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7 Behavior-Evolution Parallels
Behavior-Evolution Parallels 91 this in Hawaii with two porpoises. She rewarded each day a behavior never seen before and concluded:
A technique of reinforcing a series of different, normally occurring actions, in a series of training sessions . . . serve[d] . . . in the case of Hou, as with Malia, to establish in the animal a highly increased probability that new types of behavior would be emitted. 4
Interestingly, some of these behaviors were entirely novel to the dolphin spe-cies with which she worked ( Steno bredanensis ), although they were seen in others (such as the more common Tursiops truncatus ). It’s also interesting that this technique doesn’t seem to work with pigeons; they don’t become more creative as the training is continued. 5
Human beings are of course more complicated—or at least, via language, have more different things they can do—than dolphins. If we want to train them in a complex skill, like writing poetry, just paying them off for any new scribble won’t do it! It takes countless zillions of monkeys randomly tapping keyboards to produce a single Shakespeare sonnet. Just generating variety is not, by itself, enough. Selection must also be involved.
Darwin faced the problem in applying natural selection to what he called organs of extreme perfection and complication , like the eye:
To suppose that the eye with all its inimitable contrivances for adjusting the focus to different distances, for admitting different amounts of light, and for the correction of spherical and chromatic aberration, could have been formed by natural selection, seems, I freely confess, absurd in the highest degree. . . . [But] [r]eason tells me, that if numerous gradations from a simple and imperfect eye to one complex and perfect can be shown to exist, each grade being useful to its possessor, as is certainly the case; if further, the eye ever varies and the variations be inherited, as is likewise certainly the case; and if such variations should be useful to any animal under chang-ing conditions of life, then the diffi culty of believchang-ing that a perfect and complex eye could be formed by natural selection, though insuperable by our imagination, should not be considered as subversive of the theory. 6 By meticulously describing parallels of stages of eye development within (embryology) and between existing species, from simple photocell eye-spots of primitive mollusks, to non-focusing eye-cups to compound eyes to eyes with a single, focusing lens, Darwin made a plausible case for a set of precur-sors along the path to the evolution of the vertebrate eye.
Much the same can be done with human behavior: Generate variation, then select. How do you get the human equivalents to Pryor’s “creative porpoise”?
First, behavioral variation without which you have nothing from which to select. But then, what are the behaviors that parallel Darwin’s stages of eye development? What are the precursors of the behavioral end product? Indeed, what is the end product of a creative education? Answers to these questions are still very much a matter of intuition on the part of the creative teacher.
Behavioral Variation: Context and Pavlovian Conditioning
Context—stimuli and reinforcers—constrains, sustains and directs behavioral variation. For example, Pavlovian conditioning, which allows a neutral stimu-lus to acquire signal properties, will itself give rise to a repertoire of reinforcer-related activities on which operant reinforcement can act. A stimulus associated with food, or food by itself, will induce a wide range of food-related activities in a hungry animal—activities from which operant contingencies can select.
Pigeons peck, chickens peck and scratch, raccoons manipulate. Pavlovian con-ditioning, with (say) a food US, in effect frames or labels the context as food related. The label then limits the emitted behavior to a food-related repertoire, which is defi ned partly by past history but also by the organism’s evolutionary history. If the operant contingency is one rarely or never encountered by the organism’s ancestors, this repertoire may be inadequate or inappropriate—and the organism will “misbehave,” as in the examples discussed earlier.
How does this labeling work? This is a neglected problem, probably because it involves not behavior but cognition. Labeling is determined by how the organism “perceives” the situation given its cognitive limitations and its past history in similar situations. It would be nice to know, for a given individual and species, exactly how context limits behavioral variation and what might be done to manage these effects—for the purposes of training and education, for example. More on training and teaching in Chapters 19 and 21 .
If context limits the range of induced activities, then the power of oper-ant reinforcement to mold behavior will also be limited, in ways that may confl ict with standard reinforcement accounts. Autoshaped pecking and some kinds of instinctive drift are examples. Given a highly predictive stimulus, pecking (in pigeons) may be the only activity induced, so that a contingency involving some other activity, particularly one that interferes with pecking, can have no effect. Recall, for example, the Williams and Williams experiment that delivered food on a Pavlovian schedule so long as no pecking occurred (omis-sion training). The birds pecked anyway about half the time, the remaining stimulus-food pairings still being suffi cient to sustain pecking as a major part of the repertoire offered up by processes of behavioral variation. Pigeons show similar misbehavior in something called the feature-negative effect 7 when they continue to peck at a stimulus that signals nonreinforcement because it shares common features with a strongly reinforced stimulus. This happens even if the pigeons can tell the positive and negative stimuli apart under other conditions.
