The ethical challenges of diversifying genomic data: A qualitative evidence synthesis.

This article aims to explore the ethical issues arising from attempts to diversify genomic data and include individuals from underserved groups in studies exploring the relationship between genomics and health. We employed a qualitative synthesis design, combining data from three sources: 1) a rapid review of empirical articles published between 2000 and 2022 with a primary or secondary focus on diversifying genomic data, or the inclusion of underserved groups and ethical issues arising from this, 2) an expert workshop and 3) a narrative review. Using these three sources we found that ethical issues are interconnected across structural factors and research practices.

Ethical and legal implications of implementing risk algorithms for early detection and screening for oesophageal cancer, now and in the future.

Background: Oesophageal cancer has significant morbidity and mortality but late diagnosis is common since early signs of disease are frequently misinterpreted. Project DELTA aims to enable earlier detection and treatment through targeted screening using a novel risk prediction algorithm for oesophageal cancer (incorporating risk factors of Barrett's oesophagus including prescriptions for acid-reducing medications (CanPredict)), together with a non-invasive, low-cost sampling device (CytospongeTM). However, there are many barriers to implementation, and this paper identifies key ethical and legal challenges to implementing these personalised prevention strategies for Barrett's oesophagus/oesophageal cancer.

Ethical and legal considerations influencing human involvement in the implementation of artificial intelligence in a clinical pathway: A multi-stakeholder perspective.

Introduction: Ethical and legal factors will have an important bearing on when and whether automation is appropriate in healthcare. There is a developing literature on the ethics of artificial intelligence (AI) in health, including specific legal or regulatory questions such as whether there is a right to an explanation of AI decision-making. However, there has been limited consideration of the specific ethical and legal factors that influence when, and in what form, human involvement may be required in the implementation of AI in a clinical pathway, and the views of the wide range of stakeholders involved.