The Myth of Artificial Intelligence

Collaboratively written with Steve Waite… [Gilder's Daily Prophecy] May 07, 2021 [UNSUBSCRIBE]( | [ARCHIVES]( External Advertisement It’s Happening [Jeff Brown blazer]( here—something tech expert Jeff Brown calls a “Convergence.” And it could be the most important financial event of your lifetime. [Click Here To Learn More.]( [Warning] Do you enjoy receiving Gilder's Daily Prophecy? Please [Click Here Now]( so we know to continue sending you Gilder's Daily Prophecy for free! The Myth of Artificial Intelligence [George Gilder]Dear Daily Prophecy Reader, The Daily Prophecy below was collaboratively written with one of my lead analysts, Steve Waite. If you want to know about AI, read this book. For several reasons — most of all because it shows how a supposedly futuristic reverence for artificial intelligence retards progress when it disparages our most irreplaceable resource for any future progress: our own human intelligence. -Peter Thiel Actually, Thiel wrote “denigrate” rather than “disparage,” but the AI spellcheckers changed it to the nonsensical “designates.” They did this in order to avoid the silly PC verbal nomenclatura banning any negative use of the Latin word for black. Although I agree that “denigrate” is infelicitous — it is typical of rote AI to replace its correct use to mean disparage with the completely different word designate. Hey, as virtual reality inventor Jaron Lanier put it in a hyperbole, “AI makes people stupid.” The Mystery of Intelligence Thiel’s blurb on the back cover of Erik Larson’s new book, The Myth of Artificial Intelligence: Why Computers Can’t Think the Way We Do, sums up with his typical concision a key point I made in both Life After Google and Gaming AI. The technology we call AI is caught in the deadly circularity of human minds denying the capabilities of the very human minds on which AI inexorably depends. Larson’s new book provides important insights into why this is true. As the computer scientist and author notes, there is no way for current AI to “evolve” general intelligence. He adds a weasel phrase — "absent a fundamental scientific discovery” — but mostly downplays existing scientific discoveries that bar coherent artificial thought. Our current knowledge of AI — derived from its early progenitors Kurt Godel, Alan Turing and Charles Sanders Peirce — ordains that no logical system can be complete, or provable within itself. As Larson explains, AI is inherently a logical system, like mathematics, dependent on outside “oracles” that, as Turing insisted, “cannot be a machine[s]” themselves. As such, AI inherits the dependence on Turing oracles or Godel axioms (originating with human minds), which cannot be part of the AI system itself. As I wrote in Gaming AI: “The need for an observer in quantum mechanics [Heisenberg uncertainty], repeats the need for an “interpretant” between object and symbol in Peirce’s triadic logic, the need for external axioms in Godel’s incompleteness theorem, the need for a non-mechanistic “oracle” in Turing machines, and the need in general for logical schemes to avoid self-referential loops, “such as using atoms and electrons to measure atoms and electrons in quantum theory.” The truth is, as Larson explains, the inferences that systems require for general intelligence — to understand a newspaper, or hold a basic conversation, or become a helpmeet like Rosie the Robot in The Jetsons — cannot be programmed, learned, or engineered with AI. AI can simulate conscious intelligence, but not achieve it. No algorithm exists for general intelligence. And, says Larson, we have good reason to be skeptical that such an algorithm will emerge through further effort on deep learning systems or any other approach, popular today. Larson argues that attaining general intelligence in AI will require a major scientific breakthrough. However, no one currently has the slightest idea what such a breakthrough would even look like, let alone the details of getting to it. The science of AI, notes Larson, has uncovered a very large mystery at the heart of intelligence — a mystery, he says, nobody has clue how to solve. To make progress toward general artificial intelligence, says Larson, we need a way to perform “abductive inference.” Let’s dive into that now… [Weird Federal rule could turn America on its head]( External Advertisement Reclusive Tech Investor Says: “Stop Buying Bitcoin” [bitcoin]( believes the market potential of a new crypto-based tech is 6x bigger than bitcoin… and most investors have no idea it exists. [Learn more here.]