Frequency-Dependent Selection
Over the long term, selection can affect variation. This process is well known in biological evolution. In frequency-dependent selection, for example, vari-ability is favored if rare types have higher fi tness than common types. Why should rare types be favored? One reason is the perceptual limitations of preda-tors. As they search for cryptic (i.e., camoufl aged) prey, rare types may do bet-ter because predators have to learn to see cryptic prey. Learning is quicker and
Behavior-Evolution Parallels 93
more complete when the same type is encountered frequently. Consequently, rare types are harder to recognize than common ones. There is now a fair amount of evidence in favor of this interesting idea. 8
If each new variant has an advantage just because of its rarity, frequency-dependent selection can give rise to a population that is highly variable in form. Biology texts describe many examples. The highly variable snail Cepea is perhaps the best known (Plate 7.1). Reinforcement schedules with the prop-erty of frequency dependence—preferentially reinforcing response types that have occurred “least recently”—also give rise to random-appearing behavior, presumably for the same reason. 9
Supernormal Stimuli and Asymmetrical Selection
Specifi c reinforcement effects have surprising parallels in phylogeny. For example, there is a phenomenon of instinctive behavior known as supernormal stimuli. A supernormal stimulus is a stimulus never seen under natural condi-tions that is nevertheless more effective than the natural stimulus. Plate 7.2 shows an example: In preference to its own egg, an oystercatcher is retrieving Plate 7.1 Some polymorphic examples of the snail Cepea (http://en.wikipedia.org/
wiki/File:Polymorphism_in_Cepaea_nemoralis.jpg).
Plate 7.2 An oystercatcher retrieving an artifi cial, super-large egg in preference to its own, smaller egg.
Plate 7.3 The Venus of Willendorf (circa 23,000 BC).
a much larger artifi cial egg. Another example is the preference of male Argyn-nis paphia butterfl ies for a light stimulus that fl ickers at a much faster rate than the natural stimulus—the wings of a female butterfl y. The hugely exaggerated proportions of primitive fertility symbols like the 25,000-year-old Venus of Willendorf (Plate 7.3) may be a human example. 10
There is a comparable phenomenon in discrimination learning (see the dis-cussion of stimulus generalization in Chapter 5 ). It works like this. A pigeon is trained to respond to one stimulus, say a wavelength of 550 nm, which is alternated with another, at 500 nm, in the presence of which it never gets any food. Pigeons soon learn not to peck the 500 nm stimulus and to peck the (rewarded) 550 nm one. Yet, a test with 600 nm will usually show more enthu-siastic pecking than to the 550 nm positive stimulus used in training. In other words, responding is maximal at a point on the wavelength dimension dis-placed away from the negative (500 nm) stimulus ( peak shift ).
These phenomena all seem to refl ect asymmetrical selection. 11 In the oper-ant case, the subject is trained to respond at 550 nm and to suppress responding
Behavior-Evolution Parallels 95 to 500 nm. It never sees 600 nm in training, so there is no selection against responding to 600 nm, which is why it is favored over 550 nm in a generaliza-tion test. In the phylogenetic case, the normal egg is favored, but retrieval of smaller-than-normal eggs may be selected against because they are likely to be unviable. Larger-than-normal eggs are never encountered in nature (too big to lay, presumably); hence they may be favored when encountered under artifi cial conditions. A similar account also works for the butterfl ies. High fl icker rates are not encountered in nature, but low rates are—the wings of birds that feed on butterfl ies. So natural selection drives preference away from low rates.
Phenotype and Genotype
Intrinsic to the Darwinian metaphor is the distinction between phenotype and genotype. The phenotype is the visible outcome of the developmental process, the whole organism with its morphology and behavior. The phenotype is what makes contact with the environment and is subject to the “contingencies of sur-vival.” (Actually, Darwinian fi tness depends on reproduction, not just survival, but Skinner’s phrase, echoing Herbert Spencer’s “survival of the fi ttest,” is catchier.) But it is the genotype that is inherited, so that only those phenotypic characteristics that have a genetic counterpart can take part in the evolutionary process. 12 The generations of spaniel pups that had their tails docked at birth have not given rise to a race of tailless spaniels.
The phenotype-genotype distinction resembles the neo-behaviorist distinc-tion between performance and learning. Performance is what you see: measured behavior. Learning, or competence , is what you can see potentially. Perfor-mance is how well you do on the exam right after a night of drunken carousing.
