(Image: Zen Buddha Silence by Marilyn Barbone.)
August 20, 2017
This week’s blog post covers another book by the theoretical physicist Michio Kaku—The Future of the Mind (First Anchor Books, 2015).
Most of the wealth we humans have created is a result of technological progress (in the context of some form of capitalism plus the rule of law). Most future wealth will result directly from breakthroughs in physics, artificial intelligence, genetics, and other sciences. This is why AI is fascinating in general (not just for investing). AI—in combination with other technologies—may eventually turn out to be the most transformative technology of all time.
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Physicists have been quite successful historically because of their ability to gather data, to measure ever more precisely, and to construct testable, falsifiable mathematical models to predict the future based on the past. Kaku explains:
When a physicist first tries to understand something, first he collects data and then he proposes a “model,” a simplified version of the object he is studying that captures its essential features. In physics, the model is described by a series of parameters (e.g., temperature, energy, time). Then the physicist uses the model to predict its future evolution by simulating its motions. In fact, some of the world’s largest supercomputers are used to simulate the evolution of models, which can describe protons, nuclear explosions, weather patterns, the big bang, and the center of black holes. Then you create a better model, using more sophisticated parameters, and simulate it in time as well. (page 42)
Kaku then writes that he’s taken bits and pieces from fields such as neurology and biology in order to come up with a definition of consciousness:
Consciousness is a process of creating a model of the world using multiple feedback loops in various parameters (e.g., in temperature, space, time, and in relation to others), in order to accomplish a goal (e.g., find mates, food, shelter).
Kaku emphasizes that humans use the past to predict the future, whereas most animals are focused only on the present or the immediate future.
Kaku writes that one can rate different levels of consciousness based on the definition. The lowest level of consciousness is Level 0, where an organism has limited mobility and creates a model using feedback loops in only a few parameters (e.g., temperature). Kaku gives the thermostat as an example. If the temperature gets too hot or too cold, the thermostat registers that fact and then adjusts the temperature accordingly using an air conditioner or heater. Kaku says each feedback loop is “one unit of consciousness,” so the thermostat – with only one feedback loop – would have consciousness of Level 0:1.
Organisms that are mobile and have a central nervous system have Level I consciousness. There’s a new set of parameters—relative to Level 0—based on changing locations. Reptiles are an example of Level I consciousness. The reptilian brain may have a hundred feedback loops based on their senses, etc. The totality of feedback loops give the reptile a “mental picture” of where they are in relation to various objects (including prey), notes Kaku.
Animals exemplify Level II consciousness. The number of feedback loops jumps exponentially, says Kaku. Many animals have complex social structures. Kaku explains that the limbic system includes the hippocampus (for memories), the amygdala (for emotions), and the thalamus (for sensory information).
You could rank the specific level of Level II consciousness of an animal by listing the total number of distinct emotions and social behaviors. So, writes Kaku, if there are ten wolves in the wolf pack, and each wolf interacts with all the others with fifteen distinct emotions and gestures, then a first approximation would be that wolves have Level II:150 consciousness. (Of course, there are caveats, since evolution is never clean and precise, says Kaku.)
LEVEL III CONSCIOUSNESS: SIMULATING THE FUTURE
Kaku observes that there is a continuum of consciousness from the most basic organisms up to humans. Kaku quotes Charles Darwin:
The difference between man and the higher animals, great as it is, is certainly one of degree and not of kind.
Kaku defines human consciousness:
Human consciousness is a specific form of consciousness that creates a model of the world and then simulates it in time, by evaluating the past to simulate the future. This requires mediating and evaluating many feedback loops in order to make a decision to achieve a goal.
Kaku explains that we as humans have so many feedback loops that we need a “CEO”—an expanded prefrontal cortex that can analyze all the data logically and make decisions. More precisely, Kaku writes that neurologist Michael Gazzaniga has identified area 10, in the lateral prefrontal cortex, which is twice as big in humans as in apes. Area 10 is where memory, planning, abstract thinking, learning rules, picking out what is relevant, etc. happens. Kaku says he will refer to this region as the dorsolateral prefrontal cortex, roughly speaking.
Most animals, by constrast, do not think and plan, but rely on instinct. For instance, notes Kaku, animals do not plan to hibernate, but react instinctually when the temperature drops. Predators plan, but only for the immediate future. Primates plan a few hours ahead.
Humans, too, rely on instinct and emotion. But humans also analyze and evaluate information, and run mental simulations of the future—even hundreds or thousands of years into the future. This, writes Kaku, is how we as humans try to make the best decision in pursuit of a goal. Of course, the ability to simulate various future scenarios gives humans a great evolutionary advantage for things like evading predators and finding food and mates.
As humans, we have so many feedback loops, says Kaku, that it would be a chaotic sensory overload if we didn’t have the “CEO” in the dorsolateral prefrontal cortex. We think in terms of chains of causality in order to predict future scenarios. Kaku explains that the essence of humor is simulating the future but then having an unexpected punch line.
Children play games largely in order to simulate specific adult situations. When adults play various games like chess, bridge, or poker, they mentally simulate various scenarios.
Kaku explains the mystery of self-awareness:
Self-awareness is creating a model of the world and simulating the future in which you appear.
As humans, we constantly imagine ourselves in various future scenarios. In a sense, we are continuously running “thought experiments” about our lives in the future.
Kaku writes that the medial prefrontal cortex appears to be responsible for creating a coherent sense of self out of the various sensations and thoughts bombarding our brains. Furthermore, the left brain fits everything together in a coherent story even when the data don’t make sense. Dr. Michael Gazzaniga was able to show this by running experiments on split-brain patients.
