Stephen M. Downes

Herbert Simon’s work on scientific discovery deserves serious attention by philosophers of science for several reasons. First, Simon was an early advocate of rational scientific discovery, contra Popper and logical empiricist philosophers of science (Simon 1966). This proposal spurred on investigation of scientific discovery in philosophy of science, as philosophers used and developed Simon’s notions of “problem solving” and “heuristics” in attempts to provide rational accounts of scientific discovery (See Nickles 1980a, Wimsatt 1980). Second, Simon promoted and developed many of the crucial techniques and methods used in cognitive science. One is the use of computers to model internal psychological processes, a technique central to his account of scientific discovery. Another is protocol analysis, the use of the verbal reports of experimental subjects in psychology to construct accounts of their psychological processes. Protocol analysis is given a detailed formulation by Simon (Simon and Ericsson 1984), and is modified for use in the study of scientific cognition in the paper on Krebs (Kulkarni and Simon 1988).

Fisher’s 1918 paper accomplished two distinct goals: unifying discrete Mendelian genetics with continuous biometric phenotypes and quantifying the variance components of variation in complex human characteristics. The former contributed to the foundation of modern quantitative genetics; the latter was adopted by social scientists interested in the pursuit of Galtonian nature-nurture questions about the biological and social origins of human behavior, especially human intelligence. This historical divergence has produced competing notions of the estimation of variance ratios referred to as heritability. Jay Lush showed that they could be applied to selective breeding on the farm, while the early twin geneticists used them as a descriptive statistic to describe the degree of genetic determination in complex human traits. Here we trace the early history of the heritability coefficient now used by social scientists.

In this paper I briefly introduce work on ancient-DNA and give some examples of the impact this work has had on responses to questions in archaeology. Next, I spell out David Reich’s reasons for his optimism about the contribution aDNA research makes to archaeology. I then use Robert Chapman and Alison Wylie’s framework to offer an alternative to Reich’s view of relations between aDNA research and archaeology. Finally, I develop Steven Mithen’s point about the different questions archaeologists and geneticists ask, arguing that different disciplinary perspectives color researchers’ perceptions of “the most important questions” or the “central topics” in a field. I conclude that evidence from aDNA research cannot solve archaeological disputes without closer, mutually respectful collaboration between aDNA researchers and archaeologists. Ancient DNA data, like radiocarbon data, is not a silver bullet for problems in archaeology.

In this paper I examine Paul Thagard's computational approach to studying science, which is a contribution to the cognitive science of science. I present several criticisms of Thagard's approach and use them to motivate some suggestions for alternative approaches in cognitive science of science. I first argue that Thagard does not clearly establish the units of analysis of his study. Second, I argue that Thagard mistakenly applies the same model to both individual and group decision making. Finally, I argue that in attempting to account for psychological and social processes as well as providing a philosophical model of successful reasoning Thagard attempts to explain too much with one model, thus straining the plausibility of his model.

Debates about human nature inform every philosophical tradition from their inception (see Stevenson 2000 for many examples). Evolutionarily based criticisms of human nature are of much more recent origin. Ironically, most evolutionarily based criticisms of human nature are directed at work whose avowed goal is to biologicize human nature and even to place human nature within an evolutionary frame. Here I will focus on accounts of human nature that begin with and come after E.O. Wilson’s sociobiology. I will also focus on criticisms of human nature that arose first as responses to sociobiology. There are some more recent approaches to human nature that have much in common with the sociobiological approach and I will show that critical arguments developed to target sociobiology have purchase on related recent approaches to human nature. In what follows I will briefly outline some well-known accounts of human nature. Next I will briefly outline some key evolutionarily based arguments against such accounts of human nature. I conclude by summarizing the evolutionary case against biological accounts of human nature and endorsing it.

I respond to Vladas Griskevicius and Douglas T. Kendrick (G&K) and Gad Saad's (S) defenses of the view that Consumer Studies would benefit from the appeal to evolution in all work aimed at understanding consumer behavior. I argue that G&K and S's reliance on one theoretical perspective, that of evolutionary psychology, limits their options. Further, I point out some specific problems with the theoretical perspective of evolutionary psychology. Finally, I introduce some alternative evolutionary approaches to studying human behavior that could profitably be adopted in consumer research.

I critically examine the semantic view of theories to reveal the following results. First, models in science are not the same as models in mathematics, as holders of the semantic view claim. Second, when several examples of the semantic approach are examined in detail no common thread is found between them, except their close attention to the details of model building in each particular science. These results lead me to propose a deflationary semantic view, which is simply that model construction is an important component of theorizing in science. This deflationary view is consistent with a naturalized approach to the philosophy of science.

There are a number of competing hypotheses about human evolution. For example, Homo habilis and Homo erectus could have existed together, or one could have evolved from the other, and paleontological evidence may allow us to decide between these two hypotheses (see, e.g., Spoor et al., 2007). For most who work on the biology of human behavior, there is no question that human behavior is in some large part a product of evolution. But, there are competing hypotheses in this area as well. Some claim that human behavior is produced by a collection of psychological mechanisms, for the most part, and that these mechanisms are adaptations that arose in the Pleistocene Epoch (e.g., Tooby & Cosmides, 1992; Buss, 2007). The claim is important and testable (although, more difficult to test than the above mentioned hypotheses about origins); but importantly, it is only one among many hypotheses about the evolutionary origins of human behavior. While I think that there may be components of our behavior that are best explained by appealing to processes or mechanisms that arose in the Pleistocene, I think that human behavior is a result of evolutionary processes both much older and more recent than the Pleistocene. I also maintain that much of human behavior, and the mechanisms underlying it, could still be subject to evolutionary..

Alternative splicing allows for the production of many gene products from a single coding sequence. I introduce the concept of alternative splicing via some examples. I then discuss some current hypotheses about the explanatory role of alternative splicing, including the claim that splicing is a significant contributor to the difference in complexity between the human genome and proteosome. Hypotheses such as these bring into question our working concepts of the gene. I examine several gene concepts introduced to cope with processes such as alternative splicing. Next I introduce some hypotheses about the evolution of mechanisms alternative splicing in higher organisms. I conclude that attention to alternative splicing reveals that we adopt an attitude that developmental theorizing must inform evolutionary theorizing and vice versa

In this paper I examine various ways in whichphilosophers have made connections between truth andnatural selection. I introduce several versions ofthe view that mechanisms of true belief generationarise as a result of natural selection and argue thatthey fail to establish a connection between truth andnatural selection. I then turn to scientific truthsand argue that evolutionary accounts of the origin ofscientific truth generation mechanisms also fail. Iintroduce David Hull's selectionist model ofscientific development and argue that his account ofscientific success does not rely on connecting truthand natural selection. I argue that Hull's model,which severs the connection between truth andselection, can account for some aspects of scientificchange, but it still leaves us plenty of questionsabout what aspects of our individual cognitive make-upcontribute to scientific change and how they do so. I introduce an evolutionary approach to scientificcognition that shows how some of these questions canbe answered without making an explanatory appeal toselection for true belief generating mechanisms.