Finding Consensus on Trust in AI in Health Care: Recommendations From a Panel of International Experts.

Background: The integration of artificial intelligence (AI) into health care has become a crucial element in the digital transformation of health systems worldwide. Despite the potential benefits across diverse medical domains, a significant barrier to the successful adoption of AI systems in health care applications remains the prevailing low user trust in these technologies. Crucially, this challenge is exacerbated by the lack of consensus among experts from different disciplines on the definition of trust in AI within the health care sector.

Digital technologies in genetic counseling: Recommendations for a morally sound integration.

To address the increasing demand for clinical genetic counseling, digital technologies are currently being developed to increase efficiency and overcome logistical and societal barriers in genetic health care. However, it is not self-evident that genetic technologies will improve the quality of and access to genetic counseling. Moreover, several ethical questions about the appropriate tasks of digital technologies in the genetic care process have been raised, particularly when personal contact is supplemented or even replaced with digital technologies.

Physicians' required competencies in AI-assisted clinical settings: a systematic review.

Background: Utilizing Artificial Intelligence (AI) in clinical settings may offer significant benefits. A roadblock to the responsible implementation of medical AI is the remaining uncertainty regarding requirements for AI users at the bedside. An overview of the academic literature on human requirements for the adequate use of AI in clinical settings is therefore of significant value.

From responsibility to responsibilization in stem cell research: An ethical framework.

Adopting a responsibilization approach can further improve the ethical conduct of stem cell (SC) research and applications. This approach helps align new and existing solutions for ethical implications by focusing on equipping SC researchers with the knowledge, skills, and organizational arrangements to take (co-)responsibility for the socio-ethical implications of their research.