COMPUTING THE ODDS YOU’LL GET LAID or
BIRTH OF EVOLUTIONARY PSYCHOLOGY from
HANDBOOK OF EVOLUTIONARY PSYCHOLOGY
I hit pay dirt when through interlibrary loan I got hold of this thick, heavy volume, HANDBOOK OF EVOLUTIONARY PSYCHOLOGY, from the University of Idaho. I’ll never finish it in the three weeks I have, But this book is a text full of the details of the exciting new field of “evolutionary psychology”. Here’s where the future of knowledge is which is most important for human progress. It’s edited by David Buss, full of basic essays about the field, and is foreworded by Steven Pinker. At the time of this blog entry, I’ve now bought a copy of the book for myself on Amazon for $75 bucks and, now, as I make this posting, it's gone up to $79.99. This entry's a long one, folks, but it’s fascinating and detailed:
[OPEN QUOTE] For those eager to leap directly from theories of selection pressures to predictions of fitness maximization, there remains a missing level of causation and explanation: the informational or computational level. This level cannot be avoided if the application of Darwin's theory to humans is ever to achieve the necessary level of scientific precision. Natural selection does not operate on behavior per se; it operates on a systematically caused relationship between information and behavior. Running—a behavior—is neither good nor bad. Running away from a lion can promote survival and reproduction; running toward a lion will curtail both. To be adaptive, behavioral regulation needs to be functionally contingent on information; for example,flee when you see a stalking lion. But a systematic relationship between information and a behavioral response cannot occur unless some reliably developing piece of organic machinery causes it. These causal relations between information and behavior are created by neural circuits in the brain, which function as programs that process information. By altering the neural circuitry that develops, mutations can alter the information processing properties of these programs, creating alternative information-behavior relationships. Selection should retain or discard alternative circuit designs from a species' neural architecture on the basis of how well the information-behavior relationships they produce promote the propagation of the genetic bases of their designs. Those circuit designs that promote their own proliferation will be retained and spread, eventually becoming species-typical (or stably frequency-dependent); those that do not will eventually disappear from the population. The idea that the evolutionary causation of behavior would lead to rigid, inflexible behavior is the opposite of the truth: Evolved neural architectures are specifications of richly contingent systems for generating responses to informational inputs.
As a result of selection acting on information-behavior relationships, the human brain is predicted to be densely packed with programs that cause intricate relationships between information and behavior, including functionally specialized learning systems, domain-specialized rules of inference, default preferences that are adjusted by experience, complex decision rules, concepts that organize our experiences and databases of knowledge, and vast databases of acquired information stored in specialized memory systems—remembered episodes from our lives, encyclopedias of plant life and animal behavior, banks of information about other people's proclivities and preferences, and so on. All of these programs and the databases they create can be called on in different combinations to elicit a dazzling variety of behavioral responses. These responses are themselves information, subsequently ingested by the same evolved programs, in endless cycles that produce complex eddies, currents, and even singularities in cultural life. To get a genuine purchase on human behavior and society, researchers need to know the architecture of these evolved programs. Knowing the selection pressures will not be enough. Our behavior is not a direct response to selection pressures or to a "need" to increase our reproduction.
Hence, one of several reasons why evolutionary psychology is distinct from human sociobiology and other similar approaches lies in its rejection of fitness maximization as an explanation for behavior (Cosmides & Tooby, 1987; Daly & Wilson, 1988; Symons, 1987, 1989, 1992; Tooby & Cosmides, 1990a, 1992). The relative degree of fitness promotion under ancestral conditions is simply the design criterion by which alternative mutant designs were sorted in the evolutionary past. (The causal role fitness plays in the present is in glacially changing the relative frequencies of alternative designs with respect to future generations.) Although organisms sometimes appear to be pursuing fitness on behalf of their genes, in reality they are executing the evolved circuit logic built into their neural programs, whether this corresponds to current fitness maximization or not. Organisms are adaptation executers, not fitness pursuers. Mapping the computational architecture of the mechanisms will give a precise theory of behavior, while relying on predictions derived from fitness maximization will give a very impoverished and unreliable set of predictions about behavioral dynamics.
To summarize, evolutionary psychology's focus on psychological mechanisms as evolved programs was motivated by new developments from a series of different fields:
Advance 1: The cognitive revolution was providing, for the first time in human history, a precise language for describing mental mechanisms as programs that process information. Galileo's discovery that mathematics provided a precise language for expressing the mechanical and physical relationships enabled the birth of modern physics. Analogously, cognitive scientists' discovery that computational-informational formalisms provide a precise language for describing the design, properties, regulatory architecture, and operation of psychological mechanisms enables a modern science of mind (and its physical basis). Computational language is not just a convenience for modeling anything with complex dynamics. The brain's evolved function is computational—to use information to adaptively regulate the body and behavior—so computational and informational formalisms are by their nature the most appropriate to capture the functional design of behavior regulation.
Advance 2: Advances in paleoanthropology, hunter-gatherer studies, and primatology were providing data about the adaptive problems our ancestors had to solve to survive and reproduce and the environments in which they did so.
Advance 3: Research in animal behavior, linguistics, and neuropsychology was showing that the mind is not a blank slate, passively recording the world. Organisms come "factory-equipped" with knowledge about the world, which allows them to learn some relationships easily and others only with great effort, if at all. Skinner's hypothesis—that there is one simple learning process governed by reward and punishment—was wrong.
Advance 4: Evolutionary biology was revolutionized by being placed on a more rigorous, formal foundation of replicator dynamics, leading to the derivation of a diversity of powerful selectionist theories, and the analytic tools to recognize and differentiate adaptations, from by-products and stochastically generated evolutionary noise (Williams, 1966). [CLOSE QUOTE]
— David Buss—