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)

Measuring the effectiveness of medical interventions faces three epistemological challenges: the choice of good measuring instruments, the use of appropriate analytic measures, and the use of a reliable method of extrapolating measures from an experimental context to a more general context. In practice each of these challenges contributes to overestimating the effectiveness of medical interventions. These challenges suggest the need for corrective normative principles. The instruments employed in clinical research should measure patient-relevant and disease-specific parameters, and should not be sensitive (...) to parameters that are only indirectly relevant. Effectiveness always should be measured and reported in absolute terms (using measures such as 'absolute risk reduction'), and only sometimes should effectiveness also be measured and reported in relative terms (using measures such as 'relative risk reduction')-employment of relative measures promotes an informal fallacy akin to the base-rate fallacy, which can be exploited to exaggerate claims of effectiveness. Finally, extrapolating from research settings to clinical settings should more rigorously take into account possible ways in which the intervention in question can fail to be effective in a target population. (shrink)

It is illegitimate to read any ontology about "race" off of biological theory or data. Indeed, the technical meaning of "genetic variation" is fluid, and there is no single theoretical agreed-upon criterion for defining and distinguishing populations (or groups or clusters) given a particular set of genetic variation data. Thus, by analyzing three formal senses of "genetic variation"—diversity, differentiation, and heterozygosity—we argue that the use of biological theory for making epistemic claims about "race" can only seem plausible when (...) it relies on the user’s own assumptions about race; the move from biological measures to claims about “race” inevitably amounts to a pernicious reification. We also excavate assumptions in the history of the technical discourse over the concept of "race" (e.g., Livingstone's and Dobzhansky's 1962 exchange, Edwards' 2003 response to Lewontin 1972, as well as contemporary discussions of cladistic "race", and "races" as clusters). We show that claims about the existence (or non-existence) of "race" are underdetermined by biological facts, methods, and theories. Biological theory does not force the concept of "race" upon us; our social discourse, social ontology, and social expectations do. We become prisoners of our abstractions at our own hands, and at our own expense. (shrink)

We argue that genuine biological autonomy, or described at human level as free will, requires taking into account quantum vacuum processes in the context of biological teleology. One faces at least three basic problems of genuine biological autonomy: (1) if biological autonomy is not physical, where does it come from? (2) Is there a room for biological causes? And (3) how to obtain a workable model of biological teleology? It is shown here that the (...) solution of all these three problems is related to the quantum vacuum. We present a short review of how this basic aspect of the fundamentals of quantum theory, although it had not been addressed for nearly 100 years, actually it was suggested by Bohr, Heisenberg, and others. Realizing that the quantum mechanical measurement problem associated with the “collapse” of the wave function is related, in the Copenhagen Interpretation of quantum mechanics, to a process between self-consciousness and the external physical environment, we are extending the issue for an explanation of the different processes occurring between living organisms and their internal environment. Definitions of genuine biological autonomy, biological aim, and biological spontaneity are presented. We propose to improve the popular two-stage model of decisions with a biological model suitable to obtain a deeper look at the nature of the mind-body problem. In the newly emerging picture biological autonomy emerges as a new, fundamental and inevitable element of the scientific worldview. (shrink)

-/- Species lists play an important role in biology and practical domains like conservation, legislation, biosecurity and trade regulation. However, their effective use by non-specialist scientific and societal users is sometimes hindered by disagreements between competing lists. While it is well-known that such disagreements exist, it remains unclear how prevalent they are, what their nature is, and what causes them. In this study, we argue that these questions should be investigated using methods based on taxon concept rather than methods based (...) on Linnaean names, and use such a concept-based method to quantify disagreement about bird classification and investigate its relation to research effort. We found that there was disagreement about 38% of all groups of birds recognized as a species, more than three times as much as indicated by previous measures. Disagreement about the delimitation of bird groups was the most common kind of conflict, outnumbering disagreement about nomenclature and disagreement about rank. While high levels of conflict about rank were associated with lower levels of research effort, this was not the case for conflict about the delimitation of bird groups. This suggests that taxonomic disagreement cannot be resolved simply by increasing research effort. (shrink)

Do sensory measurements deserve the label of “measurement”? We argue that they do. They fit with an epistemological view of measurement held in current philosophy of science, and they face the same kinds of epistemological challenges as physical measurements do: the problem of coordination and the problem of standardization. These problems are addressed through the process of “epistemic iteration,” for all measurements. We also argue for distinguishing the problem of standardization from the problem of coordination. To exemplify our (...) claims, we draw on olfactory performance tests, especially studies linking olfactory decline to neurodegenerative disorders. (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)