Kaku speculates that humans can reach better conclusions if the brain receives a great deal of competing data. With enough data and with practice and experience, the brain can often reach correct conclusions.
At the beginning of the next section—Mind Over Matter—Kaku quotes Harvard psychologist Steven Pinker:
The brain, like it or not, is a machine. Scientists have come to that conclusion, not because they are mechanistic killjoys, but because they have amassed evidence that every aspect of consciousness can be tied to the brain.
DARPA is the Pentagon’s Defense Advanced Research Projects Agency. Kaku writes that DARPA has been central to some of the most important technological breakthroughs of the twentieth century.
President Dwight Eisenhower set up DARPA originally as a way to compete with the Russians after they launched Sputnik into orbit in 1957. Over the years, some of DARPA’s projects became so large that they spun them off as separate entities, including NASA.
DARPA’s “only charter is radical innovation.” DARPA scientists have always pushed the limits of what is physically possible. One of DARPA’s early projects was Arpanet, a telecommunications network to connect scientists during and after World War III. After the breakup of the Soviet bloc, the National Science Foundation decided to declassify Arpanet and give away the codes and blueprints for free. This would eventually become the internet.
DARPA helped create Project 57, which was a top-secret project for guiding ballistic missiles to specific targets. This technology later became the foundation for the Global Positioning System (GPS).
DARPA has also been a key player in other technologies, including cell phones, night-vision goggles, telecommunications advances, and weather satellites, says Kaku.
Kaku writes that, with a budget over $3 billion, DARPA has recently focused on the brain-machine interface. Kaku quotes former DARPA official Michael Goldblatt:
Imagine if soldiers could communicate by thought alone… Imagine the threat of biological attack being inconsequential. And contemplate, for a moment, a world in which learning is as easy as eating, and the replacement of damaged body parts as convenient as a fast-food drive-through. As impossible as these visions sound or as difficult as you might think the task would be, these visions are the everyday work of the Defense Sciences Office [a branch of DARPA]. (page 74)
Goldblatt, notes Kaku, thinks the long-term legacy of DARPA will be human enhancement. Goldblatt’s daughter has cerebral palsy and has been confined to a wheelchair all her life. Goldblatt is highly motivated not only to help millions of people in the future and create a legacy, but also to help his own daughter.
Cathy Hutchinson became a quadriplegic after suffering a massive stroke. But in May 2012, scientists from Brown University placed a tiny chip on top of her brain—called Braingate—which is connected by wires to a computer. (The chip has ninety-six electrodes for picking up brain impulses.) Her brain could then send signals through the computer to control a mechanical robotic arm. She reported her great excitement and said she knows she will get robotic legs eventually, too. This might happen soon, says Kaku, since the field of cyber prosthetics is advancing fast.
Scientists at Northwestern placed a chip with 100 electrodes on the brain of a monkey. The signals were carefully recorded while the monkey performed various tasks involving the arms. Each task would involve a specific firing of neurons, which the scientists eventually were able to decipher.
Next, the scientists took the signal sequences from the chip and instead of sending them to a mechanical arm, they sent the signals to the monkey’s own arm. Eventually the monkey learned to control its own arm via the computer chips. (The reason 100 electrodes is enough is because they were placed on the output neurons. So the monkey’s brain had already done the complex processing involving millions of neurons by the time the signals reached the electrodes.)
This device is one of many that Northwestern scientists are testing. These devices, which continue to be developed, can help people with spinal cord injuries.
Kaku observes that much of the funding for these developments comes from a DARPA project called Revolutionizing Prosthetics, a $150 million effort since 2006. Retired U.S. Army colonel Geoffrey Ling, a neurologist with several tours of duty in Iraq and Afghanistan, is a central figure behind Revolutionizing Prosthetics. Dr. Ling was appalled by the suffering caused by roadside bombs. In the past, many of these brave soldiers would have died. Today, many more can be saved. However, more than 1,300 of them have lost limbs after returning from the Middle East.
Dr. Ling, with funding from the Pentagon, instructed his staff to figure out how to replace lost limbs within five years. Ling:
They thought we were crazy. But it’s in insanity that things happen.
Spurred into action by Dr. Ling’s boundless enthusiasm, his crew has created miracles in the laboratory. For example, Revolutionary Prosthetics funded scientists at the Johns Hopkins Applied Physics Laboratory, who have created the most advanced mechanical arm on Earth, which can duplicate nearly all the delicate motions of the fingers, hand, and arm in three dimensions. It is the same size and has the same strength and agility as a real arm. Although it is made of steel, if you covered it up with flesh-colored plastic, it would be nearly indistinguishable from a real arm.
This arm was attached to Jan Sherman, a quadriplegic who had suffered from a genetic disease that damaged the connection between her brain and her body, leaving her completely paralyzed from the neck down. At the University of Pittsburgh, electrodes were placed directly on top of her brain, which were then connected to a computer and then to a mechanical arm. Five months after surgery to attach the arm, she appeared on 60 Minutes. Before a national audience, she cheerfully used her new arm to wave, greet the host, and shake his hand. She even gave him a fist bump to show how sophisticated the arm was.
Dr. Ling says, ‘In my dream, we will be able to take this into all sorts of patients, patients with strokes, cerebral palsy, and the elderly.‘ (page 84)
Dr. Miguel Nicholelis of Duke University is pursuing novel applications of the brain-machine interface (BMI). Dr. Nicholelis has demonstrated that BMI can be done across continents. He put a chip on a monkey’s brain. The chip was connected to the internet. When the monkey was walking on a treadmill in North Carolina, the signals were sent to a robot in Kyoto, Japan, which performed the same walking motions.
