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In the Age of Spiritual Machines

Ray Kurzweil

Once, the Earth was ensconced by an ocean of nothing, a vast wasteland of “molecular soup.” It was the union of these molecules, however that soon filled that sea with what we now refer to as life. Deep within the single-celled organisms which began to populate the planet was a very basic program which soon learned to replicate itself. It then began creating more cells, and more still. In time, the program developed to adjust the full being to its surroundings, making small steps from generation to generation. It wasn t until several billion years later, when beings which functioned on the code were able to figure it out. Around the same time, these beings began to create technology which was superior to their own code. These beings were intelligent and emotional, and from that grew the aspiration to function at higher levels. Soon their machines grew intelligent and emotional. All of a sudden — relative to the preceding aeon — the code had been rendered obsolete by the species.

This examination will explore the arguments contained in Ray Kurzweil s book, The Age of Spiritual Machines. Artificial Intelligence is an emerging topic of debate; with every day it appears closer to reality. Today, machines aid us in many ways, from assisting the handicapped, to presenting films, to writing this paper. But as much as computers assist us, they are completely dependent on us for guidance, i.e. programming. On the flip side, computers are no longer just helping us, but now are giving us answers to questions we have sought for centuries. I will discuss the emerging and established fields of programming and advances, and how in the future it might relate to us as spiritual and ethical human beings. Most importantly, I will hope to answer the question, “when artificial intelligence comes, will we continue to teach and serve computers or will computers teach and serve us?”

Kurzweil, who, according to examples presented in his book, has an excellent track record when it comes to predicting the course of technology, proposes that the first two decades of the 21st century will bear witness to more technological achievements than in the whole of the 20th Century. Computers will continue on the path that became clear in the 90 s. Eventually, they will become fused into every facet of human life. Every student will sit at a computer rather than a static desk; tangible media will become obsolete, for movies, music, software, and even television will be purchasable and downloaded over the internet; doctors will be able to perform microsurgery from the other side of the globe; even virtual reality will serve a purpose. It seems that the idyllic future showcased in the more optimistic science fiction films will in fact come to pass. The underpinnings of human society will still be there: our desires for entertainment, love, and acquisition will remain, but as the century progresses, they will appear to become optional. And while the vast majority of social human existence benefits from the commonplace of computers, behind the scenes, a technological movement begun in this century will propose to change the purpose of computers from devices that aid us in daily life to devices that are our life.

Since the inception of automated computers, a universal goal of developers has been the realization of a machine that would absorb a vast amount of information, then ask why? . Personal computers today are abundant enough for us to see that they amass information, but only to tell us how right or wrong it is (zeroes and ones). Currently, there are three forms of advanced computing used to do this: Recursive Formula, Neural Nets, and Evolutionary Algorithms s.

The first, Recursive Formula, the formula by which IBM s Deep Blue — the computer that defeated human champion Garry Kasparov at chess — is run, creates a “tree of possibilities.” In the context of chess, the computer examines the board and consults its database of possible moves. It looks ahead a half a move at possible moves made by its opponent after its own possible move, limited only by the speed of the computer, which is dramatically faster than the human brain. When it sees that the next half-move is mutually damaging, it reaches a “termination leaf,” understanding that either it has won or lost.

Of course, the limitation of such a routine is its inability to discriminate, to find patterns, and to know which branches he should ignore altogether. While Deep Blue has trumped human-kind at it’s game, he has done so through a very unhuman process. That doesn’t make it any less of a defeat, but realizing that helps to put it in context. Let me elaborate. Deep Blue was meticulously programmed how to choose a path at each branch in the road. Presented with a slightly different or new situation, it would be unable to adapt. Change the rules a bit, and Deep Blue is helpless. That is where the next form of processing takes over.

This second form of advanced processing is the Neural Net. As its name would indicate, it is based upon the neuron operations that occur in the human brain. A Neural Net is comprised of simulated software or hardware neurons that are randomly assigned elements of an input such as a picture. Kurzweil uses the example of a banking machine that can identify a human face: like the human brain, it remembers different parts of a person s face in each of neurons. Since we use human brains, we do not remember an acquaintance s appearance in one lump area of the brain; our memories are randomly dispersed (in the case of visual memory the brain randomly stores color, shape, detail, etc.) to access that information by bringing it together upon input, or seeing the acquaintance. The computer recognizes a person s face when each neuron with the familiar information fires and triggers an output neuron on top of it. The output neuron then gives the command to display “This is James Bond, Agent 007.” What separates Neural Nets from say, a disparate Recursive system, is that it is not programmed in a linear fashion. Instead the Neural Net is taught and conditioned. When it is introduced to the face, it remembers the information in arbitrary neurons and then remembers that the information is to be associated with James Bond. If the face is presented again, and the information returned is false, then the net is conditioned to respond more efficiently the next time. The neurons which fired more accurate detail are strengthened, while the neurons which reported incorrect data are weakened.