Animal welfare is a concept that plays a role within both our moral deliberations and the relevant areas of science. The study of animal welfare has impacts on decisions made by legislators, producers and consumers with regards to housing and treatment of animals. Our ethical deliberations in these domains need to consider our impact on animals, and the study of animal welfare provides the information that allows us to make informed decisions. This thesis focusses on taking a philosophical perspective to (...) answer the question of how we can measure the welfare of animals. Animal welfare science is an applied area of biology, aimed at measuring animal welfare. Although philosophy of animal ethics is common, philosophy focussing on animal welfare science is rare. Despite this lack, there are definitely many ways in which philosophical methods can be used to analyse the methodologies and concepts used in this science. One of the aims of the work in this thesis is to remedy this lack of attention in animal welfare. Animal welfare science is a strong emerging discipline, but there is the need for conceptual and methodological clarity and sophistication in this science if it is to play the relevant informative role for our practical and ethical decision-making. There is thus is a strong role here for philosophical analysis for this purpose. The central aim of this thesis is to provide an account of how we can measure subjective animal welfare, addressing some of the potential problems that may arise in this particular scientific endeavour. The two questions I will be answering are: what is animal welfare, and how do we measure it? Part One of the thesis looks at the subjective concept of animal welfare and its applications. In it, I argue for a subjective welfare view - that animal welfare should be understood as the subjective experience of individuals over their lifetimes - and look at how the subjective welfare concept informs our ethical decision-making in two different cases in applied animal ethics. Part Two of the thesis looks more closely at the scientific role of welfare. Understanding welfare subjectively creates unique measurement problems, due to the necessarily private nature of mental states and here I address a few of these problems, including whether subjective experience is measurable, how we might validate indicators of hidden target variables such as welfare, how we can make welfare comparisons between individual animals and how we might compare or integrate the different types of experience that make up welfare. I end with a discussion of the implications of all these problems and solutions for the practice of welfare science, and indicate useful future directions for research. (shrink)

Several authors have used the notion of causal specificity in order to defend non-parity about genetic causes (Waters 2007, Woodward 2010, Weber 2017, forthcoming). Non-parity in this context is the idea that DNA and some other biomolecules that are often described as information-bearers by biologists play a unique role in life processes, an idea that has been challenged by Developmental Systems Theory (e.g., Oyama 2000). Indeed, it has proven to be quite difficult to state clearly what the alleged special role (...) of genetic causes consists in. In this paper, I show that the set of biomolecules that are normally considered to be information-bearers (DNA, mRNA) can be shown to be the most specific causes of protein primary structure, provided that causal specificity is measured over a relevant space of biological possibilities, disregarding physical as well as logically possible states of the causal variables. (shrink)

In biomedical measurement, biomarkers are used to achieve reliable prediction of, and useful causal information about patient outcomes while minimizing complexity of measurement, resources, and invasiveness. A biomarker is an assayable metric that discloses the status of a biological process of interest, be it normative, pathophysiological, or in response to intervention. The greatest utility from biomarkers comes from their ability to help clinicians (and researchers) make and evaluate clinical decisions. In this paper we discuss a specific methodological (...) use of clinical biomarkers in pharmacological measurement: Some biomarkers, called ‘surrogate markers’, are used to substitute for a clinically meaningful endpoint corresponding to events and their penultimate risk factors. We confront the reliability of clinical biomarkers that are used to gather information about clinically meaningful endpoints. Our aim is to present a systematic methodology for assessing the reliability of multiple surrogate markers (and biomarkers in general). To do this we draw upon the robustness analysis literature in the philosophy of science and the empirical use of clinical biomarkers. -/- After introducing robustness analysis we present two problems with biomarkers in relation to reliability. Next, we propose an intervention-based robustness methodology for organizing the reliability of biomarkers in general. We propose three relevant conditions for a robust methodology for biomarkers: (R1) Intervention-based demonstration of partial independence of modes: In biomarkers partial independence can be demonstrated through exogenous interventions that modify a process some number of “steps” removed from each of the markers. (R2) Comparison of diverging and converging results across biomarkers: By systematically comparing partially-independent biomarkers we can track under what conditions markers fail to converge in results, and under which conditions they successfully converge. (R3) Information within the context of theory: Through a systematic cross-comparison of the markers we can make causal conclusions as well as eliminate competing theories. We apply our robust methodology to currently developing Alzheimer’s research to show its usefulness for making causal conclusions. (shrink)

The human attempts to access, measure and organize physical phenomena have led to a manifold construction of mathematical and physical spaces. We will survey the evolution of geometries from Euclid to the Algebraic Geometry of the 20th century. The role of Persian/Arabic Algebra in this transition and its Western symbolic development is emphasized. In this relation, we will also discuss changes in the ontological attitudes toward mathematics and its applications. Historically, the encounter of geometric and algebraic perspectives enriched the mathematical (...) practices and their foundations. Yet, the collapse of Euclidean certitudes, of over 2300 years, and the crisis in the mathematical analysis of the 19th century, led to the exclusion of “geometric judgments” from the foundations of Mathematics. After the success and the limits of the logico-formal analysis, it is necessary to broaden our foundational tools and re-examine the interactions with natural sciences. In particular, the way the geometric and algebraic approaches organize knowledge is analyzed as a cross-disciplinary and cross-cultural issue and will be examined in Mathematical Physics and Biology. We finally discuss how the current notions of mathematical (phase) “space” should be revisited for the purposes of life sciences. (shrink)

The statistical technique of analysis of variance is often used by biologists as a measure of causal factors’ relative strength or importance. I argue that it is a tool ill suited to this purpose, on several grounds. I suggest a superior alternative, and outline some implications. I finish with a diagnosis of the source of error – an unwitting inheritance of bad philosophy that now requires the remedy of better philosophy.

