Multicellular organisms contain numerous symbiotic microorganisms, collectively called microbiomes. Recently, microbiomic research has shown that these microorganisms are responsible for the proper functioning of many of the systems of multicellular organisms. This has inclined some scholars to argue that it is about time to reconceptualise the organism and to develop a concept that would place the greatest emphasis on the vital role of microorganisms in the life of plants and animals. We believe that, unfortunately, there is a problem with (...) this suggestion, since there is no such thing as a universal concept of the organism which could constitute a basis for all biological sciences. Rather, the opposite is true: numerous alternative definitions exist. Therefore, comprehending how microbiomics is changing our understanding of organisms may be a very complex matter. In this paper we will demonstrate that this pluralism proves that claims about a change in our understanding of organisms can be treated as both true and untrue. Mainly, we assert that the existing concepts differ substantially, and that only some of them have to be reconsidered in order to incorporate the discoveries of microbiomics, while others are already flexible enough to do so. Taking into account the plurality of conceptualisations within different branches of modern biology, we will conduct our discussion using the developmental and the cooperation–conflict concepts of the organism. Then we will explain our results by referring to the recent philosophical debate on the nature of the concept of the organism within biology. (shrink)

Modern life sciences research is increasingly relying on artificial intelligence (AI) approaches to model biological systems, primarily centered around the use of machine learning (ML) models. Although ML is undeniably useful for identifying patterns in large, complex data sets, its widespread application in biological sciences represents a significant deviation from traditional methods of scientific inquiry. As such, the interplay between these models and scientific understanding in biology is a topic with important implications for the future of scientific (...) research, yet it is a subject that has received little attention. Here, we draw from an epistemological toolkit to contextualize recent applications of ML in biological sciences under modern philosophical theories of understanding, identifying general principles that can guide the design and application of ML systems to model biological phenomena and advance scientific knowledge. We propose that conceptions of scientific understanding as information compression, qualitative intelligibility, and dependency relation modelling provide a useful framework for interpreting ML-mediated understanding of biological systems. Through a detailed analysis of two key application areas of ML in modern biological research – protein structure prediction and single cell RNA-sequencing – we explore how these features have thus far enabled ML systems to advance scientific understanding of their target phenomena, how they may guide the development of future ML models, and the key obstacles that remain in preventing ML from achieving its potential as a tool for biological discovery. Consideration of the epistemological features of ML applications in biology will improve the prospects of these methods to solve important problems and advance scientific understanding of living systems. (shrink)

Many philosophers are skeptical about the scientific value of the concept of biological information. However, several have recently proposed a more positive view of ascribing information as an exercise in scientific modeling. I argue for an alternative role: guiding empirical data collection for the sake of theorizing about the evolution of semantics. I clarify and expand on Bergstrom and Rosvall’s suggestion of taking a “diagnostic” approach that defines biological information operationally as a procedure for collecting empirical cases. The (...) more recent modeling-based accounts still perpetuate a theory-centric view of scientific concepts, which motivated philosophers’ misplaced skepticism in the first place. (shrink)

This chapter introduces the main research schools and paradigms along which the field of evolutionary biology has been developing. Evolutionary thinking was originally founded upon the Neo-Darwinian paradigm that combines the teachings of traditional Darwinism with those of the Modern Synthesis. The Neo-Darwinian paradigm has since further diversified into the Micro-, Meso-, and Macroevolutionary schools, and it has also started to integrate the school of Ecology. Together, these schools establish the paradigm called Ecological Evolutionary Developmental Biology (Eco-Evo-Devo). A final (...) school studies Reticulate Evolution as it occurs by means of symbiosis, symbiogenesis, lateral gene transfer, infective heredity, and hybridization. This chapter reviews the major tenets and points of differentiation that exist between these distinct evolution schools. The chapter ends by looking into how evolution can be defined and how distinct units, levels, and mechanisms underlie theorizing on evolutionary hierarchies and evolutionary causation. The following chapter examines how the different evolution schools are implemented into the symbolic sciences. (shrink)

The mathematical universe hypothesis is a theory that the physical universe is not merely described by mathematics, but is mathematics, specifically a mathematical structure. Our research provides evidence that the mathematical structure of the universe is biological in nature and all systems, processes, and objects within the universe function in harmony with biological patterns. Living organisms are the result of the universe’s biological pattern and are embedded within their physiology the patterns of this biological universe. (...) Therefore physiological patterns in living organisms can be used as models to structurally map analogies from the biological domain to any target domain to reveal and understand the biological nature of the target domain. Our paper explores various analogies, structurally mapping a red blood cell to a cup; proteins produced from ribosomes to music produced from instruments; a beating heart to the melting and freezing of Antartica; cells, tissue, organs and blood, to people, organizations, industries, and money, and; bio-economic concepts in cellular society to socioeconomic concepts in human society. It also discusses how phenomena in cellular mitosis can help explain phenomena in the universe, such as black holes, dark matter, dark energy, and the structure of the universe. Building upon the concept of perennial wisdom, our research has provided evidence that the ideas of a biological universe were expressed across many past cultures and historical periods. The implications of this theory are vast, encompassing fields such as physics, science, philosophy, religion, law, economics, politics, and engineering, thus serving as a unifying theory for all knowledge. Our theory is supported by meta-analysis of scientific, historic, and religious literature, observations and first principles logic. (shrink)

Biological research on race has often been seen as motivated by or lending credence to underlying racist attitudes; in part for this reason, recently philosophers and biologists have gone through great pains to essentially deny the existence of biological human races. We argue that human races, in the biological sense of local populations adapted to particular environments, do in fact exist; such races are best understood through the common ecological concept of ecotypes. However, human ecotypic races (...) do not in general correspond with 'folk' racial categories, largely because many similar ecotypes have multiple independent origins. Consequently, while human natural races exist, they have little or nothing in common with 'folk' races. (shrink)

