Quentin Smith, “The Anthropic Principle and Many-Worlds Cosmologies,” Australasian Journal of Philosophy 63.3 (September 1985), available at http://www.qsmithwmu.com/the_anthropic_principle_and_many-worlds_cosmologies.htm.
10. See chapter 4 for a complete discussion of the brain’s self-organizing principles and the relationship of this principle of operation to pattern recognition.
11. With a “linear” plot (where all graph divisions are equal), it would be impossible to visualize all of the data (such as billions of years) in a limited space (such as a page of this book). A logarithmic (“log”) plot solves that by plotting the order of magnitude of the values rather than the actual values, allowing you to see a wider range of data.
12. Theodore Modis, professor at DUXX, Graduate School in Business Leadership in Monterrey, Mexico, attempted to develop a “precise mathematical law that governs the evolution of change and complexity in the Universe.” To research the pattern and history of these changes, he required an analytic data set of significant events where the events equate to major change. He did not want to rely solely on his own list, because of selection bias. Instead, he compiled thirteen multiple independent lists of major events in the history of biology and technology from these sources:
Carl Sagan, The Dragons of Eden: Speculations on the Evolution of Human Intelligence (New York: Ballantine Books, 1989). Exact dates provided by Modis.
American Museum of Natural History. Exact dates provided by Modis.
The data set “important events in the history of life” in the Encyclopaedia Britannica.
Educational Resources in Astronomy and Planetary Science (ERAPS), University of Arizona, http://ethel.as.arizona.edu/~collins/astro/subjects/evolve-26.html.
Paul D. Boyer, biochemist, winner of the 1997 Nobel Prize, private communication. Exact dates provided by Modis.
J. D. Barrow and J. Silk, “The Structure of the Early Universe,” Scientific American 242.4 (April 1980): 118–28.
J. Heidmann, Cosmic Odyssey: Observatoir de Paris, trans. Simon Mitton (Cambridge, U.K.: Cambridge University Press, 1989).
J. W. Schopf, ed., Major Events in the History of Life, symposium convened by the IGPP Center for the Study of Evolution and the Origin of Life, 1991 (Boston: Jones and Bartlett, 1991).
Phillip Tobias,“Major Events in the History of Mankind,” chap. 6 in Schopf, Major Events in the History of Life.
David Nelson, “Lecture on Molecular Evolution I,” http://drnelson.utmem.edu/evolution.html, and “Lecture Notes for Evolution II,” http://drnelson.utmem.edu/evolution2.html.
G. Burenhult, ed., The First Humans: Human Origins and History to 10,000 BC (San Francisco: HarperSanFrancisco, 1993).
D. Johanson and B. Edgar, From Lucy to Language (New York: Simon & Schuster, 1996).
R. Coren, The Evolutionary Trajectory: The Growth of Information in the History and Future of Earth, World Futures General Evolution Studies (Amsterdam: Gordon and Breach, 1998).
These lists date from the 1980s and 1990s, with most covering the known history of the universe, while three focus on the narrower period of hominoid evolution. The dates used by some of the older lists are imprecise, but it is the events themselves, and the relative locations of these events in history, that are of primary interest.
Modis then combined these lists to find clusters of major events, his “canonical milestones.” This resulted in 28 canonical milestones from the 203 milestone events in the lists. Modis also used another independent list by Coren as a check to see if it corroborated his methods. See T. Modis, “Forecasting the Growth of Complexity and Change,” Technological Forecasting and Social Change 69.4 (2002); http://ourworld.compuserve.com/homepages/tmodis/TedWEB.htm.
13. Modis notes that errors can arise from variations in the size of lists and from variations in dates assigned to events (see T. Modis, “The Limits of Complexity and Change,” The Futurist [May–June 2003], http://ourworld.compuserve.com/homepages/tmodis/Futurist.pdf). So he used clusters of dates to define his canonical milestones. A milestone represents an average, with known errors assumed to be the standard deviation. For events without multiple sources, he “arbitrarily assign[ed] the average error as error.” Modis also points out other sources of error—cases where precise dates are unknown or where there is the possibility of inappropriate assumption of equal importance for each data point—which are not caught in the standard deviation.
Note that Modis’s date of 54.6 million years ago for the dinosaur extinction is not far enough back.