The third and most efficient form of automated problem-solving is the Evolutionary Algorithm . In Junior High School, we learned in algebra that we could solve the equation “6 + x = 10″ could be solved by subtracting six from either side and arriving at the answer “x = 4.” Eventually, we learned more complex reasoning. The Evolutionary Algorithm is used when there are problems with hundreds of variables, possibilities with different outcomes, that would take long expanses of time and many human hands to arrive at the best possible outcome. It is a simulated software organism. Kurzweil draws an example from a computer using an Evolutionary algorithm to invest in stocks. A group of simulated software organisms are fed data and statistics reflecting the behavior and fluctuations of the market and the stock. The organisms then hypothetically invest. Each organism is programmed to have a different mode of operation when playing the market. The organisms that underperform are killed off, and the ones that succeed evolve to the next level, sharing their better traits amongst them. Eventually, we get generation after generation of increasingly better investors. The applications of Evolutionary algorithms are more widespread than we might think, ranging from thumb print identification, to the designs of jet engines, to even the nanokernels which our computer operating systems are based on.

Although all three of these technologies are incredible achievements for humans, they are just that: achievements for humans. Despite the massive amounts of information that computers learn and calculate, the learning process must be programmed by an external source. Kurzweil defines intelligence as “the ability to to use optimally limited resources, including time, to achieve a variety of goals.” If this holds true, then yes, we might able able to classify modern machines as intelligent. They do manipulate the very scarce resources they are given in order to arrive at certain goals. However, the computers do not set these goals themselves. We do. Though computers serve us in a variety of ways, we are still ultimately subservient to them: we give them existence (existence being functional operation alone) and we are quite meticulous about programming the means to their goals. The next step in the evolution of technology would be for machines to ponder their actions. To achieve this process, we must look at the hardware and software that we use 24 hours a day, 7 days a week, our brains. The integrated chips that we use on our computers calculate thousands, even millions of times faster than we can think, but in comparison to our brains, it is that much simpler. The brain is structured in three dimensions, in a highly connected, rather than serial, network, and has functions which, if replicated in a computer, would seem like science fiction. But according to Kurzweil, it is not. Kurzweil says that the coming century will see advances in the non-invasive scanning of living brain tissue, giving scientists the ability to map all the functions of the mind and programmers the ability to replicate it. The Neural Net was a start; successfully imitating the fundamentals behind the operation of the brain gives us the hope that a successful imitation of the entire human brain is an attainable goal. A computer running on a hardware replica of the human brain would not only ask “why,” but would also show preference, feel emotions, and have spiritual experiences. All of these characteristically human traits are all attributed to parts of the brain.

The next question is, “once we have attained the level of technological achievement where we have machines that think and act much like we do, how do we coexist?” There will be serious ethical problems rising from this new era; we will assume that these computers are telling the truth when they claim to be lucid, emotional beings. Would it be ethical to pull their plug if we get mad at them? Hack into their fantasies? Remove certain hardware or software features — lobotomize them — if they get too excited? Kurzweil believe that when A.I. is abundant enough, it will merge with humankind — literally. Biological evolution, Kurzweil says, is at an impasse. Any headway to be made by the human subspecies would take eons. DNA, regardless of the fact that it is a wondrous machine in our current paradigm, cannot trash an entire design and start from scratch. Steve Jobs, the interim CEO of Apple Computer was dissatisfied with the line of Macintosh computers in 1997 when he returned to the company. The next year, he unveiled a completely new — restructured both architecturally and aesthetically — line of Macs that proved to be some of the more successful computer models sold. This is the advantage of the fact that we control the course of technology. If an evolving technology hits a stalemate, then it should be rethought when its usage becomes archaic. To use the analogy of Apple Computer again, our current bodies are the clunky beige PowerPC 604-based Macs that were being outsold by Pentium machines and threatening Steve Jobs with unemployment. The prospect of integrating our bodies with the technology we created is like a colorful iMac or G3 that outsells and outperforms most Windows-based machines.