Dr. Nicholelis is also working on the problem that today’s prosthetic hands lack a sense of touch. Dr. Nicholelis is trying to create a direct brain-to-brain interface to overcome this challenge. Messages would go from the brain to the mechanical arm, and then directly back to the brain, bypassing the stem altogether. This is a brain-machine-brain interface (BMBI).
Dr. Nicholelis connected the motor cortex of rhesus monkeys to mechanical arms. The mechanical arms have sensors, and send signals back to the brain by electrodes connected to the somato-sensory cortex (which registers the sensation of touch). Dr. Nicholelis invented a new code to represent different surfaces. After a month of practice, the brain learns the new code and can thus distinguish among different surfaces.
Dr. Nicholelis told Kaku that something like the holodeck from Star Trek—where you wander in a virtual world, but feel sensations when you bump into virtual objects—will be possible in the future. Kaku writes:
The holodeck of the future might use a combination of two technologies. First, people in the holodeck would wear internet contact lenses, so that they would see an entirely new virtual world everywhere they looked. The scenery in your contact lense would change instantly with the push of a button. And if you touched any object in this world, signals sent into the brain would simulate the sensation of touch, using BMBI technology. In this way, objects in the virtual world you see inside your contact lense would feel solid. (page 87)
Scientists have begun to explore an “Internet of the mind,” or brain-net. In 2013, scientists went beyond animal studies and demonstrated the first human brain-to-brain communication.
This milestone was achieved at the University of Washington, with one scientist sending a brain signal (move your right arm) to another scientist. The first scientist wore an EEG helmet and played a video game. He fired a cannon by imagining moving his right arm, but was careful not to move it physically.
The signal from the EEG helmet was sent over the Internet to another scientist, who was wearing a transcranial magnetic helmet carefully placed over the part of his brain that controlled his right arm. When the signal reached the second scientist, the helmet would send a magnetic pulse into his brain, which made his right arm move involuntarily, all by itself. Thus, by remote control, one human brain could control the movement of another.
This breakthrough opens up a number of possibilities, such as exchanging nonverbal messages via the Internet. You might one day be able to send the experience of dancing the tango, bungee jumping, or skydiving to the people on your e-mail list. Not just physical activity, but emotions and feelings as well might be sent via brain-to-brian communication.
Nicholelis envisions a day when people all over the world could participate in social networks not via keyboards, but directly through their minds. Instead of just sending e-mails, people on the brain-net would be able to telepathically exchange thoughts, emotions, and ideas in real time. Today a phone call conveys only the information of the conversation and the tone of voice, nothing more. Video conferencing is a bit better, since you can read the body language of the person on the other end. But a brain-net would be the ultimate in communications, making it possible to share the totality of mental information in a conversation, including emotions, nuances, and reservations. Minds would be able to share their most intimate thoughts and feeelings. (pages 87-88)
Kaku gives more details of what would be needed to create a brain-net:
Creating a brain-net that can transmit such information would have to be done in stages. The first step would be inserting nanoprobes into important parts of the brain, such as the left temporal lobe, which governs speech, and the occipital lobe, which governs vision. Then computers would analyze these signals and decode them. This information in turn could be sent over the Internet by fiber-optic cables.
More difficult would be to insert these signals into another person’s brain, where they could be processed by the receiver. So far, progress in this area has focused only on the hippocampus, but in the future it should be possible to insert messages directly into other parts of the brain corresponding to our sense of hearing, light, touch, etc. So there is plenty of work to be done as scientists try to map the cortices of the brain involved in these senses. Once these cortices have been mapped… it should be possible to insert words, thoughts, memories, and experiences into another brain. (page 89)
Dr. Nicolelis’ next goal is the Walk Again Project. They are creating a complete exoskeleton that can be controlled by the mind. Nicolelis calls it a “wearable robot.” The aim is to allow the paralyzed to walk just by thinking. There are several challenges to overcome:
First, a new generation of microchips must be created that can be placed in the brain safely and reliably for years at a time. Second, wireless sensors must be created so the exoskeleton can roam freely. The signals from the brain would be received wirelessly by a computer the size of a cell phone that would probably be attached to your belt. Third, new advances must be made in deciphering and interpreting signals from the brain via computers. For the monkeys, a few hundred neurons were necessary to control the mechanical arms. For a human, you need, at minimum, several thousand neurons to control an arm or leg. And fourth, a power supply must be found that is portable and powerful enough to energize the entire exoskeleton. (page 92)
MEMORIES AND THOUGHTS
One interesting possibility is that the long-term memory evolved in humans because it was useful for us in simulating and predicting future scenarios.
Indeed, brain scans done by scientists at Washington University in St. Louis indicate that areas used to recall memories are the same as those involved in simulating the future. In particular, the link between the dorsolateral prefrontal cortex and the hippocampus lights up when a person is engaged in planning for the future and remembering the past. In some sense, the brain is trying to ‘recall the future,’ drawing upon memories of the past in order to determine how something will evolve into the future. This may also explain the curious fact that people who suffer from amnesia… are often unable to visualize what they will be doing in the future or even the very next day. (page 113)
Some claim that Alzheimer’s disease may be the disease of the century. As of Kaku’s writing, there were 5.3 million Americans with Alzheimer’s, and that number is expected to quadruple by 2050. Five percent of people aged sixty-five to seventy-four have it, but more than 50 percent of those over eighty-five have it, even if they have no obvious risk factors.
