Darwin's Conjecture Blog
Darwin's Conjecture Blog
Geoffrey M. Hodgson and Thorbjørn Knudsen
First published April-August 2013
First published April-August 2013
In 2013 a blog was set up by Geoff Hodgson and Thorbjørn Knudsen to discuss their book Darwin’s Conjecture: The Search for General Principles of Social and Economic Evolution (University of Chicago Press, 2010). People were invited to join the reading group for this book, make comments, and raise questions, on a scheduled, chapter-by-chapter basis. Chapter discussions were scheduled between April and August. This webpage records the chapter summaries and questions.
CHAPTER ONE
The opening chapter of the book discussed the relationship between evolutionary biology and the social sciences and its history. A distinction must be drawn between “biological reductionism” (attempting to explain social phenomena entirely in terms of genes) and the application of abstract evolutionary principles to socio-economic change. Darwin himself (who knew nothing about genes) conjectured that his principles may apply to the evolution of entities at the social level. This idea was taken up by a number of writers – including Walter Bagehot and Thorstein Veblen – before the whole idea of using biological ideas in the social sciences became highly unpopular in the early decades of the twentieth century. The application of abstract Darwinian principles to social evolution was revived by Donald T. Campbell (1965) and others after the Second World War. But it was not until the last few years that abstract Darwinian evolutionary principles have been sufficiently refined to develop a theoretical framework that is applicable to socio-economic evolution.
KEY QUESTIONS
1. What is the difference between biological reductionism and the derivation of common principles applicable to both biological and social evolution?
2. Why did the idea of deriving abstract evolutionary principles for the social sciences fall out of favor for so long?
3. What is the difference between analogy and generalization?
CHAPTER TWO
This chapter outlines the basic argument and explains what is meant by generalizing Darwinian principles. Instead of the vague, extremely broad, and ambiguous word “evolution” we start from the basic ontology of the general kind of system that we are addressing. This ontology is described in section 2.1. Such worlds are given the name “complex population systems.”
Among its important features is a population of entities, each of which has the capacity to store and pass on information relevant for its survival. These entities face (at least) locally scarce resources, and have to struggle to survive and minimize degradation. We claim that this ontology applies to both biological and social reality: just as there are populations of organisms, in society there are populations of organizations.
We then interpret the Darwinian principles of variation, selection, and inheritance (synonymous with replication) as explanatory requirements: the facts of survival, variation and information transmission must be explained. Our next step is to argue that such explanations will inevitably involve a combination of generalities and attention to specific mechanisms. So explanations at the most abstract level are necessary but insufficient.
What would make this argument inapplicable? Critics could argue that the ontology of complex populations systems does not apply to social reality. Another objection would be that the argument does not help us very much. But we are not claiming that it is a complete explanation. It is more a meta-theory, or a way of organizing theories and raising questions that require further theories and explanations.
KEY QUESTIONS
1. Is social reality a “complex population system” as described in Section 2.1?
2. What is meant by the Darwinian principles of variation, selection and inheritance?
3. What are the roles of general and more specific (auxiliary) theories in the explanation of complex phenomena?
CHAPTER THREE
This chapter deals with some prominent criticisms of the idea that Darwinian principles apply to social evolution. First we address the claim that Darwinism is inappropriate because it cannot deal with human intentionality. On the contrary, Darwin accepted that some species – including humans – were capable of reflecting on their circumstances, setting goals, and actin intentionally. But Darwin insisted that the evolution of intentionality and the development of intentions were caused, and subject to causal explanation.
Second we address the possibility of artificial selection. This is where some agent carries out a form of selection on a population. A misunderstanding here is to see it as a rival to selection more generally. Artificial selection is one form of selection. If it occurs in the social domain then that does not overturn Darwinism. On the contrary, Darwin used examples such as pigeon breeding to illustrate the more general idea of selection.
