The only working model of human-level intelligence, as far as we know, is the human brain. We have no evidence of any higher form of intelligence anywhere in the universe. Yet scientists from widely varied areas of cognitive studies continue to make unlikely claims that they will achieve reverse-engineering of the human brain within 10 or 20 years. The problem with humans attempting to use machines to emulate intelligence, is that humans do not understand intelligence very well at all.
Recent progress in "memristor synapses" has given reverse-engineers of the brain hope, that they may finally be developing a hardware substrate that is better capable of emulating brain function. But even if that is true, how close do these developments place us to the goal of reverse-engineering a functioning human brain? Bluntly put, not close at all.
Scientists are slowly gaining an appreciation for how human memories are encoded -- within and by the hippocampus. For example, new memory formation requires the hippocampus to be able to produce new nerve cells of various types from stem cells. Some neuroscientists apparently feel that this understanding will help them to discover new "drug targets" for treating memory dysfunction, such as dementia. We should hope so, because dementia and brain atrophy of one form or another waits for virtually all of us -- if we live long enough.
But successful treatment of dementia does not help us to understand how our intelligence works -- except insofar as it provides tools for further research into the intricate mechanisms of human learning, memory, and creative imagination.
The encoding and decoding of human memories (more) has virtually nothing in common with what is generally thought of as "computation." Consequently the substrate of ordinary computation -- such as digital computers -- should not be seen as likely substrates for reverse engineering a human brain.
Human intelligence evolved over millions of years by natural selection, in the course of solving a variety of problems of survival. Human brains are not well evolved to solve the most pressing problems currently facing human societies. The average IQ for human populations is just below 90 points, and on a downward, dysgenic trajectory. Most humans are simply not intelligent enough to solve complex problems -- except those for which the human brain is evolved to solve. Most of the "big" problems of today do not fall within that category.
Even most humans with IQs in the 130 to 180 ++ range are generally not well suited to understand the basis for their own intelligence on any logical level -- much less most or all of them. If the potential to understand our own intelligence rests within the developing embryo and infant child, its critical window of development inevitably passes without the proper training. And so it goes, almost certainly, for a significant number of potential human abilities -- lost out of ignorance. But I digress.
Artificial intelligence research suffers from the lack of individuals with a special combination of trained aptitudes. Brilliant researchers abound in the disparate disciplines of computer science, neuroscience, cognitive psychology, linguistics, anthropology, philosophy, electrical engineering, and a wide array of creative, inventive, and speculative arts and sciences. But workers with the right combinations of skills and attitudes are extremely rare. The potential accomplishments of the uni-disciplinary approach to higher education evaporate very quickly when it comes to solving the extremely hard problems with which we are faced.
Solving the problem will require a different way of thinking about the problem. But that is a virtual impossibility for most people -- no matter how "intelligent."
Contemplate what may be involved in the efficient teaching and learning of "lateral thinking." The most rewarding known examples of lateral thinking occurred by accident. But de Bono claims to be able to teach the skill. It is virtually certain that such teaching is more effective if initiated during childhood -- and more effective in some children than in others.
Modern human knowledge is "full of holes", like a Sierpinski gasket. No matter how conscientiously we set about to fill in the holes, we only create more holes. Humans need to learn to relish this creation of holes, because the more holes we create, the more we have filled in. But the development of such a relishing of the fractal world of knowledge must likely begin in childhood.
Which brings us back to the creation and upbringing of children, their training and the societal milieu in which they are to be raised. We are botching the job rather badly at this time.
More on these topics later.
HAL: Dave, this conversation can serve no purpose anymore. Goodbye.
ReplyDeleteThis and a host of other reasons is why I agree that sentient AI will not be developed for quite some time.
ReplyDeleteWonderful insights on a wonderful subject. Your article reminds me of Albert Einstein being buried in 1955 sans his brain. Many years later, scientists took sample tissues from Einstein's brain and compared them with samples from the brains of a banker and a mason. They discovered that Einstein's had more complex networks. That's all. They were no closer to understanding human intelligence in general and Einstein's in particular.
ReplyDeleteDoctors in the West tend to regard the human body as no more than a machine. It's the same mistake that's now being repeated by those who seek a better understanding of human intelligence and attempt to create something that would mimic it.
Two cents worth from Barista Uno of Marine Cafe Blog.