One possible way to try to combat Alzheimer’s is to create antibodies or a vaccine that might specifically target misshapen protein molecules associated with the disease. Another approach might be to create an artificial hippocampus. Yet another approach is to see if specific genes can be found that improve memory. Experiments on mice and fruit flies have been underway.
If the genetic fix works, it could be administered by a simple shot in the arm. If it doesn’t work, another possible approach is to insert the proper proteins into the body. Instead of a shot, it would be a pill. But scientists are still trying to understand the process of memory formation.
Eventually, writes Kaku, it will be possible to record the totality of stimulation entering into a brain. In this scenario, the Internet may become a giant library not only for the details of human lives, but also for the actual consciousness of various individuals. If you want to see how your favorite hero or historical figure felt as they confronted the major crises of their lives, you’ll be able to do so. Or you could share the memories and thoughts of a Nobel Prize-winning scientist, perhaps gleaning clues about how great discoveries are made.
ENHANCING OUR INTELLIGENCE
What made Einstein Einstein? It’s very difficult to say, of course. Partly, it may be that he was the right person at the right time. Also, it wasn’t just raw intelligence, but perhaps more a powerful imagination and an ability to stick with problems for a very long time. Kaku:
The point here is that genius is perhaps a combination of being born with certain mental abilities and also the determination and drive to achieve great things. The essence of Einstein’s genius was probably his extraordinary ability to simulate the future through thought experiments, creating new physical principles via pictures. As Einstein himself once said, ‘The true sign of intelligence is not knowledge, but imagination.’ And to Einstein, imagination meant shattering the boundaries of the known and entering the domain of the unknown. (page 133)
The brain remains “plastic” even into adult life. People can always learn new skills. Kaku notes that the Canadian psychologist Dr. Donald Hebb made an important discovery about the brain:
the more we exercise certain skills, the more certain pathways in our brains become reinforced, so the task becomes easier. Unlike a digital computer, which is just as dumb today as it was yesterday, the brain is a learning machine with the ability to rewire its neural pathways every time it learns something. This is a fundamental difference between the digital computer and the brain. (page 134)
Scientists also believe that the ability to delay gratification and the ability to focus attention may be more important than IQ for success in life.
Furthermore, traditional IQ tests only measure “convergent” intelligence related to the left brain and not “divergent” intelligence related to the right brain. Kaku quotes Dr. Ulrich Kraft:
‘The left hemisphere is responsible for convergent thinking and the right hemisphere for divergent thinking. The left side examines details and processes them logically and analytically but lacks a sense of overriding, abstract connections. The right side is more imaginative and intuitive and tends to work holistically, integrating pieces of an informational puzzle into a whole.’ (page 138)
Kaku suggests that a better test of intelligence might measure a person’s ability to imagine different scenarios related to a specific future challenge.
Another avenue of intelligence research is genes. We are 98.5 percent identical genetically to chimpanzees. But we live twice as long and our mental abilities have exploded in the past six million years. Scientists have even isolated just a handful of genes that may be responsible for our intelligence. This is intriguing, to say the least.
In addition to having a larger cerebral cortex, our brains have many folds in them, vastly increasing their surface area. (The brain of Carl Friedrich Gauss was found to be especially folded and wrinkled.)
Scientists have also focused on the ASPM gene. It has mutated fifteen times in the last five or six million years. Kaku:
Because these mutations coincide with periods of rapid growth in intellect, it it tantalizing to speculate that ASPM is among the handful of genes responsible for our increased intelligence. If this is true, then perhaps we can determine whether these genes are still active today, and whether they will continue to shape human evolution in the future. (page 154)
Scientists have also learned that nature takes numerous shortcuts in creating the brain. Many neurons are connected randomly, so a detailed blueprint isn’t needed. Neurons organize themselves in a baby’s brain in reaction to various specific experiences. Also, nature uses modules that repeat over and over again.
It is possible that we will be able to boost our intelligence in the future, which will increase the wealth of society (probably significantly). Kaku:
It may be possible in the coming decades to use a combination of gene therapy, drugs, and magnetic devices to increase our intelligence. (page 162)
…raising our intelligence may help speed up technological innovation. Increased intelligence would mean a greater ability to simulate the future, which would be invaluable in making scientific discoveries. Often, science stagnates in certain areas because of a lack of fresh new ideas to stmulate new avenues of research. Having an ability to simulate different possible futures would vastly increase the rate of scientific breakthroughs.
These scientific discoveries, in turn, could generate new industries, which would enrich all of society, creating new markets, new jobs, and new opportunities. History if full of technological breakthroughs creating entirely new industries that benefited not just the few, but all of society (think of the transistor and the laser, which today form the foundation of the world economy). (page 164)
Kaku explains that the brain, as a neural network, may need to dream in order to function well:
The brain, as we have seen, is not a digital computer, but rather a neural network of some sort that constantly rewires itself after learning new tasks. Scientists who work with neural networks noticed something interesting, though. Often these systems would become saturated after learning too much, and instead of processing more information they would enter a “dream” state, whereby random memories would sometimes drift and join together as the neural networks tried to digest all the new material. Dreams, then, might reflect “house cleaning,” in which the brain tries to organize its memories in a more coherent way. (If this is true, then possibly all neural networks, including all organisms that can learn, might enter a dream state in order to sort out their memories. So dreams probably serve a purpose. Some scientists have speculated that this might imply that robots that learn from experience might also eventually dream as well.)
