by Ray Kurzweil
The knowledge is right there in front of us, or rather inside of us. It is not impossible to get at. Let’s start with the most straightforward scenario, one that is essentially feasible today (at least to initiate).
We start by freezing a recently deceased brain.
Now, before I get too many indignant reactions, let me wrap myself in Leonardo da Vinci’s cloak. Leonardo also received a disturbed reaction from his contemporaries. Here was a guy who stole dead bodies from the morgue, carted them back to his dwelling, and then took them apart. This was before dissecting dead bodies was in style. He did this in the name of knowledge, not a highly valued pursuit at the time. He wanted to learn how the human body works, but his contemporaries found his activities bizarre and disrespectful. Today we have a different view, that expanding our knowledge of this wondrous machine is the most respectful homage we can pay We cut up dead bodies all the time to learn more about how living bodies work, and to teach others what we have already learned.
There’s no difference here in what I am suggesting. Except for one thing: I am talking about the brain, not the body. This strikes closer to home. We identify more with our brains than our bodies. Brain surgery is regarded as more invasive than toe surgery. Yet the value of the knowledge to be gained from probing the brain is too valuable to ignore. So we’ll get over whatever squeamishness remains.
As I was saying, we start by freezing a dead brain. This is not a new concept—Dr. E. Fuller Torrey, a former supervisor at the National Institute of Mental Health and now head of the mental health branch of a private research foundation, has 44 freezers filled with 226 frozen brains.21 Torrey and his associates hope to gain insight into the causes of schizophrenia, so all of his brains are of deceased schizophrenic patients, which is probably not ideal for our purposes.
We examine one brain layer—one very thin slice—at a time. With suitably sensitive two-dimensional scanning equipment we should be able to see every neuron and every connection represented in each synapse-thin layer. When a layer has been examined and the requisite data stored, it can be scraped away to reveal the next slice. This information can be stored and assembled into a giant three-dimensional model of the brain’s wiring and neural topology
It would be better if the frozen brains were not already dead long before freezing. A dead brain will reveal a lot about living brains, but it is clearly not the ideal laboratory. Some of that deadness is bound to reflect itself in a deterioration of its neural structure. We probably don’t want to base our designs for intelligent machines on dead brains. We are likely to be able to take advantage of people who, facing imminent death, will permit their brains to be destructively scanned just slightly before rather than slightly after their brains would have stopped functioning on their own. Recently, a condemned killer allowed his brain and body to be scanned and you can access all 10 billion bytes of him on the Internet at the Center for Human Simulation’s “Visible Human Project” web site.22 There’s an even higher resolution 25-billion-byte female companion on the site as well. Although the scan of this couple is not high enough resolution for the scenario envisioned here, it’s an example of donating one’s brain for reverse engineering. Of course we may not want to base our templates of machine intelligence on the brain of a convicted killer, anyway
Easier to talk about are the emerging noninvasive means of scanning our brains. I began with the more invasive scenario above because it is technically much easier. We have in fact the means to conduct a destructive scan today (although not yet the bandwidth to scan the entire brain in a reasonable amount of time). In terms of noninvasive scanning, high-speed, high-resolution magnetic resonance imaging (MRI) scanners are already able to view individual somas (neuron cell bodies) without disturbing the living tissue being scanned. More powerful MRIs are being developed that will be capable of scanning individual nerve fibers that are only ten microns (millionths of a meter) in diameter. These will be available during the first decade of the twenty-first century. Eventually we will be able to scan the presynaptic vesicles that are the site of human learning.
We can peer inside someone’s brain today with MRI scanners, which are increasing their resolution with each new generation of this technology. There are a number of technical challenges in accomplishing this, including achieving suitable resolution, bandwidth (that is, speed of transmission), lack of vibration, and safety. For a variety of reasons it is easier to scan the brain of someone recently deceased than of someone still living. (It is easier to get someone deceased to sit still, for one thing.) But noninvasively scanning a living brain will ultimately become feasible as MRI and other scanning technologies continue to improve in resolution and speed.
A new scanning technology called optical imaging, developed by Professor Amiram Grinvald at Israel’s Weizmann Institute, is capable of significantly higher resolution than MRI. Like MRI, it is based on the interaction between electrical activity in the neurons and blood circulation in the capillaries feeding the neurons. Grinvald’s device is capable of resolving features smaller than fifty microns, and can operate in real time, thus enabling scientists to view the firing of individual neurons. Grinvald and researchers at Germany’s Max Planck Institute were struck by the remarkable regularity of the patterns of neural firing when the brain was engaged in processing visual information.23 One of the researchers, Dr. Mark Hübener, commented that “our maps of the working brain are so orderly they resemble the street map of Manhattan rather than, say, of a medieval European town.” Grinvald, Hübener, and their associates were able to use their brain scanner to distinguish between sets of neurons responsible for perception of depth, shape, and color. As these neurons interact with one another, the resulting pattern of neural firings resembles elaborately linked mosaics. From the scans, it was possible for the researchers to see how the neurons were feeding information to each other. For example, they noted that the depth perception neurons were arranged in parallel columns, providing information to the shape-detecting neurons that formed more elaborate pinwheel-like patterns. Currently, the Grinvald scanning technology is only able to image a thin slice of the brain near its surface, but the Weizmann Institute is working on refinements that will extend its three-dimensional capability. Grinvald’s scanning technology is also being used to boost the resolution of MRI scanning. A recent finding that near-infrared light can pass through the skull is also fueling excitement about the ability of optical imaging as a high-resolution method of brain scanning.