14. Typical interneuronal reset times are on the order of five milliseconds, which allows for two hundred digital-controlled analog transactions per second. Even accounting for multiple nonlinearities in neuronal information processing, this is on the order of a million times slower than contemporary electronic circuits, which can switch in less than one nanosecond (see the analysis of computational capacity in chapter 2).
15. A new analysis by Los Alamos National Lab researchers of the relative concentrations of radioactive isotopes in the world’s only known natural nuclear reactor (at Oklo in Gabon, West Africa) has found a decrease in the fine-structure constant, or alpha (the speed of light is inversely proportional to alpha), over two billion years. That translates into a small increase in the speed of light, although this finding clearly needs to be confirmed. See “Speed of Light May Have Changed Recently,” New Scientist, June 30, 2004, http://www.newscientist.com/news/news.jsp?id=ns99996092. See also http://www.sciencedaily.com/releases/2005/05/050512120842.htm.
16. Stephen Hawking declared at a scientific conference in Dublin on July 21, 2004, that he had been wrong in a controversial assertion he made thirty years ago about black holes. He had said information about what had been swallowed by a black hole could never be retrieved from it. This would have been a violation of quantum theory, which says that information is preserved. “I’m sorry to disappoint science fiction fans, but if information is preserved there is no possibility of using black holes to travel to other universes,” he said. “If you jump into a black hole, your mass energy will be returned to our universe, but in a mangled form, which contains the information about what you were like, but in an unrecognizable state.” See Dennis Overbye, “About Those Fearsome Black Holes? Never Mind,” New York Times, July 22, 2004.
17. An event horizon is the outer boundary, or perimeter, of a spherical region surrounding the singularity (the black hole’s center, characterized by infinite density and pressure). Inside the event horizon, the effects of gravity are so strong that not even light can escape, although there is radiation emerging from the surface owing to quantum effects that cause particle-antiparticle pairs to form, with one of the pair being pulled into the black hole and the other being emitted as radiation (so-called Hawking radiation). This is the reason why these regions are called “black holes,” a term invented by Professor John Wheeler. Although black holes were originally predicted by German astrophysicist Kurt Schwarzschild in 1916 based on Einstein’s theory of general relativity, their existence at the centers of galaxies has only recently been experimentally demonstrated. For further reading, see Kimberly Weaver, “The Galactic Odd Couple,” http://www.scientificamerican.com, June 10, 2003; Jean-Pierre Lasota, “Unmasking Black Holes,” Scientific American (May 1999): 41–47; Stephen Hawking, A Brief History of Time: From the Big Bang to Black Holes (New York: Bantam, 1988).
18. Joel Smoller and Blake Temple, “Shock-Wave Cosmology Inside a Black Hole,” Proceedings of the National Academy of Sciences 100.20 (September 30, 2003): 11216–18.
19. Vernor Vinge, “First Word,” Omni (January 1983): 10.
20. Ray Kurzweil, The Age of Intelligent Machines (Cambridge, Mass.: MIT Press, 1989).
21. Hans Moravec, Mind Children: The Future of Robot and Human Intelligence (Cambridge, Mass.: Harvard University Press, 1988).
22. Vernor Vinge, “The Coming Technological Singularity: How to Survive in the Post-Human Era,” VISION-21 Symposium, sponsored by
the NASA Lewis Research Center and the Ohio Aerospace Institute, March 1993. The text is available at http://www.KurzweilAI.net/vingesing.
23. Ray Kurzweil, The Age of Spiritual Machines: When Computers Exceed Human Intelligence (New York: Viking, 1999).
24. Hans Moravec, Robot: Mere Machine to Transcendent Mind (New York: Oxford University Press, 1999).
25. Damien Broderick, two works: The Spike: Accelerating into the Unimaginable Future (Sydney, Australia: Reed Books, 1997) and The Spike: How Our Lives Are Being Transformed by Rapidly Advancing Technologies, rev. ed. (New York: Tor/Forge, 2001).
26. One of John Smart’s overviews, “What Is the Singularity,” can be found at http://www.KurzweilAI.net/meme/frame.html?main=/articles/art0133.html; for a collection of John Smart’s writings on technology acceleration, the Singularity, and related issues, see http://www.singularitywatch.com and http://www.Accelerating.org.