Neurological studies seem to back up this conclusion. Studies have shown that retaining memories can be improved by getting sufficient sleep between the time of activity and a test. Neuroimaging shows that the areas of the brain that are activated during sleep are the same a those involved in learning a new task. Dreaming is perhaps useful in consolidating this new information. (page 172)
In 1977, Dr. Allan Hobson and Dr. Robert McCarley made history – seriously challenging Freud’s theory of dreams—by proposing the “activation synthesis theory” of dreams:
The key to dreams lies in nodes found in the brain stem, the oldest part of the brain, which squirts out special chemicals, called adrenergics, that keep us alert. As we go to sleep, the brain stem activates another system, the cholinergic, which emits chemicals that put us in a dream state.
As we dream, cholinergic neurons in the brain stem begin to fire, setting off erratic pulses of electrical energy called PGO (pontine-geniculate-occipital) waves. These waves travel up the brain stem into the visual cortex, stimulating it to create dreams. Cells in the visual cortex begin to resonate hundreds of times per second in an irregular fashion, which is perhaps responsible for the sometimes incoherent nature of dreams. (pages 174-175)
ALTERED STATE OF CONSCIOUSNESS
There seem to be certain parts of the brain that are associated with religious experiences and also with spirituality. Dr. Mario Beauregard of the University of Montreal commented:
If you are an atheist and you live a certain kind of experience, you will relate it to the magnificence of the universe. If you are a Christian, you will associate it with God. Who knows. Perhaps they are the same thing.
Kaku explains how human consciousness involves delicate checks and balances similar to the competing points of view that a good CEO considers:
We have proposed that a key function of human consciousness is to simulate the future, but this is not a trivial task. The brain accomplishes it by having these feedback loops check and balance one another. For example, a skillful CEO at a board meeting tries to draw out the disagreement among staff members and to sharpen competing points of view in order to sift through the various arguments and then make a final decision. In the same way, various regions of the brain make diverging assessments of the future, which are given to the dorsolateral profrontal cortex, the CEO of the brain. These competing assessments are then evaluated and weighted until a balanced final decision is made. (page 205)
The most common mental disorder is depression, afflicting twenty million people in the United States. One way scientists are trying to cure depression is deep brain stimulation (DBS)—inserting small probes into the brain and causing an electrical shock. Kaku:
In the past decade, DBS has been used on forty thousand patients for motor-related diseases, such as Parkinson’s and epilepsy, which cause uncontrolled movements of the body. Between 60 and 100 percent of the patients report significant improvement in controlling their shaking hands. More than 250 hospitals in the United States now perform DBS treatment. (page 208)
Dr. Helen Mayberg and colleagues at Washington University School of Medicine have discovered an important clue to depression:
Using brain scans, they identified an area of the brain, called Brodmann area 25 (also called the subcallosal cingulate region), in the cerebral cortex that is consistently hyperactive in depressed individuals for whom all other forms of treatment have been unsuccessful.
…Dr. Mayberg had the idea of applying DBS directly to Broadmann area 25… her team took twelve patients who were clinically depressed and had shown no improvement after exhaustive use of drugs, psychotherapy, and electroshock therapy.
They found that eight of these chronically depressed individuals showed immediate progress. Their success was so astonishing, in fact, that other groups raced to duplicate these results and apply DBS to other mental disorders…
Dr. Mayberg says, ‘Depression 1.0 was psychotherapy… Depression 2.0 was the idea that it’s a chemical imbalance. This is Depression 3.0. What has captured everyone’s imagination is that, by dissecting a complex behavior disorder into its component systems, you have a new way of thinking about it.’
Although the success of DBS in treating depressed individuals is remarkable, much more research needs to be done…
THE ARTIFICIAL MIND AND SILICON CONSCIOUSNESS
Kaku introduces the potential challenge of handling artificial intelligence as it evolves:
Given the fact that computer power has been doubling every two years for the past fifty years under Moore’s law, some say it is only a matter of time before machines eventually acquire self-awareness that rivals human intelligence. No one knows when this will happen, but humanity should be prepared for the moment when machine consciousness leaves the laboratory and enters the real world. How we deal with robot consciousness could decide the future of the human race. (page 216)
Kaku observes that AI has gone through three cycles of boom and bust. In the 1950s, machines were built that could play checkers and solve algebra problems. Robot arms could recognize and pick up blocks. In 1965, Dr. Herbert Simon, one of the founders of AI, made a prediction:
Machines will be capable, within 20 years, of doing any work a man can do.
In 1967, another founder of AI, Dr. Marvin Minsky, remarked:
…within a generation… the problem of creating ‘artificial intelligence’ will substantially be solved.
But in the 1970s, not much progress in AI had been made. In 1974, both the U.S. and British governments significantly cut back their funding for AI. This was the beginning of the first AI winter.
But as computer power steadily increased in the 1980s, a new gold rush occurred in AI, fueled mainly by Pentagon planners hoping to put robot soldiers on the battlefield. Funding for AI hit a billion dollars by 1985, with hundreds of millions of dollars spent on projects like the Smart Truck, which was supposed to be an intelligent, autonomous truck that could enter enemy lines, do reconnaissance by itself, perform missions (such as rescuing prisoners), and then return to friendly territory. Unfortunately, the only thing that the Smart Truck did was get lost. The visible failures of these costly projects created yet another AI winter in the 1990s. (page 217)
But now, with the relentless march of computer power, a new AI renaissance has begun, and slow but substantial progress has been made. In 1997, IBM’s Deep Blue computer beat world chess champion, Garry Kasparov. In 2005, a robot car from Stanford won the DARPA Grand Challenge for a driverless car. Milestones continue to be reached.
This question remains: Is the third try a charm?
Scientists now realize that they vastly underestimated the problem, because most human thought is actually subconscious. The conscious part of our thoughts, in fact, represents only the tiniest portion of our computations.
