Browsing by Author "Rosenberg, Alexander"

This thesis comprises an investigation into a very well known and perennial philosophical debate over the interpretive status of our most well confirmed scientific theories, known as "scientific realism." I do not defend scientific realism; rather, I set out to determine what scientific realism is in the first place. My contention is that the thesis is not a single, unified view, but rather a conglomeration of loosely associated propositions that are highly conceptually interwoven, but rarely distinguished. These consist of several different metaphysical, epistemological, and semantic doctrines, which I examine in great detail. I then argue that the indeterminate nature of scientific realism muddles the issue (if there is any) and renders debates fruitless. I attempt to define a thesis with relatively more precise content, which I call the "Core Realist Commitment," CRC. I argue that the CRC prioritizes epistemology - with the thesis that we can and do have (some) theoretical knowledge. I then demonstrate the relatively minimal commitments of the CRC, namely, a minimalist and very undemanding metaphysics, and almost none of the semantic theses that have been traditionally associated with realism. I conclude that the CRC is a step forward in thinking about the debate, not just for its relative precision but also because it is consistent with, and even tolerant of, a wide array of disagreement over concerns that are, I argue, external to the debate and need to be decided on independent grounds.

At the end of the nineteenth century Charles Sanders Peirce wrote that "chance begets order" - indeterministic or `chancy' processes can underlie orderly and seemingly deterministic processes. Indeed, Peirce argues that indeterminism is the seed of all order in the natural world. The dissertation explores this theme in three parts. The first chapter reconstructs and elaborates Peirce's objections against necessitarianism, the position that all natural laws are perfectly orderly, deterministic. The second chapter examines and elaborates Ronald Aylmer Fisher's sophisticated analogy between gas models from statistical mechanics and his own population genetics models. The final chapter treats a contemporary indeterministic account of biological fitness and examines several points on which intuitions from deterministic theories misinterpret this quintessentially indeterministic position. The dissertation motivates an indeterministic theory of natural law and reinvigorates its implications for hierarchical models of the natural world.

My dissertation applies models borrowed from game theory to the evolution of language and the emergence of meaning. To justify the use of such models, I begin in Chapter 1: Quantitative Methods in Philosophy by examining the prevalence of modeling techniques and other quantitative methods in philosophy. I then argue that reliance on quantitative methods is beneficial in some philosophical fields. Chapter 2: The Constructive Empiricist's Dilemma turns to computer models. In this chapter, I argue that only scientific realism can justify the use of computational models that assess the reliability of inference methods. This is surprising, given that modelers’ urge to idealize and simplify is often claimed to be at odds with scientific realism. In Chapter 3: Cheap Talk in Structured Populations, I present a model for the evolution of signaling and show both analytically and with computer simulations that signaling evolves with significantly lower signal cost if the population is spatially structured. Drawing on similar models of signaling, I examine in Chapter 4: Ambiguous Signals, Partial Beliefs, and Propositional Content the part that propositions are supposed to play in explanations of rational behavior. Simply put, my claim is that propositions cannot account for the behavior of rational agents.

This dissertation develops a theory of cognition, driven by recent developments in the electrophysiological investigation of the neuronal mechanisms that support adaptive behavior. In the first chapter, I situate the theory in the conceptual landscape of the philosophy of mind, distinguishing componential from systemic dynamical theories of cognition. In the second chapter, I analyze two case studies from electrophysiological cognitive neuroscience, arguing that cognitive neuroscientists are beginning to uncover the dynamical components of cognition. Drawing on the recent literature on mechanisms and scientific explanation, I propose a revised definition of a mechanism that accommodates these dynamical mechanisms, as well as making room for their implementation by physical mechanisms. In the third chapter, I argue that the investigation of a particular class of intelligent behavior begins with the construction of a formal model of the processing problem for that behavior, where this model is distinct from the physical device and the functions performed by the device's components. In the third chapter, I argue that the component dynamical mechanisms of cognitive systems are distinct from though implemented by physical mechanisms. These dynamical mechanisms are described by sets of differential equations, possess a set of organized components and activities that execute the formal models of processing, and are implemented by the physical machinery of the cognitive system, such as the brain. After I argue that these multiple interacting dynamical mechanisms are the components of cognition, defending this componentiality claim against several objections, I define the implementation relation that holds between dynamical and physical mechanisms. I next discuss the grounds for inferring the existence of dynamical mechanisms that are type distinct from physical mechanisms, their implementing substrate. In the fourth chapter, I argue that these dynamical mechanisms are reused: they can execute different formal models and be implemented by different physical substrates. I define this concept of reuse, situating it in the debate on theories of reuse, and illustrate how dynamical mechanisms are reused in cognitive systems.