John Smart runs the “Accelerating Change” conference, which covers issues related to “artificial intelligence and intelligence amplification.” See http://www.accelerating.org/ac2005/index.html.
27. An emulation of the human brain running on an electronic system would run much faster than our biological brains. Although human brains benefit from massive parallelism (on the order of one hundred trillion interneuronal connections, all potentially operating simultaneously), the reset time of the connections is extremely slow compared to contemporary electronics.
28. See notes 20 and 21 in chapter 2.
29. See the appendix, “The Law of Accelerating Returns Revisited,” for a mathematical analysis of the exponential growth of information technology as it applies to the price-performance of computation.
30. In a 1950 paper published in Mind: A Quarterly Review of Psychology and Philosophy, the computer theoretician Alan Turing posed the famous questions “Can a machine think? If a computer could think, how could we tell?” The answer to the second question is the Turing test. As the test is currently defined, an expert committee interrogates a remote correspondent on a wide range of topics such as love, current events, mathematics, philosophy, and the correspondent’s personal history to determine whether the correspondent is a computer or a human. The Turing test is intended as a measure of human intelligence; failure to pass the test does not imply a lack of intelligence. Turing’s original article can be found at http://www.abelard.org/turpap/turpap.htm; see also the Stanford Encyclopedia of Philosophy, http://plato.stanford.edu/entries/turing-test, for a discussion of the test.
There is no set of tricks or algorithms that would allow a machine to pass a properly designed Turing test without actually possessing intelligence at a fully human level. Also see Ray Kurzweil, “A Wager on the Turing Test: Why I Think I Will Win,” http://www.KurzweilAI.net/turingwin.
31. See John H. Byrne, “Propagation of the Action Potential,” Neuroscience Online, https://oac22.hsc.uth.tmc.edu/courses/nba/s1/i3-1.html: “The propagation velocity of the action potentials in nerves can vary from 100 meters per second (580 miles per hour) to less than a tenth of a meter per second (0.6 miles per hour).”
Also see Kenneth R. Koehler, “The Action Potential,” http://www.rwc.uc.edu/koehler/biophys/4d.html: “The speed of propagation for mammalian motor neurons is 10–120 m/s, while for nonmyelinated sensory neurons it’s about 5–25 m/s (nonmyelinated neurons fire in a continuous fashion, without the jumps; ion leakage allows effectively complete circuits but slows the rate of propagation).”
32. A 2002 study published in Science highlighted the role of the beta-catenin protein in the horizontal expansion of the cerebral cortex in humans. This protein plays a key role in the folding and grooving of the surface of the cerebral cortex; it is this folding, in fact, that increases the surface area of this part of the brain and makes room for more neurons. Mice that overproduced the protein developed wrinkled, folded cerebral cortexes with substantially more surface area than the smooth, flat cerebral cortexes of control mice. Anjen Chenn and Christopher Walsh, “Regulation of Cerebral Cortical Size by Control of Cell Cycle Exit in Neural Precursors,” Science 297 (July 2002): 365–69.
A 2003 comparison of cerebral-cortex gene-expression profiles for humans, chimpanzees, and rhesus macaques showed a difference of expression in only ninety-one genes associated with brain organization and cognition. The study authors were surprised to find that 90 percent of these differences involved up-regulation (higher activity). See M. Cacares et al., “Elevated Gene Expression Levels Distinguish Human from Non-human Primate Brains,” Proceedings of the National Academy of Sciences 100.22 (October 28, 2003): 13030–35.
However, University of California–Irvine College of Medicine researchers have found that gray matter in specific regions in the brain is more related to IQ than is overall brain size and that only about 6 percent of all the gray matter in the brain appears related to IQ. The study also discovered that because these regions related to intelligence are located throughout the brain, a single “intelligence center,” such as the frontal lobe, is unlikely. See “Human Intelligence Determined by Volume and Location of Gray Matter Tissue in Brain,” University of California–Irvine news release (July 19, 2004), http://today.uci.edu/news/release_detail.asp?key=1187.
