Artificial Intelligence in Basic and Clinical Neuroscience: Opportunities and Ethical Challenges

Abstract

Abstract The analysis of large amounts of personal data with artificial neural networks for deep learning is the driving technology behind new artificial intelligence (AI) systems for all areas in science and technology. These AI methods have evolved from applications in computer vision, the automated analysis of images, and now include frameworks and methods for analyzing multimodal datasets that combine data from many different source, including biomedical devices, smartphones and common user behavior in cyberspace. For neuroscience, these widening streams of personal data and machine learning methods provide many opportunities for basic data-driven research as well as for developing new tools for diagnostic, predictive and therapeutic applications for disorders of the nervous system. The increasing automation and autonomy of AI systems, however, also creates substantial ethical challenges for basic research and medical applications. Here, scientific and medical opportunities as well ethical challenges are summarized and discussed.