Dr. Steve Pinker says, ‘I would pay a lot for a robot that would put away the dishes or run simple errands, but I can’t, because all of the little problems that you’d need to solve to build a robot to do that, like recognizing objects, reasoning about the world, and controlling hands and feet, are unsolved engineering problems.’ (pages 217-218)
Kaku asked Dr. Minsky when he thought machines would equal and then surpass human intelligence. Minsky replied that he’s confident it will happen, but that he doesn’t make predictions about specific dates any more.
If you remove a single transistor from a Pentium chip, the computer will immediately crash, writes Kaku. But the human brain can perform quite well even with half of it missing:
This is because the brain is not a digital computer at all, but a highly sophisticated neural network of some sort. Unlike a digital computer, which has a fixed architecture (input, output, and processor), neural networks are collections of neurons that constantly rewire and reinforce themselves after learning a new task. The brain has no programming, no operating system, no Windows, no central processor. Instead, its neural networks are massively parallel, with one hundred billion neurons firing at the same time in order to accomplish a single goal: to learn.
In light of this, AI researchers are beginning to reexamine the ‘top-down approach’ they have followed for the past fifty years (e.g., putting all the rules of common sense on a CD). Now AI researchers are giving the ‘bottom-up approach’ a second look. This approach tries to follow Mother Nature, which has created intelligent beings (us) via evolution, starting with simple animals like worms and fish and then creating more complex ones. Neural networks must learn the hard way, by bumping into things and making mistakes. (page 220)
Dr. Rodney Brooks, former director of the MIT Artificial Intelligence Laboratory, introduced a totally new approach to AI. Why not build small, insectlike robots that learn how to walk by trail and error, just as nature learns? Brooks told Kaku that he used to marvel at the mosquito, with a microscopic brain of a few neurons, which can, nevertheless, maneuver in space better than any robot airplane. Brooks built a series of tiny robots called ‘insectoids’ or ‘bugbots,’ which learn by bumping into things. Kaku comments:
At first, it may seem that this requires a lot of programming. The irony, however, is that neural networks require no programming at all. The only thing that the neural network does is rewire itself, by changing the strength of certain pathways each time it makes a right decision. So programming is nothing; changing the network is everything. (page 221)
The Mars Curiosity rover is one result of this bottom-up approach.
Scientists have realized that emotions are central to human cognition. Humans usually need some emotional input, in addition to logic and reason, in order to make good decisions. Robots are now be programmed to recognize various human emotions and also to exhibit emotions themselves. Robots also need a sense of danger and some feeling of pain in order to avoid injuring themselves. Eventually, as robots become ever more conscious, there will be many ethical questions to answer.
Biologists used to debate the question, “What is life?” But, writes Kaku, the physicist and Nobel Laureate Francis Crick has observed that the question is not well-defined now that we are advancing in our understanding of DNA. There are many layer and complexities to the question, “What is life?” Similarly, there are likely to be many layers and complexities to the question of what constitutes “emotion” or “consciousness.”
Moreover, as Rodney Brooks argues, we humans are machines. Eventually the robot machines we are building will be just as alive as we are. Kaku summarizes a conversation he had with Brooks:
This evolution in human perspective started with Nicholaus Copernicus when he realized that the Earth is not the center of the universe, but rather goes around the sun. It continued with Darwin, who showed that we were similar to the animals in our evolution. And it will continue into the future… when we realize that we are machines, except that we are made of wetware and not hardware. (page 248)
Kaku then quotes Brooks directly:
We don’t like to give up our specialness, so you know, having the idea that robots could really have emotions, or that robots could be living creatures—I think is going to be hard for us to accept. But we’re going to come to accept it over the next fifty years.
Brooks also thinks we will successfully create robots that are safe for humans:
…The robots are coming, but we don’t have to worry too much about that. It’s going to be a lot of fun.
Furthermore, Brooks argues that we are likely to merge with robots. After all, we’ve already done this to an extent. Over twenty thousand people have cochlear implants, giving them the ability to hear.
Similarly, at the University of Southern California and elsewhere, it is possible to take a patient who is blind and implant an artificial retina. One method places a mini video camera in eyeglasses, which converts an image into digital signals. These are sent wirelessly to a chip placed in the person’s retina. The chip activates the retina’s nerves, which then send messages down the optic nerve to the occipital lobe of the brain. In this way, a person who is totally blind can see a rough image of familiar objects. Another design has a light-sensitive chip placed on the retina itself, which then sends signals directly to the optic nerve. This design does not need an external camera. (page 249)
This means, says Kaku, that eventually we’ll be able to enhance our ordinary senses and abilities. We’ll merge with our robot creations.
REVERSE ENGINEERING THE BRAIN
Kaku highlights three approaches to the brain:
Because the brain is so complex, there are at least three distinct ways in which it can be taken apart, neuron by neuron. The first is to simulate the brain electronically with supercomputers, which is the approach being taken by the Europeans. The second is to map out the neural pathways of living brains, as in BRAIN [Brain Research Through Advancing Innovative Neurotechnologies Initiative]. (This task, in turn, can be further subdivided, depending on how these neurons are analyzed – either anatomically, neuron by neuron, or by function and activity.) And third, one can decipher the genes that control the development of the brain, which is an approach pioneered by billionaire Paul Allen of Microsoft. (page 253)
- Human Brain Project: https://www.humanbrainproject.eu/en/
- BRAIN: https://www.braininitiative.nih.gov
- Human Connectome Project: http://www.humanconnectomeproject.org/
- Allen Brain Atlas: http://www.brain-map.org/
Dr. Henry Markram is a central figure in the Human Brain Project. Kaku quotes Dr. Markram:
To build this—the supercomputers, the software, the research—we need around one billion dollars. This is not expensive when one considers that the global burden of brain disease will exceed twenty percent of the world gross domestic project very soon.
