Ethical Challenges of New Technologies and Insights from Research Ethics Experts on Oversight of AI in Health, Extended Reality, Gene Editing and Biobanking

Abstract Research on emerging technologies such as AI-driven health interventions, extended reality (XR) systems, biobanks, and genome editing poses novel ethical challenges that traditional ethics governance models struggle to address. This article explores various models of research ethics governance within the European Union (EU) context, starting from traditional one-time research ethics committee (REC) reviews, REC review with post-approval monitoring, as well as alternative models such as ethics self-assessment, and ethics-by-design approaches. Based on literature analysis and a survey of European research ethics experts, the study identifies prevalent models of research ethics oversight, research ethics expert perceptions of their sufficiency, and challenges such as insufficient technical and ethics expertise, lack of specific guidelines, and unclear boundaries of REC responsibilities. Findings also indicate that traditional REC reviews remain dominant but have limitations in effectively managing rapidly evolving technologies. Research ethics experts highlighted the feasibility of continuous oversight mechanisms to better integrate ethical reflection throughout the research lifecycle. The article concludes by recommending a shift towards proportional, risk-based oversight, development of clearer, technology-specific guidelines, enhanced REC training, and improved harmonization across EU ethics governance systems to address current gaps.

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Publication Details

Journal
NanoEthics
Published
2026-01-21
DOI
https://doi.org/10.1007/s11569-025-00491-y
Citations
1
Primary Topic
Artificial Intelligence in Healthcare and Education
Type
article
Field-Weighted Citation Impact
17.70
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article

Ethical Challenges of New Technologies and Insights from Research Ethics Experts on Oversight of AI in Health, Extended Reality, Gene Editing and Biobanking

Miltos Ladikas, Vygintas Aliukonis, Daniela Proske, Jūratė Lekstutienė et al.
1 citations
NanoEthics
Artificial Intelligence in Healthcare and Education
17.70
article

Ethical Challenges of New Technologies and Insights from Research Ethics Experts on Oversight of AI in Health, Extended Reality, Gene Editing and Biobanking

Miltos Ladikas, Vygintas Aliukonis, Daniela Proske, Jūratė Lekstutienė, Vilma Lukaševičienė, Eugenijus Gefenas, David Shaw
article en
1 citations

Abstract

Abstract Research on emerging technologies such as AI-driven health interventions, extended reality (XR) systems, biobanks, and genome editing poses novel ethical challenges that traditional ethics governance models struggle to address. This article explores various models of research ethics governance within the European Union (EU) context, starting from traditional one-time research ethics committee (REC) reviews, REC review with post-approval monitoring, as well as alternative models such as ethics self-assessment, and ethics-by-design approaches. Based on literature analysis and a survey of European research ethics experts, the study identifies prevalent models of research ethics oversight, research ethics expert perceptions of their sufficiency, and challenges such as insufficient technical and ethics expertise, lack of specific guidelines, and unclear boundaries of REC responsibilities. Findings also indicate that traditional REC reviews remain dominant but have limitations in effectively managing rapidly evolving technologies. Research ethics experts highlighted the feasibility of continuous oversight mechanisms to better integrate ethical reflection throughout the research lifecycle. The article concludes by recommending a shift towards proportional, risk-based oversight, development of clearer, technology-specific guidelines, enhanced REC training, and improved harmonization across EU ethics governance systems to address current gaps.

NanoEthicsVol. 20(1)
Karlsruhe Institute of Technology (DE), University of Bonn (DE), Vilnius University (LT), University of Basel (CH), Maastricht University (NL), Vilnius University of Applied Sciences (LT)
Partnerships for the goals
Openalex Percentile: Top 2%
Artificial Intelligence in Healthcare and Education
17.70
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