A 2004 study found that human nervous system genes displayed accelerated evolution compared with nonhuman primates and that all primates had accelerated evolution compared with other mammals. Steve Dorus et al., “Accelerated Evolution of Nervous System Genes in the Origin of Homo sapiens,” Cell 119 (December 29, 2004): 1027–40. In describing this finding, the lead researcher, Bruce Lahn, states, “Humans evolved their cognitive abilities not due to a few accidental mutations, but rather from an enormous number of mutations acquired through exceptionally intense selection favoring more complex cognitive abilities.” Catherine Gianaro, University of Chicago Chronicle 24.7 (January 6, 2005).
A single mutation to the muscle fiber gene MYH16 has been proposed as one change allowing humans to have much larger brains. The mutation made ancestral humans’ jaws weaker, so that humans did not require the brain-size limiting muscle anchors found in other great apes. Stedman et al., “Myosin Gene Mutation Correlates with Anatomical Changes in the Human Lineage,” Nature 428 (March 25, 2004): 415–18.
33. Robert A. Freitas Jr., “Exploratory Design in Medical Nanotechnology: A Mechanical Artificial Red Cell,” Artificial Cells, Blood Substitutes, and Immobil. Biotech. 26 (1998): 411–30; http://www.foresight.org/Nanomedicine/
Respirocytes.html; see also the Nanomedicine Art Gallery images (http://www.foresight.org/Nanomedicine/Gallery/Species/Respirocytes.html) and award-winning animation (http://www.phleschbubble.com/album/beyondhuman/
respirocyte01.htm) of the respirocytes.
34. Foglets are the conception of the nanotechnology pioneer and Rutgers professor J. Storrs Hall. Here is a snippet of his description: “Nanotechnology is based on the concept of tiny, self-replicating robots. The Utility Fog is a very simple extension of the idea: Suppose, instead of building the object you want atom by atom, the tiny robots [foglets] linked their arms together to form a solid mass in the shape of the object you wanted? Then, when you got tired of that avant-garde coffee table, the robots could simply shift around a little and you’d have an elegant Queen Anne piece instead.” J. Storrs Hall, “What I Want to Be When I Grow Up, Is a Cloud,” Extropy, Quarters 3 and 4, 1994. Published on KurzweilAI.net July 6, 2001: http://www.KurzweilAI.net/foglets. See also J. Storrs Hall, “Utility Fog: The Stuff That Dreams Are Made Of,” in Nanotechnology: Molecular Speculations on Global Abundance, B.C. Crandall, ed. (Cambridge, Mass.: MIT Press, 1996). Published on KurzweilAI.net July 5, 2001: http://www.KurzweilAI.net/utilityfog.
35. Sherry Turkle, ed., “Evocative Objects: Things We Think With,” forthcoming.
36. See the “Exponential Growth of Computing”figure in chapter 2 (p. 70). Projecting the double exponential growth of the price-performance of computation to the end of the twenty-first century, one thousand dollars’
worth of computation will provide 1060 calculations per second (cps). As we will discuss in chapter 2, three different analyses of the amount of computing required to functionally emulate the human brain result in an estimate of 1015 cps. A more conservative estimate, which assumes that it will be necessary to simulate all of the nonlinearities in every synapse and dendrite, results in an estimate of 1019 cps for neuromorphic emulation of the human brain. Even taking the more conservative figure, we get a figure of 1029 cps for the approximately 1010 humans. Thus, the 1060 cps that can be purchased for one thousand dollars circa 2099 will represent 1031 (ten million trillion trillion) human civilizations.
37. The invention of the power loom and the other textile automation machines of the early eighteenth century destroyed the livelihoods of the cottage industry of English weavers, who had passed down stable family businesses for hundreds of years. Economic power passed from the weaving families to the owners of the machines. As legend has it, a young and feebleminded boy named Ned Ludd broke two textile factory machines out of sheer clumsiness. From that point on, whenever factory equipment was found to have mysteriously been damaged, anyone suspected of foul play would say, “But Ned Ludd did it.” In 1812 the desperate weavers formed a secret society, an urban guerrilla army. They made threats and demands of factory owners, many of whom complied. When asked who their leader was, they replied, “Why, General Ned Ludd, of course.” Although the Luddites, as they became known, initially directed most of their violence against the machines, a series of bloody engagements erupted later that year. The tolerance of the Tory government for the Luddites ended, and the movement dissolved with the imprisonment and hanging of prominent members. Although they failed to create a sustained and viable movement, the Luddites have remained a powerful symbol of opposition to automation and technology.