Unless one embraces activities as foundational, understanding activities in mechanisms requires an account of the means by which entities in biological mechanisms engage in their activities—an account that does not merely explain activities in terms of more basic entities and activities. Recent biological research on molecular motors exemplifies such an account, one that explains activities in terms of free energy and constraints. After describing the characteristic “stepping” activities of these molecules and mapping the stages of those steps (...) onto the stages of the motors’ hydrolytic cycles, researchers pieced together from images of the molecules in different hydrolyzation states accounts of how the chemical energy in ATP is transformed in the constrained environments of the motors into the characteristic activities of the motors. We argue that New Mechanism’s standard set of analytic categories—entities, activities, and organization—should be expanded to include constraints and energetics. Not only is such an expansion required descriptively to capture research on molecular motors but, more importantly from a philosophical point of view, it enables a non-regressive account of activities in mechanisms. In other words, this expansion enables a philosophical account of mechanistic explanation that avoids a regress of entities and activities “all the way down.” Rather, mechanistic explanation bottoms out in constraints and energetics. (shrink)

Synthetic biology is a field of research that concentrates on the design, construction, and modification of new biomolecular parts and metabolic pathways using engineering techniques and computational models. By employing knowledge of operational pathways from engineering and mathematics such as circuits, oscillators, and digital logic gates, it uses these to understand, model, rewire, and reprogram biological networks and modules. Standard biological parts with known functions are catalogued in a number of registries (e.g. Massachusetts Institute of Technology Registry (...) of Standard Biological Parts). Biological parts can then be selected from the catalogue and assembled in a variety of combinations to construct a system or pathway in a microbe. Through the innovative re-engineering of biological circuits and the optimization of certain metabolic pathways, biological modules can be designed to reprogram organisms to produce products or behaviors. Synthetic biology is what is known as a “platform technology”. That is, it generates highly transferrable theoretical models, engineering principles, and know-how that can be applied to create potential products in a wide variety of industries. Proponents suggest that applications of synthetic biology may be able to provide scientific and engineered solutions to a multitude of worldwide problems from health to energy. Synthetic biology research has already been successful in constructing microbial products which promise to offer cheaper pharmaceuticals such as the antimalarial synthetic drug artemisinin, engineered microbes capable of cleaning up oil spills, and the engineering of biosensors that can detect the presence of high concentrations of arsenic in drinking water. One of the potential benefits of synthetic biology research is in its application to biofuel production. It is this application which is the focus of this entry. The term “biofuel” has referred generally to all liquid fuels that are sourced from plant or plant byproducts and are used for energy necessary for transportation vehicles (Thompson 2012). Biofuels that are produced using synthetic biological techniques re-engineer microbes into biofuel factories are a subset of these. (shrink)

The new mechanists and the autonomy approach both aim to account for how biological phenomena are explained. One identifies appeals to how components of a mechanism are organized so that their activities produce a phenomenon. The other directs attention towards the whole organism and focuses on how it achieves self-maintenance. This paper discusses challenges each confronts and how each could benefit from collaboration with the other: the new mechanistic framework can gain by taking into account what happens outside individual (...) mechanisms, while the autonomy approach can ground itself in biological research into how the actual components constituting an autonomous system interact and contribute in different ways to realize and maintain the system. To press the case that these two traditions should be constructively integrated we describe how three recent developments in the autonomy tradition together provide a bridge between the two traditions: (1) a framework of work and constraints, (2) a conception of function grounded in the organization of an autonomous system, and (3) a focus on control. (shrink)

Waters’s (2007) actual difference making and Weber’s (2013, 2017) biological normality approaches to causal selection have received many criticisms, some of which miss their target. Disagreement about whether Waters’s and Weber’s views succeed in providing criteria that uniquely singles out the gene as explanatorily significant in biology has led philosophers to overlook a prior problem. Before one can address whether Waters’s and Weber’s views successfully account for the explanatory significance of genes, one must ask whether either view satisfactorily meets (...) the necessary conditions for causal selection in the first place. An adequate defense of causal selection must meet two desiderata. First, there must be an explanatory property that sets some causes apart from others. Second, the property identified must be one that is recognized by biologists as relevant to their domain(s) of inquiry. I argue that both fall short of meeting the second condition. I demonstrate this by showing how many of the biological technologies crucial to experimentation do not fit either view very well. I offer a more adequate proposal that accommodates non-actual and artificial causal variables. A consequence of my view is the following: When analyzing the causal selection practices of biologists, philosophers should consider the explanatory targets relevant to a research program – including ones whose explanans must appeal to biological technologies. I then explain how this proposal can inform the existing debate between Weber (2017) and Griffiths et al. (2015). (shrink)

The theory of evolution, which provides the conceptual framework for all modern research in organismal biology and informs research in molecular bi- ology, has gone through several stages of expansion and refinement. Darwin and Wallace (1858) of course proposed the original idea, centering on the twin concepts of natural selection and common descent. Shortly thereafter, Wallace and August Weismann worked toward the complete elimination of any Lamarckian vestiges from the theory, leaning in particular on Weismann’s (1893) concept of (...) the separation of soma and germ, resulting in what is some- times referred to as “neo-Darwinism”. (shrink)

In recent years, a proliferation of books about empathy, cooperation and pro-social behaviours (Brooks, 2011a) has significantly influenced the discourse of the life-sciences and reversed consolidated views of nature as a place only for competition and aggression. In this article I describe the recent contribution of three disciplines – moral psychology (Jonathan Haidt), primatology (Frans de Waal) and the neuroscience of morality – to the present transformation of biology and evolution into direct sources of moral phenomena, a process here named (...) the ‘moralization of biology’. I conclude by addressing the ambivalent status of this constellation of authors, for whom today ‘morality comes naturally’: I explore both the attractiveness of their message, and the problematic epistemological assumptions of their research programmes in the light of new discoveries in developmental and molecular biology. (shrink)

This article argues for an epistemology of music, stating that dealing with music can be considered as a process of knowledge acquisition. What really matters is not the representation of an ontological musical reality, but the generation of music knowledge as a tool for adaptation to the sonic world. Three major positions are brought together: the epistemological claims of Jean Piaget, the biological methodology of Jakob von Uexküll, and the constructivistic conceptions of Ernst von Glasersfeld, each ingstress the role (...) of the music user rather than the music. Dealing with music, in this view, is not a matter of representation, but a process of semiotization of the sonorous environment as the outcome of interactions with the sound. Hence the role of enactive cognition and perceptual-motor interaction with the sonic environment. What is considered a central issue is the way how listeners as subjects experience their own phenomenal world or Umwelt, and how they can make sense out of their sonic environment. Umwelt-research, therefore, is highly relevant for music education in stressing the role of the listener and his/her listening strategies. (shrink)