How much does stimulus input shape perception? The common-sense view is that our perceptions are representations of objects and their features and that the stimulus structures the perceptual object. The problem for this view concerns perceptual biases as responsible for distortions and the subjectivity of perceptual experience. These biases are increasingly studied as constitutive factors of brain processes in recent neuroscience. In neural network models the brain is said to cope with the plethora of sensory information by predicting stimulus regularities (...) on the basis of previous experiences. Drawing on this development, this chapter analyses perceptions as processes. Looking at olfaction as a model system, it argues for the need to abandon a stimulus-centred perspective, where smells are thought of as stable percepts, computationally linked to external objects such as odorous molecules. Perception here is presented as a measure of changing signal ratios in an environment informed by expectancy effects from top-down processes. (shrink)

Philosophical discussion about the reality of sensory perceptions has been hijacked by two tendencies. First, talk about perception has been largely centered on vision. Second, the realism question is traditionally approached by attaching objects or material structures to matching contents of sensory perceptions. These tendencies have resulted in an argumentative impasse between realists and anti-realists, discussing the reliability of means by which the supposed causal information transfer from object to perceiver takes place. Concerning the nature of sensory experiences and their (...) capacity to provide access to reality, this article challenges the standard categories through which most arguments in this debate have been framed to date. Drawing on the underexplored case of olfaction, I first show how the details of the perception process determine the modalities of sensory experiences. I specifically examine the role of measurement and analyze its influence on the characterization of perceptions in olfaction. My aim is to argue for an understanding of perception through a process view, rather than one pertaining to objects and properties of objects. (shrink)

This paper explores the evolution of consciousness and subjectivity through a biological framework for understanding the universe. It posits that functional patterns in biological systems mirror cosmic mathematical principles, defining our objective reality. Similar to wave and Fibonacci patterns in different physical phenomena, biological patterns are intrinsic to all things and can be quantified using Dedre Gentner’s approach to analogy. For example, Earth’s ocean currents and the melting and freezing of Antarctica resemble the circulatory system and heart, (...) while the production of music from instruments is analogous to ribosomal protein synthesis. Shelves, tables, and chairs function like cytosol by holding objects in space, and a coffee cup mirrors red blood cell distribution. These analogies reveal a universal order rooted in biology’s functional patterns, essential for shaping the emergence and evolution of life. The paper traces the development of consciousness from its rudimentary cellular states to complex human cognition, highlighting the role of biologically-patterned environments in driving evolutionary changes. Organisms that recognized and organized according to these patterns evolved as “pattern recognition engines” crucial for survival—thus, Life (survival) being the primary measure of consciousness. Humans advanced this capacity, gaining cognitive freedom by insulating themselves from environmental constraints, but faced increased subjectivity complexity. Consciousness, while inherently subjective and necessary for cognitive development, evolves in humans to understand objective reality and its biological nature, so to understand and navigate complexities of subjectivity. Ultimately, the paper asserts consciousness is the ability to recognize and adhere to life-sustaining patterns and principles. Successful adherence deems them worthy of continued existence, while failure leads to demise. Parallels with historical concepts like Atman and Brahman in Hinduism suggest ancient recognition of the correspondence between human and universal patterns. This ancient understanding, coupled with modern scientific evidence, reveals the interconnectedness and intrinsic biological nature of reality. (shrink)

Griffiths et al. (2015) have proposed a quantitative measure of causal specificity and used it to assess various attempts to single out genetic causes as being causally more specific than other cellular mechanisms, for example, alternative splicing. Focusing in particular on developmental processes, they have identified a number of important challenges for this project. In this discussion note, I would like to show how these challenges can be met.

The INBIOSA project brings together a group of experts across many disciplines who believe that science requires a revolutionary transformative step in order to address many of the vexing challenges presented by the world. It is INBIOSA’s purpose to enable the focused collaboration of an interdisciplinary community of original thinkers. This paper sets out the case for support for this effort. The focus of the transformative research program proposal is biology-centric. We admit that biology to date has been more fact-oriented (...) and less theoretical than physics. However, the key leverageable idea is that careful extension of the science of living systems can be more effectively applied to some of our most vexing modern problems than the prevailing scheme, derived from abstractions in physics. While these have some universal application and demonstrate computational advantages, they are not theoretically mandated for the living. A new set of mathematical abstractions derived from biology can now be similarly extended. This is made possible by leveraging new formal tools to understand abstraction and enable computability. [The latter has a much expanded meaning in our context from the one known and used in computer science and biology today, that is "by rote algorithmic means", since it is not known if a living system is computable in this sense (Mossio et al., 2009).] Two major challenges constitute the effort. The first challenge is to design an original general system of abstractions within the biological domain. The initial issue is descriptive leading to the explanatory. There has not yet been a serious formal examination of the abstractions of the biological domain. What is used today is an amalgam; much is inherited from physics (via the bridging abstractions of chemistry) and there are many new abstractions from advances in mathematics (incentivized by the need for more capable computational analyses). Interspersed are abstractions, concepts and underlying assumptions “native” to biology and distinct from the mechanical language of physics and computation as we know them. A pressing agenda should be to single out the most concrete and at the same time the most fundamental process-units in biology and to recruit them into the descriptive domain. Therefore, the first challenge is to build a coherent formal system of abstractions and operations that is truly native to living systems. Nothing will be thrown away, but many common methods will be philosophically recast, just as in physics relativity subsumed and reinterpreted Newtonian mechanics. -/- This step is required because we need a comprehensible, formal system to apply in many domains. Emphasis should be placed on the distinction between multi-perspective analysis and synthesis and on what could be the basic terms or tools needed. The second challenge is relatively simple: the actual application of this set of biology-centric ways and means to cross-disciplinary problems. In its early stages, this will seem to be a “new science”. This White Paper sets out the case of continuing support of Information and Communication Technology (ICT) for transformative research in biology and information processing centered on paradigm changes in the epistemological, ontological, mathematical and computational bases of the science of living systems. Today, curiously, living systems cannot be said to be anything more than dissipative structures organized internally by genetic information. There is not anything substantially different from abiotic systems other than the empirical nature of their robustness. We believe that there are other new and unique properties and patterns comprehensible at this bio-logical level. The report lays out a fundamental set of approaches to articulate these properties and patterns, and is composed as follows. -/- Sections 1 through 4 (preamble, introduction, motivation and major biomathematical problems) are incipient. Section 5 describes the issues affecting Integral Biomathics and Section 6 -- the aspects of the Grand Challenge we face with this project. Section 7 contemplates the effort to formalize a General Theory of Living Systems (GTLS) from what we have today. The goal is to have a formal system, equivalent to that which exists in the physics community. Here we define how to perceive the role of time in biology. Section 8 describes the initial efforts to apply this general theory of living systems in many domains, with special emphasis on crossdisciplinary problems and multiple domains spanning both “hard” and “soft” sciences. The expected result is a coherent collection of integrated mathematical techniques. Section 9 discusses the first two test cases, project proposals, of our approach. They are designed to demonstrate the ability of our approach to address “wicked problems” which span across physics, chemistry, biology, societies and societal dynamics. The solutions require integrated measurable results at multiple levels known as “grand challenges” to existing methods. Finally, Section 10 adheres to an appeal for action, advocating the necessity for further long-term support of the INBIOSA program. -/- The report is concluded with preliminary non-exclusive list of challenging research themes to address, as well as required administrative actions. The efforts described in the ten sections of this White Paper will proceed concurrently. Collectively, they describe a program that can be managed and measured as it progresses. (shrink)