Third we address the phenomenon of self-organization, which is important in nature and in human society. Some authors have claimed that self-organization can serve as a general framework for understanding evolution. But self-organization addresses the emergence or development of a single entity, not a population of entities. Consequently it is an important but inadequate concept for dealing with evolution in complex population systems.
Fourth we address Ulrich Witt’s “continuity hypothesis”, which is a claim that nature grounds and constrains social evolution. We fully agree with this proposition. And it is entirely consistent with generalized Darwinian principles. So it would be a mistake to pose these two sets of ideas as mutually exclusive rivals.
KEY QUESTIONS
1. If some evolutionary biologists have downplayed deliberation or intentionality in their study of nature, does that mean that Darwinism necessarily excludes them?
2. How does the concept of artificial selection relate to selection per se? And how does the actual process of artificial selection relate to other processes of selection?
3. If self-organization is important, is it a sufficient organizing principle? If not, why not?
4. What is the relationship between the “continuity hypothesis” and generalized Darwinism?
CHAPTER FOUR
This chapter is mainly on Lamarckism and has critical and constructive messages. We focus on the meaning of Lamarckism as “the inheritance of acquired characters”.
On the critical side, the chapter rebuts the idea that social evolution is Lamarckian rather than Darwinian. This is mistaken for a number of reasons. First, Darwinism (suitably defined) and Lamarckism are not mutually exclusive. In fact, Darwin believed in Lamarckian inheritance in the biological world. Subsequent biologists have thought otherwise, but that is beyond the point. Second, even if Lamarckian inheritance did occur (as on our imaginary Planet Lamarck) it would still require some process of selection to explain evolution in populations. Consequently, if Lamarckism were true it would require Darwinism. (This point was made previously by Richard Dawkins.)
Lamarckism raises a number of other questions and problems. As the late David Hull pointed out, it is important to be clear about the meaning of “inheritance” in the “inheritance of acquired characters”. Inheritance must be distinguished from contagion. Otherwise the transmission of fleas from one dog to another would be the “inheritance of acquired characters”. It is clearly not.
In contrast to contagion, inheritance means the copying of developmental instructions. It is not good enough for a Lamarckian to say that if we develop strong arm muscles then our children will have strong arms too. The Lamarckian must uphold that we have passed on the developmental capacity to develop strong arms through our genes, which carry these (new) developmental instructions.
Now here comes the clinch, which signals the constructive part of this chapter. Hereditable “developmental instructions” (with a bit more definitional stuff added), are REPLICATORS. Consequently, simply to make sense of Lamarckian inheritance (leaving aside whether it is true or not) we have to adopt something like the REPLICATOR-INTERACTOR distinction. Those that reject the replicator concept while saying that (social) evolution is Lamarckian (e.g. Richard Nelson and Peter Richerson) cannot have it both ways.
Finally, and also on the constructive side, we consider possible social replicators (above the level of genes), namely habits and routines. When we address these replicators and consider possible Lamarckian inheritance in social evolution, further problems arise. Something (very vaguely) like Lamarckism may exist in social evolution but calling it Lamarckian is highly misleading.
KEY QUESTIONS
1. Are Darwinism and Lamarckism mutually exclusive?
2. What is the difference between inheritance and contagion?
3. Why does coherent Lamarckism require the replicator concept?
4. What are possible social replicators?
CHAPTER FIVE
This chapter discusses the concept of selection. It is trickier than it may appear at first sight. It is striking that numerous authors in the social sciences use terms such as “variation-selection-retention model” without defining selection or apparently realizing its complexity.
Selection implies an ontology of multiple entities existing at the same point in time. Critics of the selection concept often overlook this. They often regard “evolution” as the process of development of a single entity, which of course is one of several possible meanings of that word. Generalized Darwinism applies to a population of multiple entities.
Selection neither implies progress nor excludes cooperation. It can take different forms and involves multiple possible mechanisms. Our definition of selection (in section 5.1) follows closely the work of George Price. The definition involves an anterior and posterior set of entities in a population. The posterior set can be a subset of the anterior set (which we call subset selection), or it can be some kind of offspring of the anterior set (which we call successor selection). This definition is helpful for analytical purposes. It can be made operational, and thus useful in empirical research by translation to a regression framework.