Competence is how you could have done, had you managed your evening more moderately. Skinner never accepted the competence-performance distinction.
Consequently, he never admitted that the phenotype-genotype distinction might also apply to operant behavior, even though it is part and parcel of the Darwinian metaphor. The distinction nevertheless refl ects well-known facts.
Not all phenotypic characteristics are heritable, and hence subject to selection pressure. Only some things that animals do can be selected through operant reinforcement. Distinguishing those that can from those that cannot requires an understanding of the relations between the internal processes that gener-ate overt actions and the actions themselves—the behavioral equivalent of the laws of development that translate genotype into phenotype. It also requires an understanding of the differences between those internal states that have succes-sors across time (i.e., memories ) and those internal states that leave no imprint on the future. Skinner never accepted the idea of internal states as essential elements in explanations for behavior. So: no memories, no principled way to distinguished between experiences that do have persistent effects and those that don’t.
The Darwinian metaphor can be applied in many different ways—and there is often no easy way to distinguish empirically among them. What we can say
is that Skinner’s application was rather superfi cial. Even in the area of human social arrangements, much better attempts have been made. D. T. Campbell, for example, in a carefully reasoned account, identifi ed sources of confl ict between “selfi sh” propensities favored by individual genetic selection, and
“altruistic” propensities favored by cultural evolution within groups driven by competition between them. Campbell’s claims were cautious: “You are hereby warned—this talk is not hardheaded science but an exercise in quasi-scientifi c speculation.” 13 He frequently reminds his readers that real-life social ques-tions cannot be the subject of meaningful experiments. Campbell knew that generalizing from laboratory situations to the world at large was fraught with uncertainty. In recent years, a new fi eld of evolutionary psychology has come into being, which seeks to apply the Darwinian metaphor in systematic and testable ways to human behavior. 14 It has so far had limited success, for reasons that Campbell well understood.
Notes
1. In his later years, Darwin did come up with a theory of inheritance, which he called pangenesis. In effect it stood modern genetics on its head. Rather than the genome dividing along with the zygote and its descendants, Darwin’s gene equivalents, which he called “gemmules,” migrated in the adult from every part of the body into the reproductive organs. See http://en.wikipedia.org/wiki/Pangenesis.
2. Darwin, C. (1868). The variation of animals and plants under domestication (John Murray). Retrieved from http://darwin-online.org.uk/EditorialIntroductions/
Freeman_VariationunderDomestication.html.
3. For a quick video summary, see Charles Osgood on the Sunday Morning Show around 1972 or so: www.youtube.com/watch?v=D-RS80DVvrg.
4. Pryor, K. W., Haag, R., & O’Reilly, J. (1969). The creative porpoise: Training for novel behavior. Journal of the Experimental Analysis of Behavior, 12 , 653–661.
See also Maltzman, I. (1960). On the training of originality. Psychological Review, 67 , 229–242.
5. JERS, unpublished data.
6. Darwin, C. (1859). The origin of species .
7. See Staddon, J. E. R. (2010). Adaptive behavior and learning, Ch. 11. Retrieved from http://dukespace.lib.duke.edu/dspace/handle/10161/2878.
8. See, for example, “Search Image Formation in the Blue Jay ( Cyanocitta cristata )”
by Alexandra T. Pietrewicz and Alan C. Kamil: http://digitalcommons.unl.edu/cgi/
viewcontent.cgi?article=1065&context=bioscibehavior&sei-redir=1&referer=ht tp%3A%2F%2Fscholar.google.com%2Fscholar%3Fhl%3Den%26q%3Dsearch
%2Bimage%26btnG%3D%26as_sdt%3D1%252C34%26as_sdtp%3D#search=
%22search%20image%22.
For reviews, see Davies, N. B., Krebs, J. R., & West, S. A. (2012). An introduction to behavioural ecology (New York: John Wiley); see also Shettleworth, S. (2010).
Cognition, evolution and behavior (New York: Oxford University Press).
9. The original frequency-dependent experiment was done by Blough, D. S. (1966).
The reinforcement of least-frequent interresponse times. Journal of the Experi-mental Analysis of Behavior, 9 (5), 581–591. More recent studies are Machado, A. (1992). Behavioral variability and frequency-dependent selection. Journal of the Experimental Analysis of Behavior, 58 , 241–263; and Page, S., & Neuringer, A. (1985). Variability is an operant. Journal of Experimental Psychology: Animal Behavior Processes, 11 , 429–452.