At the intersection of taxonomy and nomenclature lies the scientific practice of typification. This practice occurs in biology with the use of holotypes (type specimens), in geology with the use of stratotypes, and in metrology with the use of measurement prototypes. In this paper I develop the first general definition of a scientific type and outline a new philosophical theory of types inspired by Pierre Duhem. I use this general framework to resolve the necessity-contingency debate about type specimens in (...) philosophy of biology, to advance the debate over the myth of the absolute accuracy of standards in metrology, and to address the definition-correlation debate in geology. I conclude that just as there has been a productive synergy between philosophical accounts of natural kinds and scientific taxonomic practices, so too there is much to be gained from developing a deeper understanding of the practices and philosophy of scientific types. (shrink)

In spite of being ubiquitous in life sciences, the concept of information is harshly criticized. Uses of the concept other than those derived from Shannon's theory are denounced as pernicious metaphors. We perform a computational experiment to explore whether Shannon's information is adequate to describe the uses of said concept in commonplace scientific practice. Our results show that semantic sequences do not have unique complexity values different from the value of meaningless sequences. This result suggests that quantitative theoretical frameworks do (...) not account fully for the complex phenomenon that the term “information” refers to. We propose a restructuring of the concept into two related, but independent notions, and conclude that a complete theory of biological information must account completely not only for both notions, but also for the relationship between them. (shrink)

There is a common argument form in the metaphysics of natural laws literature: a theory of natural law is attacked by offering a claim L as a law of scientific field F (physics, chemistry, biology, etc.), and from this law metaphysical implications contrary to the theory are drawn. Quite often however, L would not be regarded as a law by a scientist of F. Roberts' "measurability account of laws" offers a new and interesting way to more reliably identify the laws (...) of a field F and to eliminate the L that are not laws of F from the literature. (shrink)

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)

Researchers have suggested since the early days of quantum theory that there are strong analogies between quantum phenomena and mental phenomena and these have developed into a vibrant new field of quantum cognition during recent decades. After revisiting some early analogies by Niels Bohr and David Bohm, this paper focuses upon Bohm and Hiley’s ontological interpretation of quantum theory which suggests further analogies between quantum phenomena and biological and psychological phenomena, including the proposal that the human brain operates in (...) some ways like a quantum measuring apparatus. After discussing these analogies I will also consider, from a quantum perspective, Hintikka’s suggestion that Kant’s notion of things in themselves can be better understood by making an analogy between our knowledge-seeking activities and an elaborate measuring apparatus. (shrink)

Throughout the biological and biomedical sciences there is a growing need for, prescriptive ‘minimum information’ (MI) checklists specifying the key information to include when reporting experimental results are beginning to find favor with experimentalists, analysts, publishers and funders alike. Such checklists aim to ensure that methods, data, analyses and results are described to a level sufficient to support the unambiguous interpretation, sophisticated search, reanalysis and experimental corroboration and reuse of data sets, facilitating the extraction of maximum value from data (...) sets them. However, such ‘minimum information’ MI checklists are usually developed independently by groups working within representatives of particular biologically- or technologically-delineated domains. Consequently, an overview of the full range of checklists can be difficult to establish without intensive searching, and even tracking thetheir individual evolution of single checklists may be a non-trivial exercise. Checklists are also inevitably partially redundant when measured one against another, and where they overlap is far from straightforward. Furthermore, conflicts in scope and arbitrary decisions on wording and sub-structuring make integration difficult. This presents inhibit their use in combination. Overall, these issues present significant difficulties for the users of checklists, especially those in areas such as systems biology, who routinely combine information from multiple biological domains and technology platforms. To address all of the above, we present MIBBI (Minimum Information for Biological and Biomedical Investigations); a web-based communal resource for such checklists, designed to act as a ‘one-stop shop’ for those exploring the range of extant checklist projects, and to foster collaborative, integrative development and ultimately promote gradual integration of checklists. (shrink)

