Author: Sara Gerke, Timo Minssen, and Glenn Cohen
Publisher: National Library of Medicine
Publication Year: 2020
Summary: The following article is dense, but its biggest takeaway is the impact of getting things wrong is extremely high in the healthcare sector. If an algorithm recommends an incorrect or unsafe oncology treatment, it could cost a patient their lives. The practical example of this is simply having bad training data, but it can also take a bias skew. When phenotype and genotype information are involved, biased artificial intelligence could, “lead to false diagnoses and render treatments ineffective for some subpopulations and thus jeopardize their safety.”
