|
|
My subject here is the philosophy of Internet AI engineering: the general ideas that must be understood in order to create intelligent computer programs in the Internet medium. Only a few of these ideas are of my invention; this is a body of knowledge that has emerged from the community of computer scientists, engineers, complexity scientists and associated thinkers over the last few decades. But I believe I have filled in a few crucial gaps.
This is not a traditional "AI philosophy" book. I take it for granted here that computer programs can have minds, if they are designed correctly. And I take it for granted that computer programs can be conscious -- ignoring the "problem" of computer consciousness just as I ignore the "problem" of human consciousness every day, as I interact with other humans. The reader who is interested to know my views on these matters can consult my previous publications.
I firmly believe that, by fleshing out and implementing the ideas given here, over the next decade, we will be able to create Internet-based AI programs that surpass human beings in general intelligence. Some of our expectations about AI will be remain unfulfilled -- for example, the Turing test, which requires a computer to simulate a human in conversation, is unlikely to be passed until we can engineer human-like bodies for our AI programs. But in other areas, our AI programs will exceed our expectations dramatically. Our understanding of the collective intelligence of the human race will be greatly enhanced by interaction with AI systems linked in to the collective data resources of the Internet.
Of course, I am aware that AI optimism has been proved wrong before -- AI pioneers of the 1950's and 60's predicted that true machine intelligence was right around the corner. But like optimism about human flight 150 years ago, AI optimism is bound to be proved right eventually. The AI theorists of the 50's and 60's lacked many the ideas needed to realize machine intelligence, but they also lacked adequate hardware. If they had had the needed machinery, they probably would have corrected their ideas in the iterative manner typical of empirical science. Now we have PC's with 4 gigabytes of RAM, mainframes with 100; and we have high-bandwidth network cable that can link an arbitrary number of computers together into a single computational process. Just barely, we have the firepower needed to implement a mind. The ideas in this book provide the key to making use of this firepower.
Part of the key to thinking about Internet AI correctly is placing AI in the correct context. Exciting things are happening in computing -- the Internet is more than just a way to send naked pictures of Pamela Andersen to your buddies in Chechnya. There is a new kind of computer science and computer technology brewing, one that focuses on self-organizing networks and emergent dynamics rather than algorithms and data structures (though algorithms and data structures will still be there, to be sure, just as the bit-level constructs of assembly-language were not vanquished by the advent of structured programming). Artificial intelligence is essential here, because humans don't have the time or the ability to deal with the glut of rapidly shifting information that modern networks bring. And the network computing revolution is essential, because mind and brain are necessarily networks. A non-network-based computing paradigm can never adequately support AI.
Java, the premier language of the new paradigm, is maturing into a central role in server-side network apps. Exciting new Java-derivative technologies like Objectspace Voyager are beginning to take off, and yet others like Jini and Javaspaces are waiting in the wings. Electronic commerce is beginning to become real, especially in the realm of business-to-business commerce; and online AI is finally picking up speed -- embedded in websites like Excite and barnesandnoble.com are sophisticated systems for learning and guessing user profiles. We are just a few years away from the situation where the various intelligent systems on the Net, like the ones inside Excite and barnesandnoble.com, are learning from each other rather than existing as islands of intelligence in a sea of inert text and data. The Internet, and the computing environment in general, is poised for the advent of real artificial intelligence. What is needed to make it happen is understanding on the part of the technical community -- understanding of how the network of mind emerges from the underlying network of computers.
For the last two years, since I founded the Silicon Alley start-up company Intelligenesis, I have been involved in building an internet-based AI system called Webmind, which exemplifies the methodologies of AI design to be discussed in the following pages. This project has been challenging and exciting, but has left me fairly little time to reflect on the general lessons and principles underlying the work I'm doing, and even less time to write down these lessons and principles systematically. This book synthesizes some of the ideas that I have had time to write about. Most of the chapters originated as informal articles, written to clarify ideas to myself and distributed informally to various e-mail co-workers and acquaintances; several pertain specifically to our work at Intelligenesis.
Chapter 1 reviews the network computing paradigm and its relevance to intelligence; Chapters 2 and 3 follow up on this by exploring the "mind as network" theme as it relates to the structure of the brain and the abstract structure of cognition. Chapter 4 presents a general philosophical framework for understanding Internet information space, beginning from philosopher Kent Palmer's four ontological categories: Pure Being (data), Process Being (programs), Hyper Being (network computing) and Wild Being (the next stage, emergent Internet intelligence; the origin of the term Wild Computing). Chapters 5 and 6 discuss Internet AI from two very different perspectives: economics and transpersonal consciousness (the World Wide Brain, encapsulating the essential patterns of the human "collective unconscious"). Chapters 7 and 8 introduce and discuss the Webmind network AI architecture that we are currently building at Intelligenesis Corp., a specific example of the new network AI paradigm. The full details of Webmind are not entered into here, but the architecture is painted in broad strokes, and it is indicated how Webmind has the potential to fulfill the promise of next-phase, emergent AI. Finally, Chapter 9 describes some ideas as to how a new agents communication protocol could allow a diverse population of intelligent network entities, including Webminds, to synergetically interact -- and hence form the practical infrastructure for a global brain.
This is a diverse body of thinking, and I have not attempted to force a false unity upon it. There is a real underlying coherence here, and I am too aware of its depth and profundity to want to obscure it under a glib, premature systematization. (As Nietzsche said, "The will to a system is a lack of integrity.") Instead, , the book mirrors its subject matter, in that the topics presented are not locked together into a rigid linear series, but represent rather nodes in a network, interrelating with each other in numerous complex ways. As the new computing develops, the pattern of interrelation between its various aspects will become clearer and more aesthetic. We are all part of this clarifying process.