Synthetic biology aims to synthesize novel biological systems or redesign existing ones. The field has raised numerous philosophical questions, but most especially what is novel to this field. In this article I argue for a novel take, since the dominant ways to understand synthetic biology’s specificity each face problems. Inspired by the examination of the work of a number of chemists, I argue that synthetic biology differentiates itself by a new regime of articulation, i.e. a new way of articulating (...) the questions and phenomena it wants to address. Instead of describing actual existing biological systems, the field aims to describe biological possibilities. In the second part I corroborate this hypothesis through a comparison between early research in the field of the origins of life and contemporary synthetic biologists, who are not so much interested in the historical origin of life on Earth, but rather in a universal biology of the possible origins of any life whatsoever. (shrink)

This paper adds to the philosophical literature on mechanistic explanation by elaborating two related explanatory functions of idealisation in mechanistic models. The first function involves explaining the presence of structural/organizational features of mechanisms by reference to their role as difference-makers for performance requirements. The second involves tracking counterfactual dependency relations between features of mechanisms and features of mechanistic explanandum phenomena. To make these functions salient, we relate our discussion to an exemplar from systems biological research on the mechanism (...) for countering heat shock—the heat shock response system—in Escherichia coli bacteria. This research also reinforces a more general lesson: ontic constraint accounts in the literature on mechanistic explanation provide insufficiently informative normative appraisals of mechanistic models. We close by outlining an alternative view on the explanatory norms governing mechanistic representation. (shrink)

This paper examines two parallel discussions of scientific modeling which have invoked experimentation in addressing the role of models in scientific inquiry. One side discusses the experimental character of models, whereas the other focuses on their exploratory uses. Although both relate modeling to experimentation, they do so differently. The former has considered the similarities and differences between models and experiments, addressing, in particular, the epistemic value of materiality. By contrast, the focus on exploratory modeling has highlighted the various kinds of (...) exploratory functions of models in the early stages of inquiry. These two perspectives on modeling are discussed through a case study in the field of synthetic biology. The research practice in question explores biological control by making use of an ensemble of different epistemic means: mathematical models and simulations, synthetic genetic circuits and intracellular measuring devices, and finally electronic circuits. We argue that the study of exploratory modeling should trace the ways different epistemic means, in different materialities, are being combined over time. Finally, the epistemic status of such novel investigative objects as synthetic genetic circuits is evaluated, with the conclusion that they can function as both experiments and models. (shrink)

Modeling mechanisms is central to the biological sciences – for purposes of explanation, prediction, extrapolation, and manipulation. A closer look at the philosophical literature reveals that mechanisms are predominantly modeled in a purely qualitative way. That is, mechanistic models are conceived of as representing how certain entities and activities are spatially and temporally organized so that they bring about the behavior of the mechanism in question. Although this adequately characterizes how mechanisms are represented in biology textbooks, contemporary biological (...) research practice shows the need for quantitative, probabilistic models of mechanisms, too. In this paper we argue that the formal framework of causal graph theory is well-suited to provide us with models of biological mechanisms that incorporate quantitative and probabilistic information. On the ba-sis of an example from contemporary biological practice, namely feedback regulation of fatty acid biosynthesis in Brassica napus, we show that causal graph theoretical models can account for feedback as well as for the multi-level character of mechanisms. However, we do not claim that causal graph theoretical representations of mechanisms are advantageous in all respects and should replace common qualitative models. Rather, we endorse the more balanced view that causal graph theoretical models of mechanisms are useful for some purposes, while being insufficient for others. (shrink)

One important aspect of biological explanation is detailed causal modeling of particular phenomena in limited experimental background conditions. Recognising this allows a new avenue for intertheoretic reduction to be seen. Reductions in biology are possible, when one fully recognises that a sufficient condition for a reduction in biology is a molecular model of 1) only the demonstrated causal parameters of a biological model and 2) only within a replicable experimental background. These intertheoretic identifications –which are ubiquitous in biology (...) and form the basis of ruthless reductions (Bickle 2003)- are criticised as merely “local” (Sullivan 2009) or “fragmentary” (Schaffner 2006). However, in an instructive case, a biological model is preserved in molecular terms, and a complex biological phenomenon has been successfully reduced. In doing this the molecular model remains valid in a broader range of background conditions and meaningfully unites disparate biological phenomena. (shrink)

Statistics play a critical role in biological and clinical research. However, most reports of scientific results in the published literature make it difficult for the reader to reproduce the statistical analyses performed in achieving those results because they provide inadequate documentation of the statistical tests and algorithms applied. The Ontology of Biological and Clinical Statistics (OBCS) is put forward here as a step towards solving this problem. Terms in OBCS, including ‘data collection’, ‘data transformation in statistics’, ‘data (...) visualization’, ‘statistical data analysis’, and ‘drawing a conclusion based on data’, cover the major types of statistical processes used in basic biological research and clinical outcome studies. OBCS is aligned with the Basic Formal Ontology (BFO) and extends the Ontology of Biomedical Investigations (OBI), an OBO (Open Biological and Biomedical Ontologies) Foundry ontology supported by over 20 research communities. We discuss two examples illustrating how the ontology is being applied. In the first (biological) use case, we describe how OBCS was applied to represent the high throughput microarray data analysis of immunological transcriptional profiles in human subjects vaccinated with an influenza vaccine. In the second (clinical outcomes) use case, we applied OBCS to represent the processing of electronic health care data to determine the associations between hospital staffing levels and patient mortality. Our case studies were designed to show how OBCS can be used for the consistent representation of statistical analysis pipelines under two different research paradigms. By representing statistics-related terms and their relations in a rigorous fashion, OBCS facilitates standard data analysis and integration, and supports reproducible biological and clinical research. (shrink)

We characterize access to empirical objects in biology from a theoretical perspective. Unlike objects in current physical theories, biological objects are the result of a history and their variations continue to generate a history. This property is the starting point of our concept of measurement. We argue that biological measurement is relative to a natural history which is shared by the different objects subjected to the measurement and is more or less constrained by biologists. We call symmetrization the (...) theoretical and often concrete operation which leads to considering biological objects as equivalent in a measurement. Last, we use our notion of measurement to analyze research strategies. Some strategies aim to bring biology closer to the epistemology of physical theories, by studying objects as similar as possible, while others build on biological diversity. (shrink)