( [Why This Tech Titan REALLY Retired?]( Inference and Intelligence Collide People who want to pretend to comprehend something when they don’t have a clue often adopt the strategy of magical coinage: concocting a word to cover up a mystery. Inference, abductive or not, is the basic cognitive act for conscious intelligent minds. If a cognitive agent (a person, an AI system) is not intelligent, it will infer badly. Any system that infers at all must have some basic intelligence, observes Larson, because the very act of using what is known and what is observed to update beliefs is inescapably tied up with what we mean by intelligence. If an AI system is not inferring at all, it doesn’t deserve to be called AI. Inference depends on conjecture, on projecting futures and correcting counter-factual hypotheses. Although we might say that even a system that tags pictures of cats is inferring that what it “sees” is a cat, so the bar can be quite low. But a human identifying cats does not have to be trained on billions of examples. It is impossible, writes Larson, to get a joke or merely keep up with sundry happenings and communications in the world without some inference capability or other. Only inference gets us to new knowledge or belief. Our knowledge is always changing and getting updated. For AI researchers to lack theory of inference, says Larson, is akin to nuclear engineers beginning work on the nuclear bomb without first working out the details of fission reactions. “Knowledge” of Einstein’s equation e=mc squared is not enough. And knowledge of computational theory by AI enthusiasts isn’t, either — because the very question of confronting scientists working on AI is how computation can be converted into the proper range and types of inference exhibited by minds. Induction requires abduction as a first step, notes Larson, because we need to bring into observation some framework for making sense of what philosophers call sense-datum — raw experience, uninterpreted. Larson tells us that the philosopher, Charles Sanders Peirce, who is also pivotal to Gaming AI, understood the origins of abduction as a reaction to surprise: - The surprising fact, C, is observed. - But if S were true, C would be a matter of course. - Hence, there is reason to suspect that A is true. Surprises, says Larson, are out on the long tail of trouble for induction. As I have noted in my books and Prophecies, surprise is a hallmark both of Shannon information and of profits and loss in the capitalist system. Thus, surprisal (entropy) as the measure of information enables the application of information theory to the economics of surprising entrepreneurship. Abductive inference, argues Larson, requires vast repositories of commonsense knowledge. We don’t yet know how to imbue machines with such knowledge, and even if we figure this out in the future, we won’t know how to implement an abductive inference engine to make use of all the knowledge in real-time, in the real world — not, that is, without a major conceptual breakthrough in AI. Today’s Prophecy As I point out in Life After Google and Gaming AI, a computer is a symbol system and a symbol system does not know anything. Software symbols represent phenomena that have been perceived consciously — known — by the outside oracle or intelligence, usually the conscious programmer with his imagination and counter-factual faculties which can project or “conject” into the unknown future. Consciousness is crucial to thought. Consciousness does not emerge from thought as the AI theories assert. Consciousness is the source of thought. We’ll be discussing Larson’s important AI views in future Prophecies. Regards, [George Gilder] George Gilder Editor, Gilder's Daily Prophecy [Steve Waite] Steve Waite Senior Analyst, Gilder's Daily Prophecy Will Apple, LG, Samsung… Recall their 5G phones? [red button recall]( people with 5G phones are facing the harsh truth - their phones aren’t receiving 5G signals consistently… and keep slipping back to 4G. Even some of the latest and greatest smart phones are not immune to this 5G flaw. The good news is there is a breakthrough new technology that will work with 5G phones, 4G phones, and even outdated 3G phones. And it has advantages that 5G can never have. [To know more about what could arguably be the future of smart phones and internet, Click Here.]( [Three founders Publishing]( To end your Gilder's Daily Prophecy e-mail subscription and associated external offers sent from Gilder's Daily Prophecy, feel free to [click here](. 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