Ethical layering in AI-driven polygenic risk scores—New complexities, new challenges

• DOI: 10.3389/fgene.2023.1098439
• Publication Date: 2023-01-26T06:14:41Z
• Authors: Marie-Christine F...; Kaya Akyüz; Mónica Cano Abadía; Stuart McLennan; Pekka Marttinen; Michaela Th. Mayr...; Alena M. Buyx
• Keywords: Polygenic risk score

Researchers aim to develop polygenic risk scores as a tool prevent and more effectively treat serious diseases, disorders conditions such breast cancer, type 2 diabetes mellitus coronary heart disease. Recently, machine learning techniques, in particular deep neural networks, have been increasingly developed create using electronic health records well genomic other data. While the use of artificial intelligence for may enable greater accuracy, performance prediction, it also presents range complex ethical challenges. The social issues many score applications medicine widely discussed. However, literature practice, implications their confluence with not yet sufficiently considered. Based on comprehensive review existing literature, we argue that this stands need urgent consideration research subsequent translation into clinical setting. Considering layers involved, will first give brief overview development intelligence-driven scores, associated implications, challenges ethics, finally, explore potential complexities driven by intelligence. We point out emerging complexity regarding fairness, building trust, explaining understanding regulatory uncertainties further strongly advocate taking proactive approach embedding ethics implementation processes