We have been left with a big challenge, to articulate consciousness and also to prove it in an artificial agent against a biological standard. After introducing Boltuc’s h-consciousness in the last paper, we briefly reviewed some salient neurology in order to sketch less of a standard than a series of targets for artificial consciousness, “most-consciousness” and “myth-consciousness.” With these targets on the horizon, we began reviewing the research program pursued by Jun Tani and colleagues in the isolation of (...) the formal dynamics essential to either. In this paper, we describe in detail Tani’s research program, in order to make the clearest case for artificial consciousness in these systems. In the next paper, the third in the series, we will return to Boltuc’s naturalistic non-reductionism in light of the neurorobotics models introduced (alongside some others), and evaluate them more completely. (shrink)

Culture or Biology? The question can seem deep and important. Yet, I argue in this chapter, if you are enthralled by questions about our biological differences, then you are probably confused. My goal is to diagnose the confusion. In debates about the role of biology in the social world it is easy to ask the wrong questions, and it is easy to misinterpret the scientific research. We are intuitively attracted to what is called psychological essentialism, and therefore interpret (...) what is biological as what can be traced to “essences”. On this interpretation, it would be deep and important to know what about, say, the differences between the genders is biological: it would correspond to what is essential to being a man or being a woman, and be opposed to what is a mere accidental feature that some women or some men have. Yet, the psychological essentialist understanding of ‘biological differences’ is deeply mistaken about biology. It has the wrong conception of biological kinds, of biological heritability, and of how genes and hormones work. Those who argue for an important role of ‘biology’ in the explanation of human differences often see ‘the science’ on their side. But this is false – on the interpretation of ‘biological differences’ that is most intuitive and that makes the question appear to be most interesting. Defenders of ‘biology’ often have the science against them. What is often called ‘biology’ is a myth: a myth created by an intuitive tendency that grotesquely distorts real biological research. (shrink)

Biosemiotics is a growing fi eld that investigates semiotic processes in the living realm in an attempt to combine the fi ndings of the biological sciences and semiotics. Semiotic processes are more or less what biologists have typically referred to as “ signals, ” “ codes, ”and “ information processing ”in biosystems, but these processes are here understood under the more general notion of semiosis, that is, the production, action, and interpretation of signs. Thus, biosemiotics can be seen as (...) biology interpreted as a study of living sign systems — which also means that semiosis or sign process can be seen as the very nature of life itself. In other words, biosemiotics is a field of research investigating semiotic processes (meaning, signification, communication, and habit formation in living systems) and the physicochemical preconditions for sign action and interpretation. -/- (...). (shrink)

Cross cultural studies have played a pivotal role in elucidating the extent to which behavioral and mental characteristics depend on specific environmental influences. Surprisingly, little field research has been carried out on a fundamentally important perceptual ability, namely the perception of biological motion. In this report, we present details of studies carried out with the help of volunteers from the Mundurucu indigene, a group of people native to Amazonian territories in Brazil. We employed standard biological motion perception (...) tasks inspired by over 30 years of laboratory research, in which observers attempt to decipher the walking direction of point-light (PL) humans and animals. Do our effortless skills at perceiving biological activity from PL animations, as revealed in laboratory settings, generalize to people who have never before seen representational depictions of human and animal activity? The results of our studies provide a clear answer to this important, previously unanswered question. Mundurucu observers readily perceived the coherent, global shape depicted in PL walkers, and experienced the classic inversion effects that are typically found when such stimuli are turned upside down. In addition, their performance was in accord with important recent findings in the literature, in the abundant ease with which they extracted direction information from local motion invariants alone. We conclude that the effortless, veridical perception of PL biological motion is a spontaneous and universal perceptual ability, occurring both inside and outside traditional laboratory environments. (shrink)

Research in ecology and evolutionary biology (evo-eco) often tries to emulate the “hard” sciences such as physics and chemistry, but to many of its practitioners feels more like the “soft” sciences of psychology and sociology. I argue that this schizophrenic attitude is the result of lack of appreciation of the full consequences of the peculiarity of the evo-eco sciences as lying in between a-historical disciplines such as physics and completely historical ones as like paleontology. Furthermore, evo-eco researchers have gotten (...) stuck on mathematically appealing but philosophi- cally simplistic concepts such as null hypotheses and p-values defined according to the frequentist approach in statistics, with the consequence of having been unable to fully embrace the complexity and subtlety of the problems with which ecologists and evolutionary biologists deal with. I review and discuss some literature in ecology, philosophy of science and psychology to show that a more critical methodological attitude can be liberating for the evo-eco scientist and can lead to a more fecund and enjoyable practice of ecology and evolutionary biology. With this aim, I briefly cover concepts such as the method of multiple hypotheses, Bayesian analysis, and strong inference. (shrink)

This third paper locates the synthetic neurorobotics research reviewed in the second paper in terms of themes introduced in the first paper. It begins with biological non-reductionism as understood by Searle. It emphasizes the role of synthetic neurorobotics studies in accessing the dynamic structure essential to consciousness with a focus on system criticality and self, develops a distinction between simulated and formal consciousness based on this emphasis, reviews Tani and colleagues' work in light of this distinction, and ends (...) by forecasting the increasing importance of synthetic neurorobotics studies for cognitive science and philosophy of mind going forward, finally in regards to most- and myth-consciousness. (shrink)

In the framework of materialism, the major attention is to find general organizational laws stimulated by physical sciences, ignoring the uniqueness of Life. The main goal of materialism is to reduce consciousness to natural processes, which in turn can be translated into the language of math, physics and chemistry. Following this approach, scientists have made several attempts to deny the living organism of its veracity as an immortal soul, in favor of genes, molecules, atoms and so on. However, advancement in (...) various fields of biology has repeatedly given rise to questions against such a denial and has supplied more and more evidence against the completely misleading ideological imposition that living entities are particular states of matter. In the recent past, however, the realization has arisen that cognitive nature of life at all levels has begun presenting significant challenges to the views of materialism in biology and has created a more receptive environment for the soul hypothesis. Therefore, instead of adjudicating different aprioristic claims, the development of an authentic theory of biology needs both proper scientific knowledge and the appropriate tools of philosophical analysis of life. In a recently published paper the first author of present essay made an attempt to highlight a few relevant developments supporting a sentient view of life in scientific research, which has caused a paradigm shift in our understanding of life and its origin [1]. The present essay highlights the uniqueness of biological systems that offers a considerable challenge to the mainstream materialism in biology and proposes the Vedāntic philosophical view as a viable alternative for development of a biological theory worthy of life. (shrink)