Much discussion of selection in the social sciences concentrates simply on subset selection, which in contrast to successor selection, is unable to generate novelty.
The definition of selection involves the tricky concept of fitness: by definition with selection the composition of the posterior set is causally related to fitness. Fitness is easy to define in abstract, mathematical terms. But it is difficult to define its specific expression, in both the biological and the social world. In any case, it does not simply mean survival, thus avoiding a tautological formulation of selection. We see the fitness of an interactor as the propensity of its replicators to replicate, by diffusion to other interactors or by making copies of the interactor.
The objects of selection are interactors. We write of “selection of” such objects. The outcome of the change in the population of interactors is a change in the pool of replicators in the population. This is “selection for”. (The philosopher Elliott Sober introduced the terms “selection of” and “selection for” but we use the distinction in a different way.)
In their 1982 book, Richard Nelson and Sidney Winter describe the introduction or curtailment of routines by management within an organization as selection. In contrast, in our conceptual framework only interactors can be objects of selection. We call the type of process described by Nelson and Winter “replicator manipulation”.
We also define the concept of diffusion in this chapter. Diffusion is a type of inheritance that involves the copying of replicators, but not of interactors. Diffusion is common in the social domain, particularly in regard to ideas and technologies. In these cases, associated habits and routines are copied from one interactor to another.
KEY QUESTIONS
1. Why does selection not always relate to progress or efficiency, even if it is related to fitness?
2. In what way can a selection process create novelty?
3. Are the difficulties with the fitness concept an insurmountable barrier?
4. What is the relationship between selection and replication?
5. Is diffusion related to fitness?
CHAPTER SIX
In this chapter we further clarify and develop the replicator concept, and we also develop a new concept of generative replication. The primary of generative replication virtue is that it allows us to consider replication of developmental instructions. We relate the replicator concept to complexity, and identify conditions that can lead to increases in complexity.
We emphasize that a replicator is not a thing but an informational mechanism. This is sufficient to counter many of the arguments against replicators. In general, following several other authors, replication involves three conditions, pertaining to causality, similarity and information transfer (see page 119). These establish the broad concept of a replicator.
Next, in section 6.3, inspired by work by John von Neumann, we ask what kinds of replicator and replication have the potential to increase complexity. This leads us to fine-tune the three conditions already established in the literature, and add a fourth, concerning “conditional generative mechanisms” (pages 122-3). When a replicator also satisfies this fourth condition it is called a “generative replicator”. The fourth condition is that within the information contained in the replicator there are instructions that guide the development of its host interactor. In other words, a particular kind of development information is involved.
An example of a biological replicator that is not generative is a prion (as in mad cows’ disease). Genes are clearly generative replicators. We argue that habits and routines can also be generative replicators. We criticize the meme concept to be vague and inadequate in this regard.
We argue that generative replicators have the potential to increase complexity, as long as their information is copied with sufficient fidelity. Crucially, copy error must be minimized. We note that complexity in social systems has increased much more rapidly in the last 10,000 years than in biological systems. This for us is evidence consistent with the existence of generative social replicators.
KEY QUESTIONS
1. Can the replicator concept survive the criticism to which it has been subjected?
2. What are the weaknesses of the meme concept?
3. What are good examples of generative replication in social systems?
4. How is complexity defined?
5. Why is an examination of the conditions for increasing complexity important?
CHAPTER SEVEN
This chapter introduces the ideas of group selection and multi-level selection, and defines the interactor.
Thanks to the work of David Sloan Wilson, Elliott Sober and others, the concept of group selection has been rehabilitated in mainstream biology. To understand group selection it is vital to make a distinction between objects of selection (interactors) and outcomes of selection in a population (the pool of replicators). Group selection means that groups are objects of selection, and thus interactors. For this to happen, variation within groups must be less than variation between groups.
