It is proposed that the Darwinian theoretical approach and account of living systems has not yet been clearly given. A first approximation to this is attempted, focussing on behavior in evolving environments. A theoretical terminology is defined emphasizing the mutuality of organism and environment and the existence of biologically theoretical entities.

The goal of forming a science of intentional behavior requires a more richly detailed account of symbolic systems than is assumed by the authors. Cultural systems are not simply the equivalent in the ideational domain of culture of the purported Baldwin Effect in the genetic domain. © 2014 Cambridge University Press.

The management of cross-sector social partnerships (CSSPs) among government, business, and not-for-profit entities can be complex and difficult. This article considers the importance of organizational experience and learning for the successful development of CSSPs. By analyzing the Manchester Super Casino, this research emphasizes the significant benefits of prior experience with CSSPs that enable partners to learn and develop relationships, skills, and capabilities over time, which then have positive influences on future performance. The result is a refined learning model of the (...) CSSP process that includes key variables for CSSP success. As such, these findings provide a template for managing complex CSSPs from the perspective of the different partner organizations. (shrink)

There are many branches of philosophy called “the philosophy of X,” where X = disciplines ranging from history to physics. The philosophy of artificial intelligence has a long history, and there are many courses and texts with that title. Surprisingly, the philosophy of computer science is not nearly as well-developed. This article proposes topics that might constitute the philosophy of computer science and describes a course covering those topics, along with suggested readings and assignments.

Abstract Philosophers have paid little attention to the kind of reduction involved in transforming an analytically intractable equation into solvable form. I argue that this practice is important because it involves the design of a basic level theory for use in a specific domain. The design process can lead to the construction of a new theory. As a result of my analysis, theory design emerges as an important category of analysis for scientific methodology. Similarities between design in technology and science (...) are explored to illuminate the heuristic function of such reductions. (shrink)

One might poetically muse that computers have the essence both of logic and machines. Through the case of the history of Separation Logic, we explore how this assertion is more than idle poetry. Separation Logic works because it merges the software engineer’s conceptual model of a program’s manipulation of computer memory with the logical model that interprets what sentences in the logic are true, and because it has a proof theory which aids in the crucial problem of scaling the reasoning (...) task. Scalability is a central problem, and some would even say the central problem, in appli- cations of logic in computer science. Separation Logic is an interesting case because of its widespread success in verification tools. For these two senses of model—the engineering/conceptual and the logical—to merge in a genuine sense, each must maintain their norms of use from their home disciplines. When this occurs, both the logic and engineering benefit greatly. Seeking this intersection of two different senses of model provides a strategy for how computer scientists and logicians may be successful. Furthermore, the history of Separation Logic for analysing programs provides a novel case for philosophers of science of how software engineers and computer scientists develop models and the components of such models. We provide three contributions: an exploration of the extent of models merging that is necessary for success in computer science; an introduction to the technical details of Separation Logic, which can be used for reasoning about other exhaustible resources; and an introduction to the problems, process, and results of computer scientists for those outside the field. (shrink)

It is argued that the traditional distinction between artificial intelligence and cognitive simulation amounts to little more than a difference in style of research - a different ordering in goal priorities and different methodological allegiances. Both enterprises are constrained by empirical considerations and both are directed at understanding classes of tasks that are defined by essentially psychological criteria. Because of the different ordering of priorities, however, they occasionally take somewhat different stands on such issues as the power/generality trade-off and on (...) the relevance of the sort of data collected in experimental psychology laboratories. (shrink)

The ?language of the gods? is conceived as a kind of language more complex than what we associate with human tongues in the strict sense of the term. Certain arbitrary regularities throughout the rational disciplines appear to indicate the existence of this language. The present article explores this new concept and applies it in an attempt to provide a logical clarification of the notions of individual consciousness and physical reality.