Direct neurological and especially imaging-driven investigations into the structures essential to naturally occurring cognitive systems in their development and operation have motivated broadening interest in the potential for artificial consciousness modeled on these systems. This first paper in a series of three begins with a brief review of Boltuc’s (2009) “brain-based” thesis on the prospect of artificial consciousness, focusing on his formulation of h-consciousness. We then explore some of the implications of brain research on the structure of consciousness, finding (...) limitations in biological approaches to the study of consciousness. Looking past these limitations, we introduce research in artificial consciousness designed to test for the emergence of consciousness, a phenomenon beyond the purview of the study of existing biological systems. (shrink)

As a sort of intellectual provocation and as a lateral thinking strategy for creativity, this chapter seeks to determine what the study of the dynamics of biodiversity can offer linguists. In recent years, the analogical equation "language = biological species" has become more widespread as a metaphorical source for conceptual renovation, and, at the same time, as a justification for the defense of language diversity. Language diversity would be protected in a way similar to the mobilization that has taken (...) place to protect endangered species. Nevertheless, one must be careful when uncritically transferring conceptualizations and theoretical frameworks from one field to another, since obviously, these two phenomena are quite different in the real world. The dialogue with bioecologists starts by asking about the formation of diversity, i.e., about specialization. Here, one can observe the similarity between the processes of linguistic and genetic fragmentation, in the sense that both phenomena have a (socio)geographical basis for dispersion and consequently, for the loss of their original compact nature and their intercommunication. The self-organizing and creative properties of human beings favor the development of specific varieties for each subset, varieties that continue to evolve constantly, through the unceasing "languaging" of humanity. Regarding the continuity of species or languages, one can also observe the decisive role of intragroup relations. The staying power of linguistic varieties will increase in direct proportion to the intensity of the relationship among the components of the subset. On the other hand, if exotic elements are introduced, especially if these elements are aggressive in nature, the alteration of the ecological niche may turn out to be fatal for the continuity of the previously existing forms. This suggests to us the need to make an in-depth study of what the minimal contextual conditions would be so that a set linguistic group could be assured a sustainable continuity within a framework of linguistic contact. What type of minimum (socio-)ecological niche would a language have to have if we wished to ensure its habitual reproduction? A proposal is made here to explore the ideas of "exclusive functions" and "non-hierarchical functional distribution" for codes in situations where there is high contact and a danger of disuse. As regards change, this phenomenon is seen as an inherent element in the tendency of life to create new developments, which may or not be accompanied by an adaptation to changing environmental conditions. It is pointed out that, similar to what happens in biology, much of linguistic innovation stems from a systemically reorganized mixture of solutions from different codes. An important research question would be, however, to determine why some of these innovations disappear and others survive and extend throughout the community. The big question mark, as Mufwene points out, is, then how to manage to understand how "the evolution of language proceeds by naturally selecting from among the competing alternatives available through the idiolects of individual speakers". Extinction, whether it be of languages or of species, is caused in most cases "by a combination of demographic processes and environmental changes", as Brown points out. Thus, the environment plays a fundamental role in the direction of evolution, since the "the survival of the fittest is, in actuality, the survival of those who fit into the context (Allen and Hoekstra)". This allows us to see the great degree of importance of political-economic contexts in the case of languages. In the same way, migratory movements are also one of the major variables determining the extinction of biodiversity and language diversity. Species and habitat form the basic unit of existence, and this is the major point of departure for understanding the problem of the preservation and recovery of species or languages. Given the increase in the degree of linguistic contact, the continuity of language diversity depends on determining, as exactly as possible, as Prigogine, the physicist, would say, what precise conditions of imbalance may prove to be stable. The great challenge is not so much avoiding contact but managing it. And "restorative ecology" can also be of help to us here. Being able to reach sustainable solutions for language diversity implies a profound knowledge of the dynamics for determining the ways in which language is used in contact situations. The general conclusion is that linguistics is still terminologically and conceptually ill prepared to deal with the dynamic character of human languages. The world and our objects must be conceived of as elements in a state of flux, as changing systems in an unstable equilibrium. With respect to language policy, it would be necessary to make an effort to manage to establish some general principles regarding the linguistic organization of the human species that would make it possible for local linguistic diversity and communication on a planetary scale, which must necessarily take place, to be compatible with each other. To succeed, it will be necessary to continue promoting an autonomous socio-ecological perspective devoted to the comprehension of language phenomena. Such a perspective would be based on a paradigm of complexity, and would, at the same time, place human beings at the center of its theoretical underpinnings. (shrink)

To identify and conceptualize research problems in science, philosophers and often scientists rely on classical accounts of problems that focus on intellectual problems defined in relation to theories. Recently, philosophers have begun to study the structures and functions of research problems not defined in relation to theories. Furthermore, scientists have long pursued research problems often labeled as practical or applied. As yet, no account of problems specifies the description of both so-called intellectual problems and so-called applied problems. (...) This article proposes a new conceptual framework of problems that accounts both for intellectual aspects of problems and for their practical or applied aspects. I illustrate the account with an example of a recent research project from evolutionary biology, and I indicate further routes by that to develop the account, especially in connection to empirical studies of science. (shrink)

Biological individuality is a notoriously thorny topic for biologists and philosophers of biology. In this paper we argue that biological individuality presents multiple, interconnected questions for biologists and philosophers that together form a problem agenda. Using a case study of an interdisciplinary research group in ecology, behavioral and evolutionary biology, we claim that a debate on biological individuality that seeks to account for diverse practices in the biological sciences should be broadened to include and give (...) prominence to questions about uniqueness and temporality. We show that broadening the problem agenda of biological individuality draws attention to underrecognized philosophical issues and discussions and thereby organizes and enriches the existing debate. (shrink)