This research explored the utilization of video-based instructional material in enhancing learning competency among a group of sixty (60) students enrolled in grade 8 at Satriwithaya School in Bangkok, Thailand. The study was carried out. out during the 2nd semester of S.Y. 2023–2024. The respondents were chosen using the approach of purposive sampling. The research study employed an experimental approach and utilized quantitative research. Through the use of of a one-group pre- and post-test, the researcher was able to gather the (...) necessary data. The study included statistical measures such as percentages, means, and standard deviations, as well as dependent and independent t-tests, to assess and compare the proficiency and efficacy of utilizing video-based educational materials among students at Satriwithaya School in Bangkok, Thailand. Study findings also revealed that there is a significant difference in pre- and post-test assessment scores before and after using the video-based instructional materials. The research outcomes indicated that the application of video-based teaching resources as an instructional strategy in the field of biology resulted in an increased degree of effectiveness in the students' learning process. The findings of the study suggest that the utilization of video-based instructional materials has favorable outcomes in terms of enhancing pedagogical and educational achievements in the field of biology. This methodology has been demonstrated to provide learners with with the chance to enhance their comprehension through active participation, cultivate their imagination and cleverness, consequently facilitating enhanced educational achievements. Furthermore, the establishment of a conducive learning atmosphere that is both engaging and pleasurable for students can enhance their overall learning experience. Moreover, this approach enhances the teacher's capacity to convey their intended educational objectives to their students proficiently. -/- . (shrink)

To approach the issue of the recent proposal of an Extended Evolutionary Synthesis (EES) put forth by Massimo Pigliucci and Gerd Müller, I suggest to consider the EES as a metascientific view: a description of what’s new in how evolutionary biology is carried out, not only a description of recently learned aspects of evolution. Knowing ‘what is it to do research’ in evolutionary biology, today versus yesterday, can aid training, research and career choices, establishment of relationships and collaborations, decision of (...) funding and research policies, in order to make the field advance for the better. After reviewing the concepts associated to the EES proposal (categorized for convenience as mechanisms, measures, fields, perspectives and applications), I show their transience, and sketch out ongoing disagreements about the EES. Then I examine the deep difficulties, i.e., the enormity and complexity of the covered field, affecting the achievement of trusted metascientific views; the insufficiency of conceptual analysis to capture the substance of scientific research; the entanglement between empirical and metascientific concepts, between multiple chronologies, and between descriptive and normative intentions; and the ineliminable stakeholding of any reviewer involved in the reviewed field. I propose that disciplines such as scientometrics, ethnography, sociology, economics and history, combined with conceptual analysis, inspire a more rigorous approach to the evolutionary biology scientific community, more grounded and shared, confirming or transforming claims for ‘synthesis’ while preserving their maintenance goals. (shrink)

We advance an account that grounds cognition, specifically decision-making, in an activity all organisms as autonomous systems must perform to keep themselves viable—controlling their production mechanisms. Production mechanisms, as we characterize them, perform activities such as procuring resources from their environment, putting these resources to use to construct and repair the organism's body and moving through the environment. Given the variable nature of the environment and the continual degradation of the organism, these production mechanisms must be regulated by control mechanisms (...) that select when a production is required and how it should be carried out. To operate on production mechanisms, control mechanisms need to procure information through measurement processes and evaluate possible actions. They are making decisions. In all organisms, these decisions are made by multiple different control mechanisms that are organized not hierarchically but heterarchically. In many cases, they employ internal models of features of the environment with which the organism must deal. Cognition, in the form of decision-making, is thus fundamental to living systems which must control their production mechanisms. (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)

The presumptions underlying quantum mechanics make it relevant to a limited range of situations only; furthermore, its statistical character means that it provides no answers to the question ‘what is really going on?’. Following Barad, I hypothesise that the underlying mechanics has parallels with human activities, as used by Barad to account for the way quantum measurements introduce definiteness into previously indefinite situations. We are led to consider a subtle type of order, different from those commonly encountered in the discipline (...) of physics, and yet comprehensible in terms of concepts considered by Barad and Yardley such as oppositional dynamics or ‘intra-actions’. The emergent organisation implies that nature is no longer fundamentally meaningless. Agencies can be viewed as dynamical systems, so we are dealing with models involving interacting dynamical systems. The ‘congealing of agencies’ to which Barad refers can be equated to the presence of regulatory mechanisms restricting the range of possibilities open to the agencies concerned. (shrink)

I show how archaeologists have two problems. The construction of scenarios accounting for the raw data of Archaeology, the material remains of the past, and the explanation of pre-history. Within Archaeology, there has been an ongoing debate about how to constrain speculation within both of these archaeological projects, and archaeologists have consistently looked to biological mechanisms for constraints. I demonstrate the problems of using biology, either as an analogy for cultural processes or through direct application of biological principles (...) to material remains. This is done through setting out the requirements of a Darwinian Archaeology, and then measuring various approaches against these requirements. This approach leads to the conclusion that archaeologist's explanations of the past must include within their formulations an account of human cognitive capacities within their explanatory framework. The limits of our understanding of the human past will be the limits of our understanding of Homo sapiens. (shrink)

