & Vince I.
Madai N2 - Meta-research and Trustworthy AI (TAI) share common goals, namely improving evidence, robustness, and transparency, yet there is very little interplay between the two fields. To investigate the potential benefits of closer collaboration between the domains of TAI in healthcare and meta-research, we convened an interdisciplinary workshop funded by the Volkswagen Foundation in February 2025.
The workshop aimed to collaboratively examine key tensions in translating AI ethics principles into practice and to identify potential solutions informed by meta-research approaches. A Design Thinking-informed co-creation approach was followed by an inductive descriptive analysis of the outputs. Our results demonstrate how meta-research can offer concrete contributions to address pressing challenges of TAI in healthcare.
These challenges include achieving robustness, reproducibility, and replicability; late-stage development and the integration of AI into clinical practice; the selection of appropriate evaluation metrics; specific AI-related challenges in preclinical and biomedical research; gaps of transparency in medical AI, as well as the need for improved conceptual clarity and AI literacy among stakeholders.
Finally, we offer a catalog of ideas and roadmap for future research to inform scholars in both fields on existing interconnections and serve as a foundation for guiding future interdisciplinary efforts. AB - Meta-research and Trustworthy AI (TAI) share common goals, namely improving evidence, robustness, and transparency, yet there is very little interplay between the two fields.
To investigate the potential benefits of closer collaboration between the domains of TAI in healthcare and meta-research, we convened an interdisciplinary workshop funded by the Volkswagen Foundation in February 2025. The workshop aimed to collaboratively examine key tensions in translating AI ethics principles into practice and to identify potential solutions informed by meta-research approaches.
A Design Thinking-informed co-creation approach was followed by an inductive descriptive analysis of the outputs. Our results demonstrate how meta-research can offer concrete contributions to address pressing challenges of TAI in healthcare.
These challenges include achieving robustness, reproducibility, and replicability; late-stage development and the integration of AI into clinical practice; the selection of appropriate evaluation metrics; specific AI-related challenges in preclinical and biomedical research; gaps of transparency in medical AI, as well as the need for improved conceptual clarity and AI literacy among stakeholders.
Finally, we offer a catalog of ideas and roadmap for future research to inform scholars in both fields on existing interconnections and serve as a foundation for guiding future interdisciplinary efforts. BT - How Meta-research Can Pave the Road Towards Trustworthy AI In Healthcare: Catalogue of Ideas and Roadmap for Future Research Y2 - 19 February 2025 through 21 February 2025
According to the current listing, eligibility includes: Academic and research institutions, particularly those fostering interdisciplinary collaboration between AI and meta-research, are eligible. The workshop brought together experts from both fields. Confirm the full requirements in the official notice before applying.
From Principles to Practice: Innovating Trustworthy AI through Meta-research is funded by Volkswagen Foundation. Verify program details on the funder's official page before applying.
Start from the official opportunity page linked in this listing — it carries the sponsor's submission instructions.
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