Study Finds: AI Won’t Gain Human-Like Cognition, Unless Connected To Real World Through Robots

According to a study, it is doubtful that artificial intelligence (AI) systems will develop human-like cognition unless they are linked to the actual world via robots and built according to evolutionary design principles.

The mental process of learning and comprehending through thought, experience, and the senses is known as cognition.

No matter how extensive their neural networks or the datasets used to train them may get, the research, which was published in the journal Science Robotics, concluded that if AI systems stay disembodied, they would not resemble genuine brain processing.

The Global Research

According to researchers from the University of Sheffield in the UK, Current AI systems, like ChatGPT, use large neural networks to address challenging challenges, such as producing understandable written content.

These networks educate AI to process data in a manner that is modeled after the human brain while also learning from errors to become better and more accurate.

Although these models resemble the human brain, the researchers claimed that there are still significant distinctions that prohibit them from developing intelligence that is biologically equivalent.

First of all, they claimed, actual brains are physically present in the human body, a system that directly perceives and responds to the outside world.

In contrast to disembodied AIs, which can learn to recognize and develop sophisticated patterns in data but lack a direct relationship to the real world, being embodied gives brain processes significance in a way that is not feasible, according to the researchers.

They said that as a result, such AIs are ignorant of their surroundings and lack consciousness.

Second, human brains are made up of a variety of subsystems that are arranged in a particular way, or architecture, that is shared by all vertebrate creatures, including fish and humans, but not AI.

According to the study, biological intelligence, such as that seen in the human brain, has evolved as a result of this particular architecture and how it has leveraged connections to the outside world to overcome obstacles, pick up new skills, and get better over time.

The researchers found that the connection between evolution and development is rarely taken into account while designing AI.

According to Professor Tony Prescott of the University of Sheffield, “ChatGPT and other large neural network models are exciting developments in AI that show that really difficult challenges like learning the structure of human language can be solved.”

However, Prescott warned that if the same design approaches are used in the future, these AI systems “are unlikely to advance to the point where they can fully think like a human brain.”

If AI systems are created with designs that learn and advance similarly to how the human brain does use its links to the outside world, they will be much more likely to achieve human-like cognition, he continued.

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