An approach to the philosophy of biology in the 21st century requires going beyond its epistemological side, betting on pragmatic aspects, in the sense of the social impact of the instrumentalization of biological developments. These advances have both beneficial and harmful consequences for humanity. Among the latter, it is its use for military conflicts, as a result of advances in biotechnology. The objective of this work is to address the role of biological knowledge in wars, analyzing some especially relevant cases (...) such as bioterrorism, but also other types of conflicts in which biology, broadly understood with its different branches, plays an important role. First, I will introduce the most important concepts in the relationship between biology and war, taking into account historical precedents in this area. Secondly, since biology enters in military conflicts, I will address the case of bioterrorism as one of the most pressing problems in that it is one of the forms that war is currently taking, as well as one of its derivatives, “agroterrorism”, which consists in causing the destruction of crops or the death of livestock that feeds the population. In this regard, I will examine other ways of resolving conflicts in which biological factors play an important role in establishing dominance between two or more nations or populations facing each other, paying special attention to agriculture and livestock. Regarding the possible theoretical models to analyze these conflicts, I will focus on the relationship between pure, applied science and technology, the methodological models of design sciences and ethical and moral reflection. (shrink)

“No one can serve two masters.” This Bible quotation highlights an irreducible contradiction, which echoes numerous organizational settings. This article considers the under-explored ethical implications of paradoxical injunctions created by such a contradiction at the managerial level. Contradictory organizational constraints turn into paradoxant systems , where the organization structurally settles paradoxical injunctions which challenge managerial ethics in practice. We then ask what managerial responsibility means in such contexts and find that managers have then to reshape their practice as a situated (...) construction through constant mediation between different “masters” and bricolage (i.e., tinkering with concepts). An ethnographic case study of an anti-money laundering service in an investment bank illuminates this phenomenon from a practice perspective. The possibility to enact an actual ethical practice within the contradictory organization relies on a new role of the manager. This implies drawing on an approach of responsible management as an enactment of ethics in practice which is situated within the framework of a new conception of both the organization, as a structurally “paradoxant system,” and the manager as a mediator in charge of enacting coherence. (shrink)

Although molecular biology has meant different things at different times, the term is often associated with a tendency to view cellular causation as conforming to simple linear schemas in which macro-scale effects are specified by micro-scale structures. The early achievements of molecular biologists were important for the formation of such an outlook, one to which the discovery of recombinant DNA techniques, and a number of other findings, gave new life even after the complexity of genotype–phenotype
relations had become apparent. Against this (...) background we outline how a range of scientific developments and conceptual considerations can be regarded as enabling and perhaps necessitating contemporary systems approaches. We suggest that philosophical ideas have a valuable part to play in making sense of complex scientific and disciplinary issues. (shrink)

The nature of creative engagement with computers and software presents a number of challenges to 4E cognition and requires the development of analytical frameworks that can encompass cognitive processes as they extend across material and informational realms. Here I argue that an enactive view of mind allows for better understanding of digital practice by advancing a dynamic, transactional, and affective framework for the analysis of computational design. This enactive framework is in part developed through the Material Engagement Theory put forward (...) by Lambros Malafouris, in part from the phenomenologically inspired philosophy of Bernard Stiegler. Both advance temporality, technics and technique as key to understanding human creative imagination and their work can support each other in different ways; Stiegler allows for a theorisation of digital tools largely missing from the cognitive archaeology of Malafouris, whilst Malafouris provides a cognitive theory to further develop key ideas in Stiegler’s philosophy. Bringing their work together through Gilbert Simondon’s theory of individuation, I develop the concept of enactive individuation and apply this to the analysis of a case of robotic design and fabrication from my fieldwork with digital architects and engineers. This case allows for further exploration of how enactivism might productively be extended into the digital realm by underscoring the explorative engagement at heart of even highly systematic work with computers and software. (shrink)

