Controversies in artificial intelligence
T. Y. Alvin Liu, Neil M. Bressler
Abstract
PURPOSE OF REVIEW: To review four recent controversial topics arising from deep learning applications in ophthalmology. RECENT FINDINGS: The controversies of four recent topics surrounding deep learning applications in ophthalmology are discussed, including the following: lack of explainability, limited generalizability, potential biases and protection of patient confidentiality in large-scale data transfer. SUMMARY: These controversial issues spanning the domains of clinical medicine, public health, computer science, ethics and legal issues, are complex and likely will benefit from an interdisciplinary approach if artificial intelligence in ophthalmology is to succeed over the next decade.
Topics & Concepts
Generalizability theoryConfidentialityPatient confidentialityDeep learningEthical issuesPsychologyEngineering ethicsArtificial intelligenceData scienceComputer scienceEngineeringComputer securityDevelopmental psychologyRetinal Imaging and AnalysisRetinal and Optic ConditionsArtificial Intelligence in Healthcare and Education