Modern Humans T h e i r A f r i c a n O r i g i n a n d G lo b a l D i s p e r s a l
John F. Hoffecker
Chapter One INFORMATION, COMPLEXITY, AND HUMAN EVOLUTION
Why may we not say that all Automata (Engines that move themselves by springs and wheeles as doth a watch) have an artificiall life? —THOMAS HOBBES (1651)
As Charles Darwin observed in 1871, humans are “the most dominant animal that has ever appeared on the earth.”1 Their dominance is measured not by physical size or by numbers or total biomass, although the latter two are impressive. Rather, it is measured by their control of the environment. To begin with, humans have occupied virtually every terrestrial habitat on Earth, which is remarkable for a single species, especially because it was largely accomplished more than 45,000 years ago, when the direct ancestors of living humans first spread across much of the land surface of the planet. Moreover, by manipulating both its biotic and its abiotic components, humans have radically altered the environment to suit their own needs, exponentially increasing their numbers and suppressing or eliminating other life-forms along the way. Here, too, the process began more than 45,000 years ago, long before the emergence of the earliest civilizations. Humans’ control of the environment is based on their ability to manipulate objects and materials in complex ways (that is, to make and use complex artifacts). There is nothing remarkable about the capacity to move or modify physical objects and materials, which is widespread in the animal kingdom, but the level of complexity that underlies human technology is unique. Humans can translate a large body of information stored in the brain into a hierarchically organized “artifact” such as a set of winter clothing or a sailboat. The artifacts of humans may be designed with an autonomous function—a machine, such as a self-acting rabbit snare or
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a mechanical clock—that Thomas Hobbes described as “artificiall life” in 1651.2 Evolution: The Major Transitions The evolution of life on Earth, from its beginning more than 3 billion years ago, provides a perspective on the unique ability of humans to translate information from the brain to structure—including functioning structure—in the form of a complex artifact. As John Maynard Smith and Eörs Szathmáry observed, the evolution of living systems has been characterized by a series of “major transitions.” Each reflects a fundamental change in how information is stored, transmitted, and translated. An example is the transition from single-celled to multicellular organisms, which took place more than 1 billion years ago. And each transition represents a quantum jump to a new level of complexity with emergent properties.3 Maynard Smith and Szathmáry included humans on their list of major transitions in evolution.4 Humans store, transmit, and translate information in novel ways; moreover, the changes in information represented by humans pertain to information in the brain (or neuronal information) rather than information in the genes. Humans store and transmit neuronal information in the form of language. In fact, the units of language, which include sounds made with the vocal tract, as well as the imagined sounds of the vocal tract reproduced in the brain, are translated from neuronal information. They, too, may be considered a “complex artifact,” even when they are not being rendered in material form (for example, written words).5 And the units of language may be manipulated in hierarchically organized structures with many levels and subcomponents, analogous to a machine (or what Daniel Dennett described as a “virtual machine” in the head).6 The capacity of humans to translate neuronal information into material structure, including functioning structure, represents a major transition in evolution, and it parallels the translation of genetic information into functioning structure (living organisms). Some suggest that the earliest lifeforms were both information and structure or, more specifically, RNA acting as an enzyme (or a ribozyme).7 Even the simplest cells (prokaryotes) require the translation of genetic information into proteins and other functioning structures. True cells, or eukaryotes, which may have evolved
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FIGURE 1.1 The translation of information into structure: (a) the translation of genetic information into a functioning organism in the form of a cat; (b) the translation of information stored in the human brain into functioning structure in the form of a two-state machine, or automaton (rabbit snare made by the Tanaina [see box figure 4.3]). ([b] From Cornelius Osgood, The Ethnography of the Tanaina [New Haven, Conn.: Yale University Press, 1937], 93, fig. 20. Courtesy of Yale University Publications in Anthropology)
as early as 2 billion years ago, store and transmit a much larger quantity of genetic information than do prokaryotes. They became the basis for multicellular organisms and the metazoa, including vertebrates, which undergo a protracted process of development from a single fertilized eukaryotic cell that entails the translation of massive amounts of genetic information into functioning structure (figure 1.1).8 Evolution as Computation One way to look at evolution is as a form of computation. The evolutionary process contains all the basic elements of a computation: “input” (random changes and/or recombination of genetic information that is translated into organisms), “operations” or “defining functions” (natural selection of organisms), and “output” (changes in the genetic information and the organisms).9 At least some of the changes produce an organism that is