We consider first the most fundamental „design in Nature”, the explanatory structure of the Universe on the basis of the natural sciences, and the related problem of teleology in Nature. We point out that it is necessary to generalize the presently used explanatory scheme of physics. We derive here the first essentially complete scientific world picture, and obtain new insights answering to the problem of cosmic design. Considering some important objections against teleology, we present counter-arguments, give a new classification of (...) the main classes of teleology and their quantitative complexity measures. Comparing the new classification of teleology with that of Mayr, we give useful examples and indicate why teleology is useful for natural science. As a result, we outline a general picture of the basic types of design in Nature and provide their scientific explanation. (shrink)

In her seminal text, What Should We Do With Our Brain? (2008), Catherine Malabou gestured towards neuroplasticity to upend Bergson's famous parallel of the brain as a "central telephonic exchange," whereby the function of the brain is simply that of a node where perceptions get in touch with motor mechanisms, the brain as an instrument limited to the transmission and divisions of movements. Drawing from the history of cybernetics one can trace how Bergson's 'telephonic exchange' prefigures the neural 'cybernetic metaphor.' (...) It is elsewhere, however, that What Should We Do With Our Brain? finds its crux: inspired a dialectical-speculative opposition between plasticity and flexibility (wherein plasticity is the way in which time shapes or fashions us, constitutes our subjectivity and at the same time allows for resistance), Malabou invalidates the 'telephonic exchange' metaphor for failing to take into account synaptic and neuronal vitality. Bolstered by neurologist Marc Jeannerod's research in The Nature of Mind (2002), Malabou further demonstrated, in her past work, that the cybernetic metaphor has also had its day. In Morphing Intelligence, by problematizing intelligence as strictly empirical and biologically determined, Malabou also troubles the traditional distinction between intelligence and intuition. This division is perhaps best exemplified by Bergson’s analysis of intellectual measurement magnitudes in his appeal to intensity, and intensity alone. Malabou, drawing from Dewey and the pragmatism mode of thought, characterizes this fetid standstill as little more than provincialism, charging that, ater Bergson, no truly new argument was offered to counter intelligence as defined by psychologists and biologists, including the most recent cognitivist version. Despite I disagree with her claims regarding cognitivism, in echoing Georges Canguilhem, Malabou castigates psychology’s instrumentalist regard for intelligence, making the claim that it is able to measure only the human ability to “become an instrument.” Malabou contends that Alfred Binet (who heavily critiqued Bergson) had it right—intelligence is constituted by intensities and qualities. This book picks up from this critique and works genealogically; in my exegetical review, I engage with Malabou's and its implications, given her past work. (shrink)

The study of biodiversity spans many disciplines and includes data pertaining to species distributions and abundances, genetic sequences, trait measurements, and ecological niches, complemented by information on collection and measurement protocols. A review of the current landscape of metadata standards and ontologies in biodiversity science suggests that existing standards such as the Darwin Core terminology are inadequate for describing biodiversity data in a semantically meaningful and computationally useful way. Existing ontologies, such as the Gene Ontology and others in the (...) Open Biological and Biomedical Ontologies (OBO) Foundry library, provide a semantic structure but lack many of the necessary terms to describe biodiversity data in all its dimensions. In this paper, we describe the motivation for and ongoing development of a new Biological Collections Ontology, the Environment Ontology, and the Population and Community Ontology. These ontologies share the aim of improving data aggregation and integration across the biodiversity domain and can be used to describe physical samples and sampling processes (for example, collection, extraction, and preservation techniques), as well as biodiversity observations that involve no physical sampling. Together they encompass studies of: 1) individual organisms, including voucher specimens from ecological studies and museum specimens, 2) bulk or environmental samples (e.g., gut contents, soil, water) that include DNA, other molecules, and potentially many organisms, especially microbes, and 3) survey-based ecological observations. We discuss how these ontologies can be applied to biodiversity use cases that span genetic, organismal, and ecosystem levels of organization. We argue that if adopted as a standard and rigorously applied and enriched by the biodiversity community, these ontologies would significantly reduce barriers to data discovery, integration, and exchange among biodiversity resources and researchers. (shrink)

In 2012, the Geological Time Scale, which sets the temporal framework for studying the timing and tempo of all major geological, biological, and climatic events in Earth’s history, had one-quarter of its boundaries moved in a widespread revision of radiometric dates. The philosophy of metrology helps us understand this episode, and it, in turn, elucidates the notions of calibration, coherence, and consilience. I argue that coherence testing is a distinct activity preceding calibration and consilience, and I highlight the value (...) of discordant evidence and trade-offs scientists face in calibration. The iterative nature of calibration, moreover, raises the problem of legacy data. (shrink)

The 20th Century is the starting point for the most ambitious attempts to extrapolate human life into artificial systems. Norbert Wiener’s Cybernetics, Claude Shannon’s Information Theory, John von Neumann’s Cellular Automata, Universal Constructor to the Turing Test, Artificial Intelligence to Maturana and Varela’s Autopoietic Organization, all shared the goal of understanding in what sense humans resemble a machine. This scientific and technological movement has embraced all disciplines without exceptions, not only mathematics and physics but also biology, sociology, psychology, economics etc. (...) New terms were developed, such as “information”, “organization”, “entropy”, “communication”, “encryption”, “computation” and “algorithmics” to mention a few, all which had an enormous impact on artificial systems. Our work follows this historical track but with a reversed order of priorities. Instead of deducing a reduced group of human acts into an artificial environment, we deduce the human aspects of machines by extrapolating algorithmic methodologies into everyday life acts. The present informational theories were insufficiently powered to achieve this objective without developing a new theoretical approach. Hence, our research is directed towards an expansion of the current informational theories. (shrink)

