The Wonderful Intersection of AI and Brain Science to Light the Future of Consciousness Together

Like a vine clinging to a scaffold, the relationship between AI and brain science is propelling both fields to new heights.We look at the interactions between AI and brain science to see how they are getting closer and converging in certain areas.

AI and human cognition present a stark contrast and fit with each other. One is defined by logic while the other is inherently irrational, but both are susceptible to the same weaknesses: bias, paranoia, falsehoods, etc. They complement each other and work together to overcome their respective shortcomings.

In a delicate convergence of carbon-based and silicon-based intelligence, neuroscientists are using AI to deepen their understanding of the human mind and cognition, while computer scientists are drawing on the human brain to create applications based on "neuromorphic computing," such as machine learning, convolutional neural networks, deep and reinforcement learning, and brain-computer interfaces.

As a result, a diverse group of careers have sprung up in fields where AI meets brain science. Computer scientists design systems inspired by the brain's neural networks, such as cognitive computing and deep learning. Cognitive scientists unravel the mysteries of human cognition, fueling simulation in AI. Neuroengineers enable technology to interact with the nervous system through brain-computer interfaces. Ethicists focus on the responsible use of AI in brain science, such as privacy consent. Philosophers think about the impact of AI on the understanding of consciousness and explore the ethics of creating intelligent machines. Developers generate AI technologies modeled on brain structures.

AI simulations reveal human brain function and lead neuroscientists to explore brain dynamics. Neuroscience serves as a model for AI development, and AI advances cast light on this symbiotic relationship between human systems and smarter, more capable AI, a trend with seemingly no end in sight.

Meanwhile, there are numerous applications of AI in brain science. Data analysis and pattern recognition of large amounts of data such as functional magnetic resonance imaging, electroencephalography or magnetoencephalography are analyzed through machine learning. Neuroimaging analysis improves the interpretation of brain images with the help of AI.Predictive modeling uses machine learning to establish relationships between the brain and behavior. Brain-computer interfaces enable communication between the brain and external devices, among other things.