Dr. Markram also said:
It’s essential for us to understand the human brain if we want to get along in society, and I think that it is a key step in evolution.
How does the human genome go from twenty-three thousand genes to one hundred billion neurons?
The answer, Dr. Markram believes, is that nature uses shortcuts. The key to his approach is that certain modules of neurons are repeated over and over again once Mother Nature finds a good template. If you look at microscopic slices of the brain, at first you see nothing but a random tangle of neurons. But upon closer examination, patterns of modules that are repeated over and over appear.
(Modules, in fact, are one reason why it is possible to assemble large skyscrapers so rapidly. Once a single module is designed, it is possible to repeat it endlessly on the assembly line. Then you can rapidly stack them on top of one another to create the skyscraper. Once the paperwork is all signed, an apartment building can be assembled using modules in a few months.)
The key to Dr. Markram’s Blue Brain project is the “neocortical column,” a module that is repeated over and over in the brain. In humans, each column is about two millimeters tall, with a diameter of half a millimeter, and contains sixty thousand neurons. (As a point of comparison, rat neural modules contain about ten thousand neurons each.) In took ten years, from 1995 to 2005, for Dr. Markram to map the neurons in such a column and to figure out how it worked. Once that was deciphered, he then went to IBM to create massive iterations of these columns. (page 257)
Kaku quotes Dr. Markram again:
…I think, quite honestly, that if the planet understood how the brain functions, we would resolve conflicts everywhere. Because people would understand how trivial and how deterministic and how controlled conflicts and reactions and misunderstandings are.
The slice-and-dice approach:
The anatomical approach is to take apart the cells of an animal brain, neuron by neuron, using the “slice-and-dice” method. In this way, the full complexity of the environment, the body, and memories are already encoded in the model. Instead of approximating a human brain by assembling a huge number of transistors, these scientists want to identify each neuron of the brain. After that, perhaps each neuron can be simulated by a collection of transistors so that you’d have an exact replica of the human brain, complete with memory, personality, and connection to the senses. Once someone’s brain is fully reverse engineered in this way, you should be able to have an informative conversation with that person, complete with memories and a personality. (page 259)
There is a parallel project called the Human Connectome Project.
Most likely, this effort will be folded into the BRAIN project, which will vastly accelerate this work. The goal is to produce a neuronal map of the human brain’s pathways that will elucidate brain disorders such as autism and schizophrenia. (pages 260-261)
Kaku notes that one day automated microscopes will continuously take the photographs, while AI machines continuously analyze them.
The third approach:
Finally, there is a third approach to map the brain. Instead of analyzing the brain by using computer simulations or by identifying all the neural pathways, yet another approach was taken with a generous grant of $100 million from Microsoft billionaire Paul Allen. The goal was to construct a map or atlas of the mouse brain, with the emphasis on identifying the genes responsible for creating the brain.
…A follow-up project, the Allen Human Brain Atlas, was announced… with the hope of creating an anatomically and genetically complete 3-D map of the human brain. In 2011, the Allen Institute announced that it had mapped the biochemistry of two human brains, finding one thousand anatomical sites with one hundred million data points detailing how genes are expressed in the underlying biochemistry. The data confirmed that 82 percent of our genes are expressed in the brain. (pages 261-262)
Kaku says the Human Genome Project was very successful in sequencing all the genes in the human genome. But it’s just the first step in a long journey to understand how these genes work. Similarly, once scientists have reverse engineered the brain, that will likely be only the first step in understanding how the brain works.
Once the brain is reverse-engineered, this will help scientists understand and cure various diseases. Kaku observes that, with human DNA, if there is a single mispelling out of three billion base pairs, that can cause uncontrolled flailing of your limbs and convulsions, as in Huntington’s disease. Similarly, perhaps just a few disrupted connections in the brain can cause certain illnesses.
Successfully reverse engineering the brain also will help with AI research. For instance, writes Kaku, humans can recognize a familiar face from different angles in .1 seconds. But a computer has trouble with this. There’s also the question of how long-term memories are stored.
Finally, if human consciousness can be transferred to a computer, does that mean that immortality is possible?
Kaku talked with Dr. Ray Kurzweil, who told him it’s important for an inventor to anticipate changes. Kurzweil has made a number of predictions, at least some of which have been roughly accurate. Kurzweil predicts that the “singularity” will occur around the year 2045. Machines will have reached the point when they not only have surpassed humans in intelligence; machines also will have created next-generation robots even smarter than themselves.
Kurzweil holds that this process of self-improvement can be repeated indefinitely, leading to an explosion—thus the term “singularity”—of ever-smarter and ever more capable robots. Moreover, humans will have merged with their robot creations and will, at some point, become immortal.
Robots of ever-increasing intelligence and ability will require more power. Of course, there will be breakthroughs in energy technology, likely including nuclear fusion and perhaps even antimatter and/or black holes. So the cost to produce prodigious amounts of energy will keep coming down. At the same time, because Moore’s law cannot continue forever, super robots eventually will need ever-increasing amounts of energy. At some point, this will probably require traveling—or sending nanobot probes—to numerous other stars or to other areas where the energy of antimatter and/or of black holes can be harnessed.
Kaku notes that most people in AI agree that a “singularity” will occur at some point. But it’s extremely difficult to predict the exact timing. It could happen sooner than Kurzweil predicts or it could end up taking much longer.