The driving force behind the rapidly improving capability of noninvasive scanning technologies such as MRI is again the Law of Accelerating Returns, because it requires massive computational ability to build the high-resolution, three-dimensional images from the raw magnetic resonance patterns that an MRI scanner produces. The exponentially increasing computational ability provided by the Law of Accelerating Returns (and for another fifteen to twenty years, Moore’s Law) will enable us to continue to rapidly improve the resolution and speed of these noninvasive scanning technologies.
Mapping the human brain synapse by synapse may seem like a daunting effort, but so did the Human Genome Project, an effort to map all human genes, when it was launched in 1991. Although the bulk of the human genetic code has still not been decoded, there is confidence at the nine American Genome Sequencing Centers that the task will be completed, if not by 2005, then at least within a few years of that target date. Recently, a new private venture with funding from Perkin-Elmer has announced plans to sequence the entire human genome by the year 2001. As I noted above, the pace of the human genome scan was extremely slow in its early years, and has picked up speed with improved technology, particularly computer programs that identify the useful genetic information. The researchers are counting on further improvements in their gene-hunting computer programs to meet their deadline. The same will be true of the human-brain-mapping project, as our methods of scanning and recording the 100 trillion neural connections pick up speed from the Law of Accelerating Returns
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What to Do with the Information
There are two scenarios for using the results of detailed brain scans. The most immediate—scanning the brain to understand it—is to scan portions of the brain to ascertain the architecture and implicit algorithms of interneuronal connections in different regions. The exact position of each and every nerve fiber is not as important as the overall pattern. With this information we can design simulated neural nets that operate similarly. This process will be rather like peeling an onion as each layer of human intelligence is revealed.
This is essentially what Synaptics has done in its chip that mimics mammalian neural-image processing. This is also what Grinvald, Hübener, and their associates plan to do with their visual-cortex scans. And there are dozens of other contemporary projects designed to scan portions of the brain and apply the resulting insights to the design of intelligent systems.
Within a region, the brain’s circuitry is highly repetitive, so only a small portion of a region needs to be fully scanned. The computationally relevant activity of a neuron or group of neurons is sufficiently straightforward that we can understand and model these methods by examining them. Once the structure and topology of the neurons, the organization of the interneuronal wiring, and the sequence of neural firing in a region have been observed, recorded, and analyzed, it becomes feasible to reverse engineer that region’s parallel algorithms. After the algorithms of a region are understood, they can be refined and extended prior to being implemented in synthetic neural equivalents. The methods can certainly be greatly sped up given that electronics is already more than a million times faster than neural circuitry.
We can combine the revealed algorithms with the methods for building intelligent machines that we already understand. We can also discard aspects of human computing that may not be useful in a machine. Of course, we’ll have to be careful that we don’t throw the baby out with the bathwater.
Downloading Your Mind to Your Personal Computer
A more challenging but also ultimately feasible scenario will be to scan someone’s brain to map the locations, interconnections, and contents of the somas, axons, dendrites, presynaptic vesicles, and other neural components. Its entire organization could then be re-created on a neural computer of sufficient capacity, including the contents of its memory.
This is harder in an obvious way than the scanning-the-brain-to-understand-it scenario. In the former, we need only sample each region until we understand the salient algorithms. We can then combine those insights with knowledge we already have. In this—scanning the brain to download it—scenario, we need to capture every little detail. On the other hand, we don’t need to understand all of it; we need only to literally copy it, connection by connection, synapse by synapse, neurotransmitter by neurotransmitter. It requires us to understand local brain processes, but not necessarily the brain’s global organization, at least not in full. It is likely that by the time we can do this, we will understand much of it, anyway.
To do this right, we do need to understand what the salient information-processing mechanisms are. Much of a neuron’s elaborate structure exists to support its own structural integrity and life processes,and does not directly contribute to its handling of information. We know that neuron-computing processing is based on hundreds of different neurotransmitters and that different neural mechanisms in different regions allow for different types of computing. The early vision neurons, for example, are good at accentuating sudden color changes to facilitate finding the edges of objects. Hippocampus neurons are likely to have structures for enhancing the long-term retention of memories. We also know that neurons use a combination of digital and analog computing that needs to be accurately modeled. We need to identify structures capable of quantum computing, if any All of the key features that affect information processing need to be recognized if we are to copy them accurately.