Genetic group selection refers to variation in regard to genes and changes in the gene pool of a population. Cultural group selection refers to variation in regard to cultural replicators (habits, customs, and routines) and outcomes in regard to their distribution.
In human evolution, genetic intermixing between groups may have diminished the effects of genetic group selection, whereas processes such as conformism may have created sufficient group homogeneity for cultural group selection to work.
Up to this point we draw on existing literature. From about page 103 we make a new contribution. We ask what are the features that make a selected group (in viable group selection) relatively coherent, cohesive and long-lasting. Such groups must be more than mere aggregates of individuals.
To this end we modify David Hull’s classic definition of an interactor. Our definition appears on pages 106-7. Among other things, it differentiates an interactor from its environment, and shows the dependence of component replicators on their interactor. In turn, replication depends on interaction between the interactor and its environment.
Finally we discuss how business organizations can be interactors, and how their component routines can replicate. Much replication in the social world is through diffusion, but in the case of firm spin-offs replication involves offspring replicators.
KEY QUESTIONS
1. What are the conditions for group selection to occur?
2. In what respects can groups be more than the sum of their members?
3. What are interactors?
4. What are possible mechanisms of replication in the social world?
CHAPTER EIGHT
This chapter develops some key ideas concerning replication and information transition in socio-economic evolution. Inspired by the great 1995 book on The Major Transitions in Evolution by the biologists John Maynard Smith and Eörs Szathmáry, this chapter argues that increasing social complexity has resulted from crucial changes in the way that information is stored and transmitted. Sharing their informational perspective, we identify six modes of replication in human society above that of the genes.
The first supra-genetic mechanism of transmission occurred millions of years ago in our ape-like ancestors. Even without language, there were proto-cultural mechanisms of transmission in social groups, involving expressions, noises, smells and feelings. The second social level of transmission occurred around 100,000 years ago, with the development of a complex language. This enabled the communication of know-how, rules and meanings. The third social level occurred once language became established, involving customs, ceremonies and social positions. The fourth social level involved the development of symbols and writing, which occurred at different times in different civilizations. The fifth social level concerned the development of a legal system, with a judiciary and written rules. The sixth social level emerged much more recently; it is the institutionalization of science and technology.
Each level of social evolution has its own characteristics and mechanisms. Each depends on the bedrock of preceding layers, as in Maynard Smith and Szathmáry’s (1995) account of the major transitions in biological evolution. We argue that each new level is associated with a new type of generative replicator. The complex, multi-layered nature of social evolution means that it is highly unlikely to follow an optimal path. No new layer must build on the rudiments of the past, even if they may be imperfect for the future.
KEY QUESTIONS
1. Focusing on information transitions omits other important changes in (biological and social) evolution. Does this undermine the value of this approach?
2. Why is it important to distinguish between multiple levels of social evolution? Isn’t it all “cultural”?
3. In what senses are these different levels “informational”?
4. Why is social evolution suboptimal?
CHAPTER NINE
This final chapter wraps up the book and looks to the future. In section 9.1 we once again consider why Darwinian principles have been resisted in the social sciences. We claim to have overcome key objections.
Section 9.2 argues that evolutionary approaches in the social sciences cannot start from observation alone, and an over-arching theory is required.
Section 9.3 outlines some of the conceptual advances in the volume, including our refinements of the concepts of selection and replication. Our notion of the replicator makes links with pragmatist philosophy and surpasses the problematic concept of the meme. Our use of the concept of the replicator and multiple-level selection are further contributions.
In Section 9.4 we propose that the social sciences are going through a “double gestalt shift”, involving understanding social systems as information processors and an appreciation of the implications of complexity.
Finally, in Section 9.5 we point to the need for more concrete analysis. As well as developing an over-arching framework we need empirical analysis and middle-range theory.
The thoughts and comments of the reader on all this are most welcome.