Kurzweil wants to bring his father back to life. Eventually something like this will be possible. Kaku:
…I once asked Dr. Robert Lanza of the company Advanced Cell Technology how he was able to bring a long-dead creature “back to life,” making history in the process. He told me that the San Diego Zoo asked him to create a clone of a banteng, an oxlike creature that had died out about twenty-five years earlier. The hard part was extracting a usable cell for the purpose of cloning. However, he was successful, and then he FedExed the cell to a farm, where it was implanted into a female cow, which then gave birth to this animal. Although no primate has ever been cloned, let alone a human, Lanza feels it’s a technical problem, and that it’s only a matter of time before someone clones a human. (page 273)
The hard part of cloning a human would be bringing back their memories and personality, says Kaku. One possibility would be creating a large data file containing all known information about a person’s habits and life. Such a file could be remarkably accurate. Even for people dead today, scores of questions could be asked to friends, relatives, and associates. This could be turned into hundreds of numbers, each representing a different trait that could be ranked from 0 to 10, writes Kaku.
When technology has advanced enough, it will become possible—perhaps via the Connectome Project—to recreate a person’s brain, neuron for neuron. If it becomes possible for you to have your connectome completed, then your doctor—or robodoc—would have all your neural connections on a hard drive. Then, says Kaku, at some point, you could be brought back to life, using either a clone or a network of digital transistors (inside an exeskeleton or surrogate of some sort).
Dr. Hans Moravec, former director of the Artificial Intelligence Laboratory at Carnegie Mellon University, has pioneered an intriguing idea: transferring your mind into an immortal robotic body while you’re still alive. Kaku explains what Moravec told him:
First, you lie on a stretcher, next to a robot lacking a brain. Next, a robotic surgeon extracts a few neurons from your brain, and then duplicates these neurons with some transistors located in the robot. Wires connect your brain to the transistors in the robot’s empty head. The neurons are then thrown away and replaced by the transistor circuit. Since your brain remains connected to these transistors via wires, it functions normally and you are fully conscious during this process. Then the super surgeon removes more and more neurons from your brain, each time duplicating these neurons with transistors in the robot. Midway through the operation, half your brain is empty; the other half is connected by wires to a large collection of transistors inside the robot’s head. Eventually all the neurons in your brain have been removed, leaving a robot brain that is an exact duplicate of your original brain, neuron for neuron. (page 280)
When you wake up, you are likely to have a few superhuman powers, perhaps including a form of immortality. This technology is likely far in the future, of course.
Kaku then observes that there is another possible path to immortality that does not involve reverse engineering the brain. Instead, super smart nanobots could periodically repair your cells. Kaku:
…Basically, aging is the buildup of errors, at the genetic and cellular level. As cells get older, errors begin to build up in their DNA and cellular debris also starts to accumulate, which makes the cells sluggish. As cells begin slowly to malfunction, skin begins to sag, bones become frail, hair falls out, and our immune system deteriorates. Eventually, we die.
But cells also have error-correcting mechanisms. Over time, however, even these error-correcting mechanisms begin to fail, and aging accelerates. The goal, therefore, is to strengthen natural cell-repair mechanisms, which can be done via gene therapy and the creation of new enzymes. But there is also another way: using “nanobot” assemblers.
One of the linchpins of this futuristic technology is something called the “nanobot,” or an atomic machine, which patrols the bloodstream, zapping cancer cells, repairing the damage from the aging process, and keeping us forever young and healthy. Nature has already created some nanobots in the form of immune cells that patrol the body in the blood. But these immune cells attack viruses and foreign bodies, not the aging process.
Immortality is within reach if these nanobots can reverse the ravages of the aging process at the molecular and cellular level. In this vision, nanobots are like immune cells, tiny police patrolling your bloodstream. They attack any cancer cells, neutralize viruses, and clean out the debris and mutations. Then the possibility of immortality would be within reach using our own bodies, not some robot or clone. (pages 281-282)
Kaku writes that his personal philosophy is simple: If something is possible based on the laws of physics, then it becomes an engineering and economics problem to build it. A nanobot is an atomic machine with arms and clippers that grabs molecules, cuts them at specific points, and then splices then back together. Such a nanobot would be able to create almost any known molecule. It may also be able to self-reproduce.
The late Richard Smalley, a Nobel Laureate in chemistry, argued that quantum forces would prevent nanobots from being able to function. Eric Drexler, a founder of nanotechnology, pointed out that ribosomes in our own body cut and splice DNA molecules at specific points, enabling the creation of new DNA strands. Eventually Drexler admitted quantum forces do get in the way sometimes, while Smalley acknowledged that if ribosomes can cut and split molecules, perhaps there are other ways, too.
Ray Kurzweil is convinced that nanobots will shape society itself. Kaku quotes Kurzweil:
…I see it, ultimately, as an awakening of the whole universe. I think the whole universe right now is basically made up of dumb matter and energy and I think it will wake up. But if it becomes transformed into this sublimely intelligent matter and energy, I hope to be a part of that.
THE MIND AS PURE ENERGY
Kaku writes that it’s well within the laws of physics for the mind to be in the form of pure energy, able to explore the cosmos. Isaac Asimov said his favorite science-fiction short story was “The Last Question.” In this story, humans have placed their physical bodies in pods, while their minds roam as pure energy. But they cannot keep the universe itself from dying in the Big Freeze. So they create a supercomputer to figure out if the Big Freeze can be avoided. The supercomputer responds that there is not enough data. Eons later, when stars are darkening, the supercomputer finds a solution: It takes all the dead stars and combines them, producing an explosion. The supercomputer says, “Let there be light!”
And there was light. Humanity, with its supercomputer, had become capable of creating a new universe.
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