Living organisms act as integrated wholes to maintain themselves. Individual actions can each be explained by characterizing the mechanisms that perform the activity. But these alone do not explain how various activities are coordinated and performed versatilely. We argue that this depends on a specific type of mechanism, a control mechanism. We develop an account of control by examining several extensively studied control mechanisms operative in the bacterium E. coli. On our analysis, what distinguishes a control mechanism from other mechanisms (...) is that it relies on measuring one or more variables, which results in setting constraints in the control mechanism that determine its action on flexible constraints in other mechanisms. In the most basic arrangement, the measurement process directly determines the action of the control mechanism, but in more complex arrangements signals mediate between measurements and effectors. This opens the possibility of multiple responses to the same measurement and responses based on multiple measurements. It also allows crosstalk, resulting in networks of control mechanisms. Such networks integrate the behaviors of the organism but also present a challenge in tailoring responses to particular measurements. We discuss how integrated activity can still result in differential, versatile, responses. (shrink)

Can an AGI create a more intelligent AGI? Under idealized assumptions, for a certain theoretical type of intelligence, our answer is: “Not without outside help”. This is a paper on the mathematical structure of AGI populations when parent AGIs create child AGIs. We argue that such populations satisfy a certain biological law. Motivated by observations of sexual reproduction in seemingly-asexual species, the Knight-Darwin Law states that it is impossible for one organism to asexually produce another, which asexually produces another, (...) and so on forever: that any sequence of organisms (each one a child of the previous) must contain occasional multi-parent organisms, or must terminate. By proving that a certain measure (arguably an intelligence measure) decreases when an idealized parent AGI single-handedly creates a child AGI, we argue that a similar Law holds for AGIs. (shrink)

What is reality? How do we know? Answers to these fundamental questions of ontology and epistemology, based on Mahatma Gandhi's "experiments with truth", are: reality is nonviolent (in the sense of not-inconsistent), and nonviolence (in the sense of respecting-meaning) is the only means of knowing (Gandhi, 1940). Be that as it may, science is what we think of when we think of reality and knowing. How does Gandhi's nonviolence, discovered in his spiritual quest for Truth, relate to the scientific pursuit (...) of truth? Here we show that Gandhian nonviolent knowing of nonviolent reality is an abstraction of both individual knowing (looking, reasoning) and collective scientific knowing (measurements, calculations). Specifically, Gandhi's truth-through-nonviolence is a law-like summation of the methods of physics ("do not disturb" of measurements) and of mathematics ("do not tear" of calculations) that are used to know. Moreover, physics (with its lawful behaviour of bodies) and biology (in preserving the meaning of genetic code) do affirm that the defining attribute of reality is nonviolence. In light of these correspondences, the Mahatma's derivation of a universal method of knowing (nonviolence of preserving-structure) from a universal truth (nonviolence of consistent-becoming) constitutes a science-supported general theory of reality and knowing. (shrink)

Human biological memory systems have adapted to use technological artifacts to overcome some of the limitations of these systems. For example, when performing a difficult calculation, we use pen and paper to create and store external number symbols; when remembering our appointments, we use a calendar; when remembering what to buy, we use a shopping list. This chapter looks at the history of memory artifacts, describing the evolution from cave paintings to virtual reality. It first characterizes memory artifacts, memory (...) systems, and the two main functions such artifacts have, which are to aid individual users in completing memory tasks and as a cultural inheritance channel (section 2). It then outlines some of our first symbolic practices such as making cave paintings and figurines, and then moves on to outline several key developments in external representational systems and the artifacts that support these such as written language, numeral systems and counting devices, diagrams and maps, measuring devices, libraries and archives, photographs, analogue and digital computational artifacts, the World Wide Web, virtual reality, and smartphones (section 3). After that, it makes some brief points about the cumulative nature of the cultural evolution of memory artifacts and speculates about the possible future of memory artifacts, arguing that it is very difficult to look beyond an epistemological horizon of more than five years (section 4). (shrink)

Today, the lipid bilayer structure is nearly ubiquitous, taken for granted in even the most rudimentary introductions to cell biology. Yet the image of the lipid bilayer, built out of lipids with heads and tails, went from having obscure origins deep in colloid chemical theory in 1924 to being “obvious to any competent physical chemist” by 1935. This chapter examines how this schematic, strictly heuristic explanation of the idea of molecular orientation was developed within colloid physical chemistry, and how the (...) image was transformed into a reflection of the reality and agency of lipid molecules in the biological microworld. Whereas in physical and colloid chemistry these images considered secondary to instrumental measurement and mathematical modeling of surface phenomena, in biology the manipulable image of the lipid on paper became an essential tool for the molecularization of the cell. (shrink)

One of the biggest problems in applications of animal welfare science is our ability to make comparisons between different individuals, particularly different species. Although welfare science provides methods for measuring the welfare of individual animals, there’s no established method for comparing measures between individuals. This problem occurs because of the underdetermination of the conclusions given the data, arising from two sources of variation that we cannot distinguish – variation in the underlying target variable (welfare experience) and in the relationship of (...) measured indicators to the target. In this paper I describe the similarity assumptions that underlie our current applications of interspecies comparisons and examine in which cases they are justified, as well as describing alternative methods we may use when they are not. In the end, all our available options for making interspecies comparisons are imperfect, and we need to make explicit context-specific decisions about which will be best for the task at hand while acknowledging their potential limitations. Future developments in our understanding of the biology of sentience will help strengthen our methods of making welfare comparisons. (shrink)