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better adapted (or exhibits a better “fit”) to its environment. And because the input reflects random events, evolution is a “nondeterministic”—even creative—computational process, constantly yielding what Darwin described as “endless forms most beautiful.”10 The immense variety is a consequence of the many hierarchical levels of living systems. The computations of the evolutionary process take place on several levels, however, and with more than one form of information.11 Each living species is a product of computation with genetic information that occurs on the level of the evolving lineage: the information and the organism evolve together—neither can evolve without the other—over time. Thanks to recent and remarkable developments in the recovery and analysis of ancient DNA (aDNA), we have a partial “fossil” record of both the information and the organismal structure to which it is translated (fossil plant and animal remains) in the course of development (figure 1.2a). Long ago, prokaryotes evolved a form of computation on the level of the organism that allows an individual to respond to unpredictable variations in its environment. Proteins in the cell wall of a prokaryote transmit chemical signals—a simple non-genetic form of information—about the presence of potential “food” sources or threats, and the organism responds by moving toward or away from whatever triggered the signal. Unlike the computations of an evolving lineage, the process is a deterministic one with a predictable outcome.12 The metazoa evolved a much more complex form of computation on the level of the organism, with a new type of information generated at the cellular level. Specialized eukaryotic nerve cells, or neurons, transmit and store information in the electrochemically charged structures (synapses) that connect one neuron with others. And, like the mutation and recombination of genetic information, metazoan development includes a randomizing process that renders computation with neuronal information nondeterministic and potentially creative (figure 1.2b). Humans are constantly performing creative computations with neuronal information, but they also use their power to translate neuronal information into material structure to create an entirely new level of evolutionary computation. By making machines, or automata, that function independently of a living organism, humans create nonliving structures that act like a simple organism and perform their own computations. A machine also contains all the basic elements of a computation: input (materials or
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FIGURE 1.2 Evolutionary computation on two levels: (a) computation on the level of the evolving lineage; (b) computation performed by the metazoan brain on the level of the individual organism. Humans have developed a new level of evolutionary computation in the form of automata. (Redrawn from John E. Mayfield, The Engine of Complexity: Evolution as Computation [New York: Columbia University Press, 2013], 143, fig. 5.3 [a], 253, fig. 10.1 [b])
information), operations or “transition functions,” and output (transformed materials or information).13 Unlike evolving lineages and metazoan brains, however, many machines do not compute with information, but with matter and energy, and most machines perform deterministic computations with predictable output. Machines are not confined to industrial or early
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civilizations, but have their origin among hunter-gatherer societies and probably date to more than 45,000 years ago. Language as Information Technology The unique ability of humans to translate neuronal information into structure also supports another novel form of computation both at and above the level of the organism: language. Humans compute with the units of language—spoken words or imagined words replayed in the brain—in a manner analogous to moving the beads of an abacus. The perceptible “objects” of language (words) are moved around in the “virtual machine” of the brain to compute the problems of everyday life, including the complex web of social relationships that most humans inhabit.14 Because words have referents that potentially lie outside the immediate spatial-temporal setting of the individual brain, the computations may be about the past or the future.15 Human language functions not only as a communication system but also as a computational system or, in the words of George Boole, an “instrument of reason.”16 Language represents the original information technology. And if language represents a virtual “technology” for computing with units of information in the form of spoken or imagined vocal sounds, it is apparent that humans also compute with the materials that are modified and combined into their artifacts. Before humans began designing their technology on paper with written symbols and diagrams, their artifacts reflected an unending process of trial and error with pieces of wood, stone, hide, and other materials. The units of technology—raw or cooked—were manipulated in the brain and the hands in a manner analogous to the computations of language. As a result, human technology acquired a character similar to that of language, with a potentially infinite variety of hierarchically structured combinations and recombinations of its material units (box 1.1). The Rise of the Super-Brain A major consequence of developing a system of computation from a system of communication is that two or more brains may compute the same problem (that is, may function as a super-brain).17 Humans collectively
BOX 1.1 Modern Humans and “Syntactic Technology” The technology of Homo sapiens is unique within the living world, and it differs in fundamental ways from the technology of all other animals. Because it is a product of the evolution of living systems, technology is logically defined in the context of evolutionary biology. It falls into two major categories: (1) appropriated “traits” and (2) redesigned environments. Many animals appropriate pieces of their surrounding environment to function as a trait they otherwise lack, and some animals modify these pieces of the environment to make them functional (for example, a chimpanzee stripping leaves off a twig to function as a termite-fishing stick).1 Many animals alter their environment to enhance their fitness in some way, such as a bird’s nest or a rodent’s burrow (and some animals, including humans, do both). Technology developed among the metazoa and, more specifically, among metazoans such as the cephalopods, insects, and chordates, which evolved both external functioning structures such as jaws and limbs, and a central nervous system to coordinate their functions. Humans are somewhat unusual in having evolved a specialized extremity—the paired hands, which are almost entirely devoted to manipulating pieces of the environment. This appears to be a consequence of a highly unusual locomotor adaptation among mammals—bipedalism—that probably evolved for reasons other than technological function (chapter 3). Humans also evolved a central nervous system with considerable memory-storage capacity and computational powers (which also probably evolved for reasons other than technological function). The features of modern human technology that render it unique lie in the role that information plays in both “appropriated traits” and redesigned environments. In both categories, humans evolved the capacity to translate information stored in the neuronal networks of the brain into the design of technological structures (artifacts and features). This capacity is analogous to the translation of genetic information into the functioning structure of an organism during its development, although the process of translation is very different. There are some examples of the translation of genetic information into technological structure. Some species of ant construct complex underground nests with hierarchically organized networks of tunnels and chambers. 2 And there may be rare examples of the translation of neuronal information into simple technological structure. Modern humans routinely translate neuronal information into complex, hierarchically organized artifacts and features, including those that function independently of the organism (that is, machines or automata). The technology of modern humans exhibits the same fundamental properties of syntactic language, which allows the rapid recombination of a set of finite elements (speech sounds) into a potentially infinite variety of hierarchically organized structures (sentences). 3 This property of language has been labeled “discrete infinity” by Noam Chomsky.4 Modern humans apply it to the recombination of material objects to generate a wide variety of artifacts and features. They recursively tinker with artifact and feature designs, creating novel combinations of the elements and innovative variations of both. A number of archaeologists have noted the similarities between the properties of syntactic language and the making of artifacts. 5 It is apparent, moreover, that humans actually compute with the components of artifacts and features in a manner analogous to that of computation with words or (continued)
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numbers. Innovative variations and novel combinations often are the result of creative or even random manipulations of raw materials (and/or modified pieces of the same) with the hands—and visually and tactilely coordinated feedback with neuronal networks in the brain. This is another unique feature of human technology; no other animal is known to compute with objects and materials as if they were symbols or a form of information. It also is apparent that—as in the case of language—many individual brains separated by space and time compute the same problems with the materials and objects (for example, how to construct a house). The computations are therefore collective, and the solutions arrived at by one group of people in space and time are almost certain to be modified by their descendants and neighbors. The collective character of human technological computation ensures a massive quantity of input and immense computational power (that is, super-brain function).6 The construction of machines or automata is another unique feature of human technology (and one that is confined to modern humans). The structural and functional complexity of such artifacts or devices is possible only with “syntactic technology,” which allows the translation of a complex design into a hierarchically organized structure with functions, such as a small-mammal trap. (The hierarchically structured products of language may provide a model for the machine.)7 Making an artifact that functions independently of the organism reflects a major step in the evolution of living systems. Machines or automata perform their own computations (that is, they possess all the elements of a computation) and thus represent a new level of evolutionary computation (beyond the lineage and individual organism).8 Because of the collective character of human technological computation, machine functions occur on a unique human social-cultural level that transcends individual organisms in space and time. 1. William McGrew, Chimpanzee Material Culture: Implications for Human Evolution (Cambridge: Cambridge University Press, 1992). 2. Bert Hölldobler and E. O. Wilson, The Super-Organism: The Beauty, Elegance, and Strangeness of Insect Societies (New York: Norton, 2009), 338–339. 3. See, for example, Ray Jackendoff, Foundations of Language: Brain, Meaning, Grammar, Evolution (Oxford: Oxford University Press, 2002); and Ray Jackendoff and Eva Wittenberg. “What You Can Say Without Syntax: A Hierarchy of Grammatical Complexity,” in Measuring Grammatical Complexity, ed. Frederick J. Newmeyer and Laurel B. Preston (Oxford: Oxford University Press, 2014), 65–82. 4. Marc Hauser, Noam Chomsky, and W. Tecumseh Fitch, “The Faculty of Language: What Is It, Who Has It, and How Did It Evolve?” Science 298 (2002): 1569–1579. 5. See, for example, André Leroi-Gourhan, Le Geste et la parole, vol. 1, Technique et langage (Paris: Albin Michel, 1964); and James Deetz, Invitation to Archaeology (Garden City, N.Y.: Natural History Press, 1967), 81–101. 6. John F. Hoffecker, “The Information Animal and the Super-brain,” Journal of Archaeological Method and Theory 20 (2013): 18–41. 7. Daniel C. Dennett, Consciousness Explained (Boston: Little, Brown, 1991), 210; Andy Clark, Being There: Putting Brain, Body, and World Together Again (Cambridge, Mass.: MIT Press, 1998), and Supersizing the Mind: Embodiment, Action, and Cognitive Extension (New York: Oxford University Press, 2011), 44–60. 8. John E. Mayfield, The Engine of Complexity: Evolution as Computation (New York: Columbia University Press, 2013).
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compute most of their technology, and it is difficult to think of an example—in any temporal or geographic context—of an artifact that is not the product of more than one human brain. In his book The Social Context of Innovation, Anthony F. C. Wallace described the contributions of multiple individuals to the development of the steam engine in seventeenth-century England.18 For a prehistoric setting, Grahame Clark reviewed changes in bow design during the Neolithic of northwestern Europe.19 Humans are not the only metazoans that evolved a super-brain (although they are the only metazoans that compute collectively over multiple generations). As the entomologist Thomas Seeley has shown, a honeybee colony collectively computes a new nest site by pooling and comparing information gathered by many individual bees.20 Collective computation among humans differs significantly from that among honeybees, however, because it is not based on kin selection (a high degree of genetic relatedness among the members of the colony). Collective computation among the members of a human social group is more likely to be competitive (even if the competition is subtle and masked with assurances that the computation is being performed for the common good). The social integration of the already enlarged human brain—each brain storing and transmitting billions of bits of information—underlies the immense computational power of even the smallest of socioeconomic formations (such as hunter-gatherer bands of 25 to 30 people). There is an analogy to the quantum jump in genome size in the transition from prokaryotes to eukaryotes, which significantly increased the computational power of eukaryotic lineages. The computations of the super-brain are nondeterministic and creative (with much random input). The output is stored among the individual brains and in the structures to which it is translated, as well as in a variety of other forms of external memory storage. The Evolution of Humans Humans evolved two specialized organs for the translation of information stored (and manipulated) in the brain into complex, hierarchically organized structures: the paired hands and the vocal tract. With the vocal tract, the neuronal information is translated into another form of information based on the “structures” of real or imagined sounds. (All forms
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of information have a physical basis: either matter or energy.)21 Both the specialized human hand and the vocal tract have deep roots in primate evolution. The early primates evolved nails in place of claws, reflecting the use of the extremities for grasping objects (including the branches of trees), and most primates employ their forelimbs for manipulation as well as locomotion. What the anatomist John Napier described as the “true hand” is confined to apes and humans, however.22 The true hand functions primarily as a manipulative organ. The extreme versatility of the human hand almost certainly is an (indirect?) consequence of bipedalism in early humans. The fully modern hand probably was present by 1.5 million years ago (that is, by the time humans were making hand axes).23 The vocal tract of living humans is characterized by the migration of the larynx (voice box) during infancy to a position in the neck that is low in comparison with that in apes. In this position, the larynx expands the size of the pharynx (vocal chamber), allowing humans to generate a wide range of sounds. But reconstructing the evolution of the vocal tract is difficult because it is composed of soft parts and cartilage, which do not preserve in the fossil record. Instead, skeletal features associated with vocal-tract anatomy and function are used to make inferences about the evolution of the larynx in early humans. Examples include the degree of flexure at the base of the cranium and the length of the neck (that is, size and number of cervical vertebrae).24 Also helpful is the comparative anatomy and behavior of living primates, which exhibit a wide range of vocal signals. Especially significant are the warning calls of various primates. Among vervet monkeys, each of three different calls has a specific predator referent (that is, the sounds are matched with meanings).25 The alarm calls of vervet monkeys suggest an evolutionary source for human language, but determining its presence or absence in the fossil record is problematic. In fact, given the uncertain relationship between the anatomy of the vocal tract and language (either might have evolved without the other), clues pertaining to other aspects of the language faculty ultimately may be more useful. One of them is the presence of Broca’s area in the endocast of an early Homo skull dated to about 1.7 million years ago.26 Another is evidence that the “critical learning period” for language acquisition in children27 may be a product of the delayed maturation process in more recent forms of Homo.28
Praise for Modern Humans
John F. Hoffecker is a fellow of the Institute of Arctic and Alpine Research at the University of Colorado, Boulder. He has conducted field research in Alaska and Eastern Europe and is the author of Desolate Landscapes: IceAge Settlement in Eastern Europe (2002); A Prehistory of the North: Human Settlement of the Higher Latitudes (2005); (with Scott A. Elias) Human Ecology of Beringia (Columbia, 2007); and Landscape of the Mind: Human Evolution and the Archaeology of Thought (Columbia, 2011).
“This is an exceptional book on an inherently interesting topic. Most students of human origins agree that fully modern humans represent the surviving tip of an evolutionary lineage that emerged in Africa, probably beginning at least 300,000 years ago. This was a time when other lineages, including the one that led to the Neanderthals, were evolving in Eurasia. Most specialists also agree that fully modern Africans expanded to Eurasia around 50,000 years ago, where they replaced and sometimes interbred with the Neanderthals and other non-modern people. Much has been written on the ‘Out-of-Africa’ dispersal, but now the emphasis is increasingly on indications that invading Africans acquired some genes from resident Eurasians. Fossils are then valued mostly for their ancient DNA and only incidentally for their form and geographic distribution, while relevant archaeological observations are completely ignored, even though they underlie the most plausible explanations for modern human success. John F. Hoffecker considers everything and ignores nothing, and his synthesis is extraordinary not only for its breadth but also for its clarity. Modern Humans will satisfy both curious lay readers and special-
HOFFECKER
Modern Humans Their African Origin and G lo b a l D i s p e r s aL
T h e i r A f r i c a n O r i g i n a n d G lo b a l D i s p e r s a l
John F. Hoffecker
Modern Humans is a vivid account of the most recent—and perhaps the most important— phase of human evolution: the appearance of anatomically modern people (Homo sapiens) in Africa less than half a million years ago and their later spread throughout the world. Leaving no stone unturned, John F. Hoffecker demonstrates that Homo sapiens represents a “major transition” in the evolution of living systems in terms of fundamental changes in the role of non-genetic information. Modern Humans synthesizes recent findings from genetics (including the rapidly growing body of ancient DNA), the human fossil record, and archaeology relating to the African origin and global dispersal of anatomically modern people. Hoffecker places humans in the broad context of the evolution of life, emphasizing the critical role of genetic and non-genetic forms of information in living systems as well as how changes in the storage, transmission, and translation of information underlie major transitions in evolution. He also draws on information and complexity theory to explain the emergence of Homo sapiens in Africa several hundred thousand years ago and the rapid and unprecedented spread of our species into a variety of environments in Australia and Eurasia, including the Arctic and Beringia, beginning between 75,000 and 60,000 years ago. This magisterial work will appeal to all with an interest in the ever-fascinating field of human evolution.
ists who seek a readily intelligible, authoritative update on where we came from.” Richard G. Klein, Anne T. and Robert M. Bass Professor in the School of Humanities and Sciences, Stanford University, and author of The Human Career: Human Biological and Cultural Origins, Third Edition
“Hoffecker has produced an exhaustively researched but highly accessible account of the evidence—from paleontology, archaeology, material culture, and genomics—for one of the greatest stories ever told: how, from an unremarkable origin in Africa, our species Homo sapiens began behaving in extraordinary and unprecedented ways, and rapidly took over the entire habitable world—with consequences with which we are still grappling. Modern Humans is an invaluable resource for anyone interested in how modern humans came to be the amazing creatures they are.” Ian Tattersall, Curator Emeritus, Division of Anthropology, American Museum of Natural History, and author of The Strange Case of the Rickety Cossack and Other Cautionary Tales from Human Evolution
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