How well will this work? Of course, like any new technology, it won’t be perfect at first, and initial downloads will be somewhat imprecise. Small imperfections won’t necessarily be immediately noticeable because people are always changing to some degree. As our understanding of the mechanisms of the brain improves and our ability to accurately and noninvasively scan these features improves, reinstantiating (reinstalling) a person’s brain should alter a person’s mind no more than it changes from day to day
What Will We Find When We Do This?
We have to consider this question on both the objective and subjective levels. “Objective” means everyone except me, so let’s start with that. Objectively, when we scan someone’s brain and reinstantiate their personal mind file into a suitable computing medium, the newly emergent “person” will appear to other observers to have very much the same personality, history, and memory as the person originally scanned. Interacting with the newly instantiated person will feel like interacting with the original person. The new person will claim to be that same old person and will have a memory of having been that person, having grown up in Brooklyn, having walked into a scanner here, and woken up in the machine there. He’ll say, “Hey, this technology really works.”
There is the small matter of the “new person’s” body. What kind of body will a reinstantiated personal mind file have: the original human body, an upgraded body, a synthetic body, a nanoengineered body, a virtual body in a virtual environment? This is an important question, which I will discuss in the next chapter.
Subjectively, the question is more subtle and profound. Is this the same consciousness as the person we just scanned? As we saw in chapter 3, there are strong arguments on both sides. The position that fundamentally we are our “pattern” (because our particles are always changing) would argue that this new person is the same because their patterns are essentially identical. The counter argument, however, is the possible continued existence of the person who was originally scanned. If he—Jack—is still around, he will convincingly claim to represent the continuity of his consciousness. He may not be satisfied to let his mental clone carry on in his stead. We’ll keep bumping into this issue as we explore the twenty-first century.
But once over the divide, the new person will certainly think that he was the original person. There will be no ambivalence in his mind as to whether or not he committed suicide when he agreed to be transferred into a new computing substrate leaving his old slow carbon-based neural-computing machinery behind. To the extent that he wonders at all whether or not he is really the same person that he thinks he is, he’ll be glad that his old self took the plunge, because otherwise he wouldn’t exist.
Is he—the newly installed mind—conscious? He certainly will claim to be. And being a lot more capable than his old neural self, he’ll be persuasive and effective in his position. We’ll believe him. He’ll get mad if we don’t.
A Growing Trend
In the second half of the twenty-first century, there will be a growing trend toward making this leap. Initially, there will be partial porting—replacing aging memory circuits, extending pattern-recognition and reasoning circuits through neural implants. Ultimately, and well before the twenty-first century is completed, people will port their entire mind file to the new thinking technology.
There will be nostalgia for our humble carbon-based roots, but there is nostalgia for vinyl records also. Ultimately, we did copy most of that analog music to the more flexible and capable world of transferable digital information. The leap to port our minds to a more capable computing medium will happen gradually but inexorably nonetheless.
As we port ourselves, we will also vastly extend ourselves. Remember that $1,000 of computing in 2060 will have the computational capacity of a trillion human brains. So we might as well multiply memory a trillion fold, greatly extend recognition and reasoning abilities, and plug ourselves into the pervasive wireless-communications network. While we are at it, we can add all human knowledge—as a readily accessible internal database as well as already processed and learned knowledge using the human type of d
istributed understanding.
THE AGE OF NEURAL IMPLANTS HAS ALREADY STARTED
The patients are wheeled in on stretchers. Suffering from an advanced stage of Parkinson’s disease, they are like statues, their muscles frozen, their bodies and faces totally immobile. Then in a dramatic demonstration at a French clinic, the doctor in charge throws an electrical switch. The patients suddenly come to life, get up, walk around, and calmly and expressively describe how they have overcome their debilitating symptoms. This is the dramatic result of a new neural implant therapy that is approved in Europe, and still awaits FDA approval in the United States.
The diminished levels of the neurotransmitter dopamine in a Parkinson’s patient causes overactivation of two tiny regions in the brain: the ventral posterior nucleus and the subthalmic nucleus. This overactivation in turn causes the slowness, stiffness, and gait difficulties of the disease, and ultimately results in total paralysis and death. Dr. A. L. Benebid, a French physician at Fourier University in Grenoble, discovered that stimulating these regions with a permanently implanted electrode paradoxically inhibits these overactive regions and reverses the symptoms. The electrodes are wired to a small electronic control unit placed in the patient’s chest. Through radio signals, the unit can be programmed, even turned on and off. When switched off, the symptoms immediately return. The treatment has the promise of controlling the most devastating symptoms of the disease.24
