AI Unlikely to Gain human-like Cognition, unless Connected to real World through Robots

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AI Unlikely to gain human-like cognition, unless connected to real world through robots, says study

by University of Sheffield

Credit: Pixabay/CC0 Public Domain

Connecting artificial intelligence systems to the real world through robots and designing them using principles from evolution is the most likely way AI will gain human-like cognition, according to research from the University of Sheffield.

In a paper published in Science Robotics, Professor Tony Prescott and Dr. Stuart Wilson from the University's Department of Computer Science, say that AI systems are unlikely to resemble real brain processing no matter how large their neural networks or the datasets used to train them might become, if they remain disembodied.

Current AI systems, such as ChatGPT, use large neural networks to solve difficult problems, such as generating intelligible written text. These networks teach AI to process data in a way that is inspired by the human brain and also learn from their mistakes in order to improve and become more accurate.

Although these models have similarities to the human brain, the Sheffield researchers say there are also important differences, which are preventing them from gaining biological-like intelligence.

Firstly, real brains are embodied in a physical system—the human body—that directly senses and acts in the world. Being embodied makes brain processes meaningful in a way that is not possible for disembodied AIs, which can learn to recognize and generate complex patterns in data but lack a direct connection to the physical world. Therefore such AIs have no understanding or awareness of the world around them.

Secondly, human brains are made up of multiple subsystems, which are organized in a specific configuration—known as architecture—that is similar in all vertebrate animals from fish to humans, but not in AI.

The Sheffield study suggests that biological intelligence—like in the human brain—has developed because of this specific architecture and how it has used its connections to the real world to overcome challenges, learn and improve throughout evolution. This interaction between evolution and development is rarely factored into the design of AI, according to the study.  ... '