Behavior-Evolution Parallels 97 10. See http://en.wikipedia.org/wiki/Venus_of_Willendorf.
11. Staddon, J. E. R. (1975). A note on the evolutionary signifi cance of supernormal stimuli. American Naturalist, 109 , 541–545; see also Ghirlanda, S., & Enquist, M.
(2003). A century of generalization. Animal Behaviour, 66 (1), 15–36; Reid, A. K.,
& Staddon, J. E. R. (1998). A dynamic route-fi nder for the cognitive map. Psy-chological Review, 105 , 585–601 . Retrieved from http://dukespace.lib.duke.edu/
dspace/handle/10161/7383.
12. There are some modest exceptions to this. See, for example, Nature insight. (2007).
Epigenetics, 447 (7143), 396–440: “Genetic mechanisms alone cannot explain how some cellular traits are propagated. Rapid advances in the fi eld of epigenetics are now revealing a molecular basis for how heritable information other than DNA sequence can infl uence gene function.”
13. Campbell, D. T. (1975). On the confl icts between biological and social evolution and between psychology and moral tradition. American Psychologist, 30 , 1103–
1126; Campbell, D. T. (1956). Adaptive behavior from random response. Behav-ioral Science, 1 , 105–110.
14. Buss, D. M. (Ed.). (2005). The handbook of evolutionary psychology (Hoboken, NJ: John Wiley); Stent, G. (1980). Morality as a biological phenomenon (Berkeley:
University of California Press); Ridley, M. (1997). The origins of virtue: Human instincts and the evolution of cooperation (New York: Viking); Cosmides, L., &
Tooby, J. (1994). Better than rational: Evolutionary psychology and the invisible hand. The American Economic Review, 84 (2), 327–332. See http://en.wikipedia.
org/wiki/Evolutionary_psychology.
Economists talk about “rationality,” evolutionary theorists about “optimality.”
Human beings are supposed to behave rationally—that is to say, in a way that maximizes their “utility.” For economists, that usually means maximizing their income. Evolution by natural selection often works to produce behavior that is “optimal” in terms of reproduction—number of offspring—or some proxy for reproduction like food or access to a mate. Some theorists have claimed that much operant behavior is optimal in the sense that it maximizes rate of reinforcement. The idea in all cases is that the system—evolution or the free market or the law of effect—almost always produces the “best” result.
I need to spend some time on the idea of rationality because explanations for behavior both by behaviorists and nonbehaviorists, make some use of it. Economists, for the most part, see human action as rational. Behavioral economists, of which there are at least two varieties, tend to disagree. Radical behaviorists refer to reason only to disparage it. How useful are explanations of behavior in terms of rationality? I will argue that the term is usually more trouble than it’s worth.
In economics, especially, there is much confusion about what “rational”
means. Here is an example to illustrate the problem. It’s from a brief article in Scientifi c American. The author, a distinguished economist, 1 discusses a game called the Traveler’s Dilemma. It is a variant of the well-known pris-oner’s dilemma, 2 a game in which each player, following his own interest, yields a result that is worse for both players than if they had followed less selfi sh strategies. The article begins, “When playing this simple game, people consistently reject the rational choice.” The point of the example is that the author, not alone among economists, confuses one kind of optimizing method with rationality itself. But, as the Darwinian metaphor should remind us, there are many ways to skin a cat, and rational behavior cannot be identifi ed with a single process, no matter how useful. Let’s see how the Traveler’s Dilemma works:
Lucy and Pete, returning from a remote Pacifi c island, fi nd that the airline has damaged the identical antiques that each had purchased. An airline manager says that he is happy to compensate them but is handicapped by
8 Rationality
Rationality 99 being clueless about the value of these strange objects. Simply asking the travelers for the price is hopeless, he fi gures, for they will infl ate it.
Instead he devises a more complicated scheme. He asks each of them to write down the price of the antique as any dollar integer between 2 and 100 without conferring together. If both write the same number, he will take that to be the true price, and he will pay each of them that amount.
But if they write different numbers, he will assume that the lower one is the actual price and that the person writing the higher number is cheating.
In that case, he will pay both of them the lower number along with a bonus and a penalty—the person who wrote the lower number will get $2 more as a reward for honesty and the one who wrote the higher number will get
$2 less as a punishment. For instance, if Lucy writes 46 and Pete writes 100, Lucy will get $48 and Pete will get $44.
$2 less as a punishment. For instance, if Lucy writes 46 and Pete writes 100, Lucy will get $48 and Pete will get $44.