This dissertation explores philosophical problems in biology, particularly those relating to macroevolutionary theory. It is comprised of a series of three papers drawn from work that is currently at the publication, re-submission, and review stage of the journal refereeing process, respectively. The first two chapters concern the overarching contours of complex life, while the third zeroes in on the short and long-term prospects of human evolution.

The rhetorical journey begins with a thought experiment proposed by the late paleontologist Stephen Jay Gould. Gould hypothesized that replaying the "tape of life" would result in radically different evolutionary outcomes, both with respect to animal life in general and the human species in particular. Increasingly, however, biologists and philosophers are pointing to convergent evolution as evidence for replicability and predictability in macroevolution. Chapters 1 and 2 are dedicated to fleshing out the Gouldian view of life and its antithesis, clarifying core concepts of the debate (including contingency, convergence, constraint and causation), and interpreting the empirical data in light of these conceptual clarifications. Chapter 3 examines the evolutionary biological future of the human species, and the ways in which powerful new biotechnologies can shape it, for better and for worse. More detailed chapter summaries are provided below.

In Chapter 1, I critique a book-length excoriation of Gould's contingency theory written by the paleobiologist Simon Conway Morris, in which he amasses and marshals a good bulk of the homoplasy literature in the service of promoting a more robust, counter-factually stable account of macroevolution. I show that there are serious conceptual and empirical difficulties that arise in broadly appealing to the frequency of homoplasy as evidence for robustness in the history of life. Most important is Conway Morris's failure to distinguish between convergent (`externally' constrained) and parallel (`internally' constrained) evolution, and to consider the respective implications of these significantly different sources of homoplasy for a strong adaptationist view of life.

In so doing, I propose a new definition of parallel evolution, one intended to rebut the common charge that parallelism differs from convergence merely in degree and not in kind. I argue that although organisms sharing a homoplastic trait will also share varying degrees of homology (given common decent), it is the underlying developmental homology with respect to the generators directly causally responsible for the homoplastic event that defines parallel evolution and non-arbitrarily distinguishes it from convergence. I make use of the philosophical concept of `screening-off' in order to distinguish the proximate generators of a homoplastic trait from its more distal genetic causes (such as conserved master control genes).

In Chapter 2, I critically examine a recent assessment of the contingency debate by the philosopher John Beatty, in which he offers an interpretation of Gould's thesis and argues that it is undermined by iterative ecomorphological evolution. I develop and defend alternative concepts of contingency and convergence, and show how much of the evidence generally held to negate the contingency thesis not only fails to do so, but in fact militates in favor of the Gouldian view of life. My argument once again rests heavily on the distinction between parallelism and convergence, which I elaborate on and defend against a recent assault by developmental biologists, in part by recourse to philosophical work on the ontological prioritization of biological causes.

In Chapter 3, I explore the probable (and improbable) evolutionary biological consequences of intentional germ-line modification, particularly in relation to human beings. A common worry about genetic engineering is that it will reduce the pool of genetic diversity, creating a biological monoculture that could not only increase our susceptibility to disease, but even hasten the extinction of our species. Thus far, however, the evolutionary implications of human genetic modification have remained largely unexplored. In this Chapter, I consider whether the widespread use of genetic engineering technology is likely to narrow the present range of genetic variation, and if so, whether this would in fact lead to the evolutionary harms that some authors envision. By examining the nature of biological variation and its relation to population immunity and evolvability, I show that not only will genetic engineering have a negligible impact on human genetic diversity, but that it will be more likely to ensure rather than undermine the health and longevity of the human species. To this end, I analyze the relationship between genotypic and phenotypic variation, consider process asymmetries between micro and macroevolution, and investigate the relevance of evolvability to clade-level persistence and extinction.

This dissertation proposes a new working model of reductionism for biology and a new concept of the gene based on the new reduction model. My project aims to help biologists and philosophers understand what reductionism in biology really is, or, should be. Historical debates about reductionism testify us that the classical reduction model, i.e., Ernest Nagel's bridge-law model, offers us neither an appropriate ontological reductionism nor a reductive explanation about biological phenomena. Casting doubts on the received view of the layered hierarchical model of ontology, I suggest that many interesting biological properties be construed as second-order functional properties and their first-order realizers. Providing for reduction finely-analyzed biological properties, I offer a new model for reductionism in biology - localized functional reductionism - which evolved from Jaegwon Kim's view of reductionism presented for the problems of mental causation.