A classic analytic approach to biological phenomena seeks to refine definitions until classes are sufficiently homogenous to support prediction and explanation, but this approach founders on cases where a single process produces objects with similar forms but heterogeneous behaviors. I introduce object spaces as a tool to tackle this challenging diversity of biological objects in terms of causal processes with well-defined formal properties. Object spaces have three primary components: (1) a combinatorial biological process such as protein synthesis (...) that generates objects with parts that are modular, independent, and organized according to an invariant syntax; (2) a notion of “distance” that relates the objects according to rules of change over time as found in nature or useful for algorithms; (3) mapping functions defined on the space that map its objects to other spaces or apply an evaluative criterion to measure an important quality, such as parsimony or biochemical function. Once defined, an object space can be used to represent and simulate the dynamics of phenomena on multiple scales; it can also be used as a tool for predicting higher-order properties of the objects, including stitching together series of causal processes. Object spaces are the basis for a strategy of theorizing, discovery, and analysis in biology: as heuristic idealizations of biology, they help us transform inchoate, intractable problems into articulated, well-structured ones. Developing an object space is a research strategy with a long, successful history under many other names, and it offers a unifying but not overreaching approach to biological theory. (shrink)

Clark and Chalmers claim that an external resource satisfying the following criteria counts as a memory: the agent has constant access to the resource; the information in the resource is directly available; retrieved information is automatically endorsed; information is stored as a consequence of past endorsement. Research on forgetting and metamemory shows that most of these criteria are not satisfied by biological memory, so they are inadequate. More psychologically realistic criteria generate a similar classification of standard putative external (...) memories, but the criteria still do not capture the function of memory. An adequate account of memory function, compatible with its evolution and its roles in prospection and imagination, suggests that external memory performs a function not performed by biological memory systems. External memory is thus not memory. This has implications for: extended mind theorizing, ecological validity of memory research, the causal theory of memory. (shrink)

In this study, I aimed to subject to philosophical analysis the scientific data from biological science researches that are conducted into the phenomenon of homosexuality in order to give philosophical interpretation to it thereby establishing the normative values of the scientific findings. From the study, I observed that much of the scientific data on homosexuality established the phenomenon as ingrained in the human biological construct. I argued that although homoeroticism is biological construct of the homosexual, parenting plays (...) significant role in the sexual identity ultimately developed by an individual. I have presented three conceptual frameworks to show how this happens. I determined that homoeroticism and homosexuality are not exactly the same thing; homoeroticism is a biological construct, while homosexuality is a social construct. I also determine that sexual orientation (which results from eros) is not necessarily the same thing as sexual identity (such as homosexuality or heterosexuality, which results from socialization processes). I argued that sexuality is a synthesis of dialectical interactions between the factors internal within and external to the homosexual’s body; but that the external is conditioned by the internal. I adopted the paradigm of existentialism as the philosophical framework for the analysis. In conclusion, I argued that if the homosexual’s sexual orientation is native biological construct of his/her body, then the homosexual has no control over his/her sexual orientation. The philosophical implication of that finding is that homoeroticism is facticity; and as facticity the homosexual cannot escape from being homosexual. Despite this, I used the Two-Way Test (TWT) to show that homosexuality is immoral act; although the homosexual is not an immoral person. However, I have demonstrated that the failed moral status of homosexuality is not enough ground to criminalize homosexuality. (shrink)

On most accounts, beliefs are supposed to fit the world rather than change it. But believing can have social consequences, since the beliefs we form underwrite our actions and impact our character. Because our beliefs affect how we live our lives and how we treat other people, it is surprising how little attention is usually given to the moral status of believing apart from its epistemic justification. In what follows, I develop a version of the harm principle that applies to (...) beliefs as well as actions. In doing so, I challenge the often exaggerated distinction between forming beliefs and acting on them.1 After developing this view, I consider what it might imply about controversial research the goal of which is to yield true beliefs but the outcome of which might include negative social consequences. In particular, I focus on the implications of research into biological differences between racial groups. (shrink)

As biological and biomedical research increasingly reference the environmental context of the biological entities under study, the need for formalisation and standardisation of environment descriptors is growing. The Environment Ontology (ENVO) is a community-led, open project which seeks to provide an ontology for specifying a wide range of environments relevant to multiple life science disciplines and, through an open participation model, to accommodate the terminological requirements of all those needing to annotate data using ontology classes. This paper (...) summarises ENVO’s motivation, content, structure, adoption, and governance approach. (shrink)

This essay is a defense of the social construction of racialism. I follow a standard definition of “racialism” which is the belief that “there are heritable characteristics, possessed by members of our species, that allow us to divide them into a small set of races, in such a way that all the members of these races share certain traits and tendencies with each other that they do not share with other members of any other race”. In particular I want to (...) defend the “radical” social-constructive thesis that holds “the concept of race is exclusively the product of historical and cultural causes. It claims that humans do not tend to classify people into races when groups with different phenotypes meet, save for particular historical circumstances”. The quoted position is the consensus view among historians, sociologists, anthropologists, and other social scientists who study racialism but has recently been criticized by philosophical defenders of cognitive/evolutionary psychological approaches to racialism. Drawing on developmental studies as well as historical and contemporary cross-cultural research, CEP philosophers point to similarities of racialism across time and space. They hold that social constructionist approaches to racialism cannot explain these similarities. I hold that SC approaches do explain these similarities and that such similarities actually pose a significant challenge to the proposed CEP research program on racialism. (shrink)

Philosophy of biology is often said to have emerged in the last third of the twentieth century. Prior to this time, it has been alleged that the only authors who engaged philosophically with the life sciences were either logical empiricists who sought to impose the explanatory ideals of the physical sciences onto biology, or vitalists who invoked mystical agencies in an attempt to ward off the threat of physicochemical reduction. These schools paid little attention to actual biological science, and (...) as a result philosophy of biology languished in a state of futility for much of the twentieth century. The situation, we are told, only began to change in the late 1960s and early 1970s, when a new generation of researchers began to focus on problems internal to biology, leading to the consolidation of the discipline. In this paper we challenge this widely accepted narrative of the history of philosophy of biology. We do so by arguing that the most important tradition within early twentieth-century philosophy of biology was neither logical empiricism nor vitalism, but the organicist movement that flourished between the First and Second World Wars. We show that the organicist corpus is thematically and methodologically continuous with the contemporary literature in order to discredit the view that early work in the philosophy of biology was unproductive, and we emphasize the desirability of integrating the historical and contemporary conversations into a single, unified discourse. (shrink)

