Scientists are on the verge of building an artificial brain! How do I know? Terry Sejnowski of the Salk Institute said so right here on ScientificAmerican.com. He wrote that the goal of reverse-engineering the brain—which the National Academy of Engineering recently posed as one of its "grand challenges"—is "becoming increasingly plausible." Scientists are learning more and more about the brain, and computers are becoming more and more powerful. So naturally computers will soon be able to mimic the brain's workings. So says Sejnowski.
Sejnowski is a very smart guy, whom I've interviewed several times over the years about the mysteries of the brain. But I respectfully—hell, disrespectfully, Terry can take it—disagree with his prediction that artificial brains are imminent. Sejnowski's own article shows how implausible his prediction is. He describes two projects—both software programs running on powerful supercomputers—that represent the state of the art in brain simulation. On the one hand, you have the "cat brain" constructed by IBM researcher Dharmendra Modha; his simulation contains about as many neurons as a cat's brain does organized into roughly the same architecture. On the other hand, you have the Blue Brain Project of Henry Markram, a neuroscientist at the Ecole Polytechnique Fédérale de Lausanne.
Markram's simulation contains neurons and synaptic connections that are much more detailed than those in Modha's program. Markram recently bashed Modha for "mass deception," arguing that Modha's neurons and synapses are so simple that they don't deserve to be called simulations. Modha’s program is "light years away from a cat brain, not even close to an ant's brain in complexity," Markram complained.
Talk about the pot calling the kettle black. Last year Markram stated, "It is not impossible to build a human brain and we can do it in 10 years." If Modha's simulation is "light years" away from reality, so is Markram's. Neither program includes "sensory inputs or motor outputs," Sejnowski points out, and their neural-signaling patterns resemble those of brains sleeping or undergoing an epileptic seizure. In other words, neither Modha nor Markram can mimic even the simplest operations of a healthy, awake, embodied brain.
The simulations of Modha and Markram are about as brain-like as one of those plastic brains that neuroscientists like to keep on their desks. The plastic brain has all the parts that a real brain does, it's roughly the same color and it has about as many molecules in it. OK, say optimists, the plastic brain doesn't actually perceive, emote, plan or decide, but don't be so critical! Give the researchers time! Another analogy: Current brain simulations resemble the "planes" and "radios" that Melanesian cargo-cult tribes built out of palm fronds, coral and coconut shells after being occupied by Japanese and American troops during World War II. "Brains" that can't think are like "planes" that can't fly.
In spite of all our sophisticated instruments and theories, our own brains are still as magical and mysterious to us as a cargo plane was to those Melanesians. Neuroscientists can't mimic brains because they lack basic understanding of how brains work; they don't know what to include in a simulation and what to leave out. Most simulations assume that the basic physical unit of the brain is the neuron, and the basic unit of information is the electrochemical action potential, or spike, emitted by the neuron. A typical brain contains 100 billion cells, and each cell is linked via dendrites and synapses to as many as 100,000 others. Assuming that each synapse processes one action potential per second and that these transactions represent the brain's computational output, then the brain performs at least one quadrillion operations per second.
Computers are fast approaching this information-processing capacity, leading to claims by artificial intelligence enthusiast Ray Kurzweil and others that computers will soon not just equal but surpass our brains in cognitive power. But the brain may be processing information at many levels below and above that of individual neurons and synapses. Moreover, scientists have no idea how the brain encodes information. Unlike computers, which employ a single, static machine code that translates electrical pulses into information, brains may employ many different "neural codes," which may be constantly changing in response to new experiences.
Go back a decade or two—or five or six—and you will find artificial intelligence pioneers like Marvin Minsky and Herbert Simon proclaiming, because of exciting advances in brain and computer science: Artificial brains are coming! They're going to save us! Or destroy us! Someday, these prophecies may come true, but there is no reason to believe them now.
ABOUT THE AUTHOR
John Horgan, a former Scientific American staff writer, directs the Center for Science Writings at Stevens Institute of Technology. (Photo courtesy of Skye Horgan.)
The views expressed are those of the author and are not necessarily those of Scientific American.