Darwin’s claim that Natural Selection, through optimization of fitness, explains complex biological design has not yet been properly formalized. Alan Grafen’s Formal Darwinism Project aims at providing such a formalization and at demonstrating that fitness maximization is coherent with results from Population Genetics, usually interpreted as denying it. We suggest that Grafen’s proposal suffers from some limitations linked to its concept of design as optimized fitness. In order to overcome these limitations, we propose a classification of evolutionary facts based (...) on a bi-dimensional complexity space, which adds robustness to fitness as measure of the quality of a design. In this space, each point represents an organismic architecture, and movement between two points would be an evolutionary fact. Natural Selection explains movement along the fitness axis, while non-selective mechanisms explain movement on the robustness axis. Moreover, we propose a thermodynamic metaphor to draw parallelisms between notions of fitness and entropy, robustness and energy, and movement in this space and reversible and irreversible cycles. We argue that this metaphor illustrates different evolutionary processes usually overlooked by proposals of formalization of Darwinian theory, such Grafen’s Formal Darwinism Project. (shrink)

In this dissertation, I present a novel account of the components that have a peculiar epistemic role in our scientific inquiries, since they contribute to establishing a form of coordination. The issue of coordination is a classic epistemic problem concerning how we justify our use of abstract conceptual tools to represent concrete phenomena. For instance, how could we get to represent universal gravitation as a mathematical formula or temperature by means of a numerical scale? This problem is particularly pressing when (...) justification for using these abstract tools comes, in part or entirely, from knowledge which is not independent from them, thus leading to threats of circularity. Achieving coordination between some abstract conceptual tools and the concrete phenomena that they are supposed to represent is usually a complex process, which involves several epistemic components. Some of these components eventually provide stable conditions for applying those abstract representations to concrete phenomena. It is in this sense of providing certain conditions of applicability that different philosophical traditions, as well as some contemporary reappraisals, view these components as constitutive or a priori. In this work, I present a new gradualist, contextualist, and relational approach to understand these constitutive components of scientific inquiry. It is gradualist inasmuch as the degree to which some component is constitutive depends on three quantifiable features: quasi-axiomaticity, generative potential, and empirical shielding. Since the quantification of these three features impinges on the history and practice of using these components in a scientific context, my approach is a contextualist one. Finally, my approach is relational in a double sense: first, it identifies ordinal relationships among epistemic components with respect to their constitutive character; second, these relationships are relative to a scientific framework of inquiry. After introducing my account and a classic example of constitutively a priori principles, i.e., Friedman’s (2001) analysis of Newtonian mechanics, I turn to my own case studies to demonstrate the advantages of my approach. Firstly, I discuss Okasha’s (2018) view of endogenization as a pervasive theoretical strategy in evolutionary biology and suggest that the constitutive character of the core Darwinian principles progressively increases with endogenization. Secondly, I apply a conceptual distinction between two varieties or scopes of coordination – general coordination and coordination in measurement – to Ohm’s work on electrical conductivity. This distinction allows me to pinpoint to what extent components along different dimensions (e.g., instrumentation, measurement, theorising, etc.) were constitutive of the forms of coordination which Ohm relied on. Thirdly, I discuss the epistemic function of the Hardy-Weinberg principle in the history and practice of population genetics. I assess this principle in terms of my account and identify approximation and stability as two components that are highly constitutive, in that they contribute to justifying its use in population genetics. Finally, applying my account to these case studies enables me to identify at least three qualitatively different types of constitutive components: domain-specific theoretical principles, material components, and domain-independent assumptions underlying reasoning abilities. In the light of my results, I draw some general conclusions on epistemic justification and scientific knowledge. (shrink)

Background: Microbiome biomarker discovery for patient diagnosis, prognosis, and risk evaluation is attracting broad interest. Selected groups of microbial features provide signatures that characterize host disease states such as cancer or cardio-metabolic diseases. Yet, the current predictive models stemming from machine learning still behave as black boxes and seldom generalize well. Their interpretation is challenging for physicians and biologists, which makes them difficult to trust and use routinely in the physician-patient decision-making process. Novel methods that provide interpretability and biological (...) insight are needed. Here, we introduce "predomics", an original machine learning approach inspired by microbial ecosystem interactions that is tailored for metagenomics data. It discovers accurate predictive signatures and provides unprecedented interpretability. The decision provided by the predictive model is based on a simple, yet powerful score computed by adding, subtracting, or dividing cumulative abundance of microbiome measurements. -/- Results: Tested on >100 datasets, we demonstrate that predomics models are simple and highly interpretable. Even with such simplicity, they are at least as accurate as state-of-the-art methods. The family of best models, discovered during the learning process, offers the ability to distil biological information and to decipher the predictability signatures of the studied condition. In a proof-of-concept experiment, we successfully predicted body corpulence and metabolic improvement after bariatric surgery using pre-surgery microbiome data. -/- Conclusions: Predomics is a new algorithm that helps in providing reliable and trustworthy diagnostic decisions in the microbiome field. Predomics is in accord with societal and legal requirements that plead for an explainable artificial intelligence approach in the medical field. (shrink)

This paper explