Aug 2026· AI and Ethics· Vol 6· 0 citations· 73 references
TL;DR
A notable disparity between the claimed behaviours and the observed improvements is revealed, as well as in the formalisation of governance for AI ethics, in Swiss health organisations.
Abstract
Despite the rise in the development and use of Artificial Intelligence (AI), the application of ethics to this new technology remains relatively nascent. This study investigates the implementation of AI ethics within health companies in Switzerland, their challenges and facilitating factors. A cross-sectional survey, with a 15% response rate (N = 28), was employed, targeting professionals in the private sector. The findings revealed a notable disparity between the claimed behaviours and the observed improvements, as well as in the formalisation of governance for AI ethics. The results find different practices between startups, small- and medium-sized enterprises (SMEs), and large multinational corporations (MNCs). Challenges were identified in the lack of standards, implementation guides, and ethical knowledge. The discussion addresses systemic issues, including governance and lack of ethical knowledge, as well as organisational factors such as company size and role. The paper concludes with institutional and organisational recommendations to develop clear regulatory standards, adopt proactive measures, and provide comprehensive AI ethics training and resources to support the ethical implementation of AI in Swiss health organisations.
The evidence shows strong convergence around fairness, transparency, privacy, accountability, human oversight, safety and inclusiveness, but weaker agreement on implementation, and an integrated framework for developing, deploying and monitoring AI systems in ways that are lawful, transparent, accountable, inclusive an...
Sunday Olusola Ladipo, Ifaka Queen Inazu· Direct Research Journal of E...· 0 citations
Three steps of the ENACT methodology are described and details three steps of the ENACT methodology and its potential and limitations for qualitative ethical risk assessment of AI in organisational settings are discussed.
N. Murashova, Leonora Onarheim Bergsjø, Heidi Dahl et al.· Nordic Machine Intelligence· 0 citations
Abstract Objective Artificial intelligence (AI) technologies are being rapidly adopted in healthcare, yet organisational governance often lacks the processes needed to oversee their safe and responsible use. Previous AI governance frameworks largely focus on high-level AI ethics principles, leaving healthcare organisat...
S. Freeman, Amy Wang, Sudeep Saraf et al.· BMJ digital health & AI· 0 citations
The study suggests that privacy-by-design practices, clearer accountability procedures, and visible ethical governance may support more trustworthy implementation of AI-enabled medical record systems in Oman.
Abderrazak Mkadmi, F. Hamad, Naifa Bait Bin Saleem· Discover Artificial Intellig...· 0 citations
The findings indicate that AI integration in research ethics oversight is shaped not only by technological feasibility but by institutional concerns regarding responsibility, legitimacy, and deliberative authority.
Daniel Wang, Marta Guix Arnau, Cristina Llop Julià et al.· Research Ethics· 0 citations
AI continues to be adopted in various sectors, one of which is healthcare. AI adoption in healthcare needs to be a key focus to prevent risks related to human life. However, the implementation of AI in healthcare can pose ethical and governance challenges related to transparency, accountability, fairness, privacy, trus...
Erin Erin, S. Isa, N. A. C. Andryani et al.· International Conferences on...· 0 citations
We use cookies to run the site and, with your consent, for analytics and to show ads.
See our Cookie Policy.