There are several ways in which we can integrate ourselves with machines, cybernetic implants, full neural download, and cellular nanotechnology. The first is very much in use today, though not a full implementation. A man in Scotland who lost his arm has a fully functional mechanical arm which responds to the movements of muscles in his shoulder; a chip based on evolutionary algorithms can process light and be embedded in the back of the retina to restore sight to the blind. The list of these sorts of achievements is endless. Some of Kurzweil s own innovations even aided in the development of these devices. By 2029, Kurzweil predicts, neural implants will become an accepted, though likely by that time not widespread, practice. These things all serve to better our perception and functions while retaining our current biological makeup.

Full Neural Download is perhaps the most radical integration. It also raises the most moral and ethical questions. Imagine that you want to move your favorite MP3 music file from your old computer to your new one via Zip Disk. In order to do so, you need to copy the file from the hard drive onto the disk, then onto the new hard drive. Each time you are replicating the file; it continues to have the exact same functionality on the Zip disk as it does on the hard disk, but not only is it a copy, but most likely a copy many generations old originating on someone s computer then propagating through the internet. A Neural Download would entail a similar process: you would completely download your brain into a Neural Net, causing a duplicate consciousness of yourself to be created. On the personal level, this would cause some frustration. Both the original human and the digital clone would claim to be the same person. All their memories, emotions, and perceptions would be identical. This process would not work if a dying man wanted to live: though the copy would rejoice that he has been saved, the original man would find himself in heaven or hell, rather perturbed that the process failed, unaware that his replicant has been installed in a cybernetic body and is conducting business as usual. But on the other hand, every single atom in your body is dfferent than the ones you had five years ago. So maybe you’re not really the same person. Maybe you just think you’re the same person. The point of the question is to show that maybe we’ll never answer that question but we’ll believe it to be irrelevant.

On the evolutionary level, however, this is a positive thing. If all x billion of Earth s inhabitants downloaded their brains before a flash virus wipes them all out, the human race could extend their existence as a race of machines; completely nonorganic, but retaining the drive and spirit of humanity. The Neural Download will also mean that we can service and improve our software and hardware during our (perhaps infinite) lifetimes. Physical mechanical bodies capable of manipulating the environment like we have done for millions of years will ensure that when the hardware parameters improve, we can update ourselves. And unlike John Perry s fear that if we move from body to body, our perceptions as a spirit will not be able to jive with the new set of instructions in the new body, we will be able to update our software to deal with the advancing technology.

Since, despite superficiality, we seem to like our bodies, an alternative to Neural Download is Cellular Nanotechnology. In its early stages today, nanotechnology is the creation of working machines that are only a few microns in size. Conceivably, if DNA is only a software code — and Kurzweil contests that it will be fully unraveled by 2009 — surely nanomachines could conceivably be able to replicate DNA functions, and improve it. They could create new cells containing more nanomachines that replace the old DNA-Based ones. Nanomachines acting as DNA would be able to finely tune and improve every function of the body, including the brain, gradually restructuring neurons to be faster, sharper, and better.

But that brings up another issue. When we’re at this point of manipulating and changing our bodies and brains on at the scale of a nanometer, then essentially what is the difference between living and mechanical? Organic, by definition, means to contain carbon, hydrogen and oxygen. So suppose we can manipulate our bodies through nanotechnology to gradually yield a fully inorganic being. Would that be drastically different than remaining an organic species? Would that steal our soul? Maybe it isn’t really different than a neural download into another machine.

Naturally, the latter two have their share of drawbacks. Nanomachines, besides being a very complex process, could also malfunction or be used as viruses, breaking down the cells and eventually the body. Viruses could be introduced into a Neural Net, crippling the individual, or even an entire network of individuals.

To use a basic analogy of the Evolutionary Algorithm again, we program the computer, ask a question, and it retrieves the answer for us. An Evolutionary Algorithm or even a Recursive Formula computer could conceivably run for public office and map out political strategies to optimize its jurisdiction. But as humans, we seem to enjoy the politician who walks through the street to kiss babies, because he is warm and unpredictable. And we don t need computers as much as we think we do anyway. We got along fine without them for centuries. But then again, we want so much more out of the world that cannot be done without their help. Soon, we will understand the full scope of their abilities when they get up and talk to us. They will relate to us, confide in us, and we will them. We will fall in love with them, and as in any union of true love, we will want to merge with them. If Ray Kurzweil s roadmap of the 21st Century proves to be accurate, man and machine will become one, feeling and appreciating experiences while functioning with speed and flexibility. All our dreams will be realized, and all our new perceptions will deliver us new ones. The machine is merely an extension of humanity; soon we will learn that it is no more removed from us than a part of the body.

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