Will we ever be able to create a robot with the same capabilities as humans?
With the explosive appearance of ChatGPT and other Artificial Intelligence programs, the question is not only becoming more and more relevant, but it is further fueling the imagination of engineers seeking to create a robot that thinks and acts like a human.
As the processes progress, several conclusions come to light: we have managed, especially with Artificial Intelligence, to imitate the complex reasoning and even creativity systems of our brain.
But, at the same time, a robot cannot tie a shoe.
Artificial Intelligence and robotics can make reasoned thought require fewer computations, while seemingly simpler human acts, such as tying your shoes or picking up a bag from the ground, require enormous computational effort.
This is known as the Moravec paradox.
And for many experts it is the explanation of why it has not been possible to build a fully intelligent robot.
“Human beings have taken hundreds of thousands of years of evolution to do things as simple as, for example, maintaining balance, so replicating all these processes at a computational level is almost impossible at the moment,” says Gonzalo Zabala, Robotics researcher at the Interamerican Open University, in dialogue with BBC Mundo.
Zabala points out that the opposite occurs with reasoned processes.
“How long have we been able to talk about the intelligent man, about reason? Compared to other processes we evolved, the time is much less, so we can code and replicate this with greater success, ”he says.
Hans Moravec and Alan Turing
One of the forerunners of Artificial Intelligence was undoubtedly the British scientist Alan Turing.
Among the multiple studies that he published during his short but prodigious career, one has to do with a series of questions that would serve to distinguish, in a theoretical case, a robot from a person.
Since it was formulated, in the 1950s, that was the method that guided engineers and theorists around the development of Artificial Intelligence.
As MIT robotics professor Rodney Brooks pointed out, what happened next is that engineers focused on creating programs or artifacts that could “trick” interlocutors by answering the Turing test questions appropriately. to pass for human.
Towards the end of the 70s, that approach began to have a problem: that the logical answers did not develop anything original and the path indicated by Turing began to run out of many exits.
“Even the funding for the research stopped, because it was not clear which way to go and there was no progress,” Brooks told the BBC.
Then, new alternatives were sought to advance in the development of Artificial Intelligence.
“The path that was taken was to create circuits similar to those of the human brain. Not a robot that responded logically, but a circuit that managed to think”, says Zabala.
It was then that this still unresolved contradiction appeared: Artificial Intelligence processes were created with some ease, while basic human functions were basically impossible to recreate in a robot.
This was widely observed towards the end of the 1980s by specialists in robotics such as the aforementioned Brooks, the Austrian Hans Moravec and the American Marvin Misnky.
But it was Moravec, a professor at Carnegie Mellon University in the US, who put it best in 1988 based on the work of the three colleagues:
“It is comparatively easy to make computers show adult-level performance on intelligence tests or playing chess, but difficult or impossible to give them the abilities of a one-year-old when it comes to perception and mobility.“.
Basically, robots can be as smart as they are incapable.
“What the Moravec paradox did was make sense of what was being observed. And when the problem is named, the possible solutions to the problem are named”, says Zabala.
“When this point is reached, something very interesting begins, which is getting to know ourselves better to be able to replicate it in robots: knowing how we maintain our balance, how we learn to drive, in short,” he adds.
Both Moravec and Brooks and Misnky have advanced projects with a view to elucidating the paradox.
Brooks has worked with the American company Boston Dynamics and one he founded, known as iRobots.
The principle they have followed, according to Brooks, is summed up in a direct premise: “If we want to build a robot with human intelligence, let’s first build a robot with human anatomy.”
From this, robot projects have been developed that present an aspect closer to ours.
For example, a team of European scientists has developed a prototype known as the ECCERobot, which has a thermoplastic skeleton complete with vertebrae, phalanges, and rib cage.
The ECCErobot has as many degrees of movement as a human torso, and most importantly, all these parts are packed with sensors.
But the same scientists who have developed the robot have pointed out that the drawback has not been overcome: the complexity of the ECCERobot is so great that it can barely grasp a cup. Therefore, it cannot be expected to have intelligent behavior.
“Building an intelligent humanoid robot, one that can seamlessly interact with humans and human environments naturally will require advances in computing and battery efficiency, not to mention a quantum leap in sensory equipment,” Rolf tells the BBC. Pfeifer, who coordinates the ECCERobot project.
“A really crucial development will be the skin. The skin is extremely important in the development of intelligence because it provides such rich sensory patterns: touch, temperature, pain, all at once”, he adds.
But experts point out that despite the problems presented by Moravec’s paradox, the possibility of a human-like intelligent robot, though distant, is not impossible.
“What the Moravec paradox did was highlight a problem for researchers to look for solutions. One of them, without a doubt, is what we are seeing with the Artificial Intelligence revolution, where we have taken a step towards creation, not just logical answers”, explains Zabala.
And for the expert, it becomes clear that that revolution it’s not a threat to extinction.
“I don’t think it means the end as various analysts have suggested. It is a tool that will facilitate many processes in the future ”, he concludes.
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See original article on BBC