My localized functional reductionism shows that a localized functional property is reduced to its base/structural property. I emphasize that researchers in biology do not deal with abstract general properties but always localized, structure-specific biological properties. A localized functional property and the structure-specific biological property as its base property are what we are interested in and this is what makes biological properties appropriate for research and meaningful for philosophical discussion. The localized functional reduction model, which is actually a case of token reduction model, integrates the fine-grained ontological hierarchies of both macro/micro-levels and higher/lower-orders, and it also synthesizes functional reductionism and token identity thesis. In my localized functional reductionism, functional biological properties are not eliminated but they exist with their own causal powers and true explanatory powers.

I also argue that the gene, construed as a second-order functional property, must be understood as gene expression network-specific. The gene, when it is realized on a given occasion, is reduced to, and is identical with, one of its genomic realizers on the given occasion, that is, the gene expression network. A new dynamic approach to the concept of the gene as the gene expression network vindicates reductionism.

This project advocates an urgent role for neurobiological evidence and models in the study of altruism. I argue for two claims: that neurobiological evidence should be used to constrain candidate scientific accounts of altruistic behavior, and that neurobiological techniques can be used to elucidate component mechanisms of altruistic behavior.

Chapter 1 reviews the historical progression of theories of altruism, and the empirical observations that motivated their development. A distinction is drawn between evolutionary altruism -- any self-sacrificial, fitness-reducing behavior, and psychological altruism -- self-sacrificial behaviors that are caused by psychological states like desire and motivation. Three theories of psychological altruism are described, and it is argued that the crucial difference between these theories is their conceptions of the role of affect in motivation, and how the processes of affect and motivation contribute to psychological altruism.

Chapter 2 describes dominant theories of motivation and the neurobiological and psychological mechanisms that support motivated behavior. Although the evidence is not conclusive, I argue that our best scientific models and neurobiological evidence support affective models of psychological altruism, and that other models are at best incomplete and possibly implausible in light of neurobiological considerations.

Chapter 3 introduces mind reading approaches to altruism, which argue that the capacity for altruistic motivations depends upon the capacity to represent the psychological states or circumstances of others. I conclude that altruism requires at a minimum the ability to attribute affective experiences to others. Further, I argue that the representations produced by mind reading processes provide a means for distinguishing between self-regarding and altruistic motivations. In contrast with the dominant philosophical theory of psychological altruism, the mind reading model I propose is compatible with the affective theory of motivation depicted in Chapter 2. My own empirical work is described as an example of how neurobiological techniques can reveal the differential role of neural systems in producing self-regarding and altruistic behavior.

Chapter 4 departs from the mechanistic approach to altruism discussed in the previous chapters, and presents an overview of how the fields of philosophy, psychology, psychobiology and genetics, have investigated altruism as a stable characteristic or personality trait. Recent technological advances make this a promising approach for investigating the psychological and neurobiological systems supporting altruistic behavior.

Our only example of life is that of Earth- which is a single lineage. We know very little about what life would look like if we found evidence of a second origin. Yet there are some universal features of geometry, mechanics, and chemistry that have predictable biological consequences. The surface-to-volume ratio property of geometry, for example, places a maximum limit on the size of unassisted cells in a given environment. This effect is universal, interesting, not vague, and not arbitrary. Furthermore, there are some problems in the universe that life must invariably solve if it is to persist, such as resistance to radiation, faithful inheritance, and resistance to environmental pressures. At least with respect to these universal problems, some solutions must consistently emerge.

In this dissertation, I develop and defend my own account of universal biology, the study of non-vague, non-arbitrary, non-accidental, universal generalizations in biology. In my account, a candidate biological generalization is assessed in terms of the assumptions it makes. A successful claim is accepted only if its justification necessarily makes reference to principles of evolution and makes no reference to contingent facts of life on Earth. In this way, we can assess the robustness with which generalizations can be expected to hold. I contend that using a stringent-enough causal analysis, we are able to gather insight into the nature of life everywhere. Life on Earth may be our single example of life, but this is merely a reason to be cautious in our approach to life in the universe, not a reason to give up altogether.

This dissertation presents some of the first work written and published on the Zero Force Evolutionary Law (McShea and Brandon 2010). It is a collection of four philosophy of biology papers, which together, illustrate the importance of the Zero Force Evolutionary Law (ZFEL) spanning evolutionary studies. In particular, this dissertation includes issues in the history of philosophy of science (chapter 1), group formation and network theory (chapter 2), biological hierarchy and the major transitions in evolution (chapter 3), and the Price equation and quantifying evolutionary change (chapter 4). While these four chapters may differ in focus, they make the same general claim: evolutionary methods and explanations are improved when the underlying tendency of biological systems is characterized correctly as exhibiting increasing variance.