Statistics play a critical role in biological and clinical research. To promote logically consistent representation and classification of statistical entities, we have developed the Ontology of Biological and Clinical Statistics (OBCS). OBCS extends the Ontology of Biomedical Investigations (OBI), an OBO Foundry ontology supported by some 20 communities. Currently, OBCS contains 686 terms, including 381 classes imported from OBI and 147 classes specific to OBCS. The goal of this paper is to present OBCS for community critique and (...) to describe a number of use cases designed to illustrate its potential applications. The OBCS project and source code are available at http://obcs.googlecode.com. (shrink)

The term “Complex Systems Biology” was introduced a few years ago [Kaneko, 2006] and, although not yet of widespread use, it seems particularly well suited to indicate an approach to biology which is well rooted in complex systems science. Although broad generalizations are always dangerous, it is safe to state that mainstream biology has been largely dominated by a gene-centric view in the last decades, due to the success of molecular biology. So the one gene - one trait approch, which (...) has often proved to be effective, has been extended to cover even complex traits. This simplifying view has been appropriately criticized, and the movement called systems biology has taken off. Systems biology [Noble, 2006] emphasizes the presence of several feedback loops in biological systems, which severely limit the range of validity of explanations based upon linear causal chains (e.g. gene → behaviour). Mathematical modelling is one the favourite tools of systems biologists to analyze the possible effects of competing negative and positive feedback loops which can be observed at several levels (from molecules to organelles, cells, tissues, organs, organisms, ecosystems). Systems biology is by now a well-established field, as it can be inferred by the rapid growth in number of conferences and journals devoted to it, as well as by the existence of several grants and funded projects.Systems biology is mainly focused upon the description of specific biological items, like for example specific organisms, or specific organs in a class of animals, or specific genetic-metabolic circuits. It therefore leaves open the issue of the search for general principles of biological organization, which apply to all living beings or to at least to broad classes. We know indeed that there are some principles of this kind, biological evolution being the most famous one. The theory of cellular organization also qualifies as a general principle. But the main focus of biological research has been that of studying specific cases, with some reluctance to accept (and perhaps a limited interest for) broad generalizations. This may however change, and this is indeed the challenge of complex systems biology: looking for general principles in biological systems, in the spirit of complex systems science which searches for similar features and behaviours in various kinds of systems. The hope to find such general principles appears well founded, and I will show in Section 2 that there are indeed data which provide support to this claim. Besides data, there are also general ideas and models concerning the way in which biological systems work. The strategy, in this case, is that of introducing simplified models of biological organisms or processes, and to look for their generic properties: this term, borrowed from statistical physics, is used for those properties which are shared by a wide class of systems. In order to model these properties, the most effective approach has been so far that of using ensembles of systems, where each member can be different from another one, and to look for those properties which are widespread. This approach was introduced many years ago [Kauffman, 1971] in modelling gene regulatory networks. At that time one had very few information about the way in which the expression of a given gene affects that of other genes, apart from the fact that this influence is real and can be studied in few selected cases (like e.g. the lactose metabolism in E. coli). Today, after many years of triumphs of molecular biology, much more has been discovered, however the possibility of describing a complete map of gene-gene interactions in a moderately complex organism is still out of reach. Therefore the goal of fully describing a network of interacting genes in a real organism could not be (and still cannot be) achieved. But a different approach has proven very fruitful, that of asking what are the typical properties of such a set of interacting genes. Making some plausible hypotheses and introducing some simplifying assumptions, Kauffman was able to address some important problems. In particular, he drew attention to the fact that a dynamical system of interacting genes displays selforganizing properties which explain some key aspects of life, most notably the existence of a limited number of cellular types in every multicellular organism (these numbers are of the order of a few hundreds, while the number of theoretically possible types, absent interactions, would be much much larger than the number of protons in the universe). In section 3 I will describe the ensemble based approach in the context of gene regulatory networks, and I will show that it can describe some important experimental data. Finally, in section 4 I will discuss some methodological aspects. (shrink)

The biological sciences study (bio)complex living systems. Research directed at the mechanistic explanation of the "live" state truly requires a pluralist research program, i.e. BioComplexity research. The program should apply multiple intra-level and inter-level theories and methodologies. We substantiate this thesis with analysis of BioComplexity: metabolic and modular control analysis of metabolic pathways, emergence of oscillations, and the analysis of the functioning of glycolysis.

One of biology's fundamental aims is to generate understanding of the living world around—and within—us. In this chapter, I aim to provide a relatively nonpartisan discussion of the nature of explanation in biology, grounded in widely shared philosophical views about scientific explanation. But this discussion also reflects what I think is important for philosophers and biologists alike to appreciate about successful scientific explanations, so some points will be controversial, at least among philosophers. I make three main points: (1) causal relationships (...) and broad patterns have often been granted importance to scientific explanations, and they are in fact both important; (2) some explanations in biology cite the components of or processes in systems that account for the systems’ features, whereas other explanations feature large-scale or structural causes that influence a system; and (3) there can be multiple different explanations of a given biological phenomenon, explanations that respond to different research aims and can thus be compatible with one another even when they may seem to disagree. (shrink)

Research studies increasingly use genomic sequencing to draw inferences based on comparisons between the genetic data of a set of purportedly related individuals. As use of this method progresses, it will become much more common to discover that the assumed biological relationships between the individuals are mistaken. Consequently, researchers will have to grapple with decisions about whether to return incidental findings of misattributed parentage on a much larger scale than ever before. In this paper we provide an extended (...) argument for the view that the default position for researchers ought to be the non-disclosure of misattributed parentage. (shrink)

The scientific study of living organisms is permeated by machine and design metaphors. Genes are thought of as the ‘‘blueprint’’ of an organism, organisms are ‘‘reverse engineered’’ to discover their func- tionality, and living cells are compared to biochemical factories, complete with assembly lines, transport systems, messenger circuits, etc. Although the notion of design is indispensable to think about adapta- tions, and engineering analogies have considerable heuristic value (e.g., optimality assumptions), we argue they are limited in several important respects. In (...) particular, the analogy with human-made machines falters when we move down to the level of molecular biology and genetics. Living organisms are far more messy and less transparent than human-made machines. Notoriously, evolution is an oppor- tunistic tinkerer, blindly stumbling on ‘‘designs’’ that no sensible engineer would come up with. Despite impressive technological innovation, the prospect of artificially designing new life forms from scratch has proven more difficult than the superficial analogy with ‘‘programming’’ the right ‘‘software’’ would sug- gest. The idea of applying straightforward engineering approaches to living systems and their genomes— isolating functional components, designing new parts from scratch, recombining and assembling them into novel life forms—pushes the analogy with human artifacts beyond its limits. In the absence of a one-to-one correspondence between genotype and phenotype, there is no straightforward way to imple- ment novel biological functions and design new life forms. Both the developmental complexity of gene expression and the multifarious interactions of genes and environments are serious obstacles for ‘‘engi- neering’’ a particular phenotype. The problem of reverse-engineering a desired phenotype to its genetic ‘‘instructions’’ is probably intractable for any but the most simple phenotypes. Recent developments in the field of bio-engineering and synthetic biology reflect these limitations. Instead of genetically engi- neering a desired trait from scratch, as the machine/engineering metaphor promises, researchers are making greater strides by co-opting natural selection to ‘‘search’’ for a suitable genotype, or by borrowing and recombining genetic material from extant life forms. (shrink)

