Author: Neil Savage
Publisher: Nature
Publication Year: 2019
Summary: The following article explores how artificial intelligence (AI) and neuroscience enhance each other. AI, with its ability to identify patterns in large, complex datasets, has seen remarkable successes in the past decade, in part by emulating how the brain performs certain computations. Cognitive science is beginning to benefit from the power of AI, both as a model for developing and testing ideas about how the brain performs computations and as a tool for processing the complex data sets that researchers are producing. Neuroscientists are still a long way from understanding how the brain goes about a task such as distinguishing jazz from rock music, but machine learning does give them a way of constructing models with which to explore such questions. If researchers can design systems that perform similarly to the brain, their design can inform ideas about how the brain solves such tasks. That’s important because scientists often don’t have a working hypothesis for how the brain operates. Making a machine perform a particular task will give them at least one possible explanation for how the brain achieves the same thing. Ethics concerns are already rising and will become more potent as these systems are developed. Toying with the human brain via AI is a dangerous game, and regulation will be needed to ensure no harm is done.