This paper analyzes the rapid and unexpected rise of deep learning within Artificial Intelligence and its applications. It tackles the possible reasons for this remarkable success, providing candidate paths towards a satisfactory explanation of why it works so well, at least in some domains. A historical account is given for the ups and downs, which have characterized neural networks research and its evolution from “shallow” to “deep” learning architectures. A precise account of “success” is given, in order to sieve out (...) aspects pertaining to marketing or sociology of research, and the remaining aspects seem to certify a genuine value of deep learning, calling for explanation. The alleged two main propelling factors for deep learning, namely computing hardware performance and neuroscience findings, are scrutinized, and evaluated as relevant but insufficient for a comprehensive explanation. We review various attempts that have been made to provide mathematical foundations able to justify the efficiency of deep learning, and we deem this is the most promising road to follow, even if the current achievements are too scattered and relevant for very limited classes of deep neural models. The authors’ take is that most of what can explain the very nature of why deep learning works at all and even very well across so many domains of application is still to be understood and further research, which addresses the theoretical foundation of artificial learning, is still very much needed. (shrink)

Extrapolation from a well-understood base population to a less-understood target population can fail if the base and target populations are not sufficiently similar. Differences between laboratory mice and humans, for example, can hinder extrapolation in medical research. Mice that carry a partial or complete human physiological system, known as humanized mice, are supposed to make extrapolation more reliable by simulating a variety of human diseases. But what justifies our belief that these mice are similar enough to their human counterparts to (...) simulate human disease? I argue that, unless three requirements are met in the process of humanizing mice, very little does. My requirements are not meant to provide necessary and sufficient conditions that guarantee a particular outcome. Instead, they serve as a heuristic for guiding scientific judgments involving extrapolation. In developing each requirement, I engage with philosophical issues concerning the nature of model-based science and the mechanistic approach (and its limits) to making generalizations in the life sciences. (shrink)

Many people have argued that the evolution of the human language faculty cannot be explained by Darwinian natural selection. Chomsky and Gould have suggested that language may have evolved as the by-product of selection for other abilities or as a consequence of as-yet unknown laws of growth and form. Others have argued that a biological specialization for grammar is incompatible with every tenet of Darwinian theory – that it shows no genetic variation, could not exist in any intermediate forms, confers (...) no selective advantage, and would require more evolutionary time and genomic space than is available. We examine these arguments and show that they depend on inaccurate assumptions about biology or language or both. Evolutionary theory offers clear criteria for when a trait should be attributed to natural selection: complex design for some function, and the absence of alternative processes capable of explaining such complexity. Human language meets these criteria: Grammar is a complex mechanism tailored to the transmission of propositional structures through a serial interface. Autonomous and arbitrary grammatical phenomena have been offered as counterexamples to the position that language is an adaptation, but this reasoning is unsound: Communication protocols depend on arbitrary conventions that are adaptive as long as they are shared. Consequently, language acquisition in the child should systematically differ from language evolution in the species, and attempts to analogize them are misleading. Reviewing other arguments and data, we conclude that there is every reason to believe that a specialization for grammar evolved by a conventional neo-Darwinian process. (shrink)

Defending or attacking either functionalism or computationalism requires clarity on what they amount to and what evidence counts for or against them. My goal here is not to evaluate their plausibility. My goal is to formulate them and their relationship clearly enough that we can determine which type of evidence is relevant to them. I aim to dispel some sources of confusion that surround functionalism and computationalism, recruit recent philosophical work on mechanisms and computation to shed light on them, and (...) clarify how functionalism and computationalism may or may not legitimately come together. (shrink)

Starting in the 1950s, computer programs for simulating cognitive processes and intelligent behaviour were the hallmark of Good Old-Fashioned Artificial Intelligence and ‘cognitivist’ cognitive science. This article examines a somewhat neglected case of simulation pursued by one of the founding fathers of simulation methodology, Herbert A. Simon. In the 1970s and 1980s, Simon had repeated contacts with Marxist countries and scientists, in the context of which he advanced the idea that cognitivism could be used as a framework for simulating dialectical (...) materialism. Simon's idea was, in particular, to represent dialectical processes through a ‘symbolic’ version of dialectical logic. This article explores the context of Simon's interaction with Marxist countries—China and the USSR—and also assesses the outcome of the simulation. The difficulty with simulating distinctive features of dialectical materialism is read in light of the underlying assumptions of cognitivism and, ultimately, in light of the attempt to tame a rival world view. (shrink)