Policies that require male-female sex comparisons in all areas of biomedical research conflict with the goal of improving health outcomes through context-sensitive individualization of medical care. Sex, like race, requires a rigorous, contextual approach in precision medicine. A “sex contextualist” approach to gender-inclusive medicine better aligns with this aim.

Intelligence in current AI research is measured according to designer-assigned tasks that lack any relevance for an agent itself. As such, tasks and their evaluation reveal a lot more about our intelligence than the possible intelligence of agents that we design and evaluate. As a possible first step in remedying this, this article introduces the notion of “self-concern,” a property of a complex system that describes its tendency to bring about states that are compatible with its continued self-maintenance. Self-concern, (...) as argued, is the foundation of the kind of basic intelligence found across all biological systems, because it reflects any such system's existential task of continued viability. This article aims to cautiously progress a few steps closer to a better understanding of some necessary organisational conditions that are central to self-concern in biological systems. By emulating these conditions in embodied AI, perhaps something like genuine self-concern can be implemented in machines, bringing AI one step closer to its original goal of emulating human-like intelligence. (shrink)

Despite numerous and increasing attempts to define what life is, there is no consensus on necessary and sufficient conditions for life. Accordingly, some scholars have questioned the value of definitions of life and encouraged scientists and philosophers alike to discard the project. As an alternative to this pessimistic conclusion, we argue that critically rethinking the nature and uses of definitions can provide new insights into the epistemic roles of definitions of life for different research practices. This paper examines the (...) possible contributions of definitions of life in scientific domains where such definitions are used most (e.g., Synthetic Biology, Origins of Life, Alife, and Astrobiology). Rather than as classificatory tools for demarcation of natural kinds, we highlight the pragmatic utility of what we call operational definitions that serve as theoretical and epistemic tools in scientific practice. In particular, we examine contexts where definitions integrate criteria for life into theoretical models that involve or enable observable operations. We show how these definitions of life play important roles in influencing research agendas and evaluating results, and we argue that to discard the project of defining life is neither sufficiently motivated, nor possible without dismissing important theoretical and practical research. (shrink)

The scientific study of living organisms is permeated by machine and design metaphors. Genes are thought of as the ‘‘blueprint’’ of an organism, organisms are ‘‘reverse engineered’’ to discover their functionality, and living cells are compared to biochemical factories, complete with assembly lines, transport systems, messenger circuits, etc. Although the notion of design is indispensable to think about adaptations, and engineering analogies have considerable heuristic value (e.g., optimality assumptions), we argue they are limited in several important respects. In particular, the (...) analogy with human-made machines falters when we move down to the level of molecular biology and genetics. Living organisms are far more messy and less transparent than human-made machines. Notoriously, evolution is an opportunistic tinkerer, blindly stumbling on ‘‘designs’’ that no sensible engineer would come up with. Despite impressive technological innovation, the prospect of artificially designing new life forms from scratch has proven more difficult than the superficial analogy with ‘‘programming’’ the right ‘‘software’’ would suggest. The idea of applying straightforward engineering approaches to living systems and their genomes— isolating functional components, designing new parts from scratch, recombining and assembling them into novel life forms—pushes the analogy with human artifacts beyond its limits. In the absence of a one-to-one correspondence between genotype and phenotype, there is no straightforward way to implement novel biological functions and design new life forms. Both the developmental complexity of gene expression and the multifarious interactions of genes and environments are serious obstacles for ‘‘engineering’’ a particular phenotype. The problem of reverse-engineering a desired phenotype to its genetic ‘‘instructions’’ is probably intractable for any but the most simple phenotypes. Recent developments in the field of bio-engineering and synthetic biology reflect these limitations. Instead of genetically engineering a desired trait from scratch, as the machine/engineering metaphor promises, researchers are making greater strides by co-opting natural selection to ‘‘search’’ for a suitable genotype, or by borrowing and recombining genetic material from extant life forms. (shrink)

The generalized Darwinian research programme accepts physicalism, but holds that all life is purposive in character. It seeks to understand how and why all purposiveness has evolved in the universe – especially purposiveness associated with what we value most in human life, such as sentience, consciousness, person-to-person understanding, science, art, free¬dom, love. As evolution proceeds, the mechanisms of evolution themselves evolve to take into account the increasingly important role that purposive action can play - especially when quasi-Lamarckian evolution by (...) cultural means comes into existence. This programme of research brings together, into a coherent field of inquiry, aspects of such diverse fields of research as orthodox Darwinian theory (given its purposive interpretation), the study of animal behaviour, palaeontology, archaeology, history, anthropology, psycho-neurology, artificial intelligence, psychology, sociology, philosophy, linguistics, semantics, history and philosophy of science, and history and philosophy of inquiry more generally (the history and philosophy of ideas and culture). The great advantage of the generalized Darwinian research programme is that it provides a framework for understanding the deeds, achievements and experiences of people in a way that is compatible with the kind of knowledge and understanding achieved in the physical sciences, without being reducible to such knowledge and understanding. It promises to enable us to understand ourselves as a part of the biological domain without our humanity, our distinctive human value, being in any way denied: persons are not reduced to animals, and nor are animals misconceived to be persons. It holds out the hope that we can come to understand the human world as an integral part of the natural world without the meaning and value of the human world being thereby conceptually annihilated. The programme specifies in general terms what we must seek to do in order to develop a coherent understanding of nature and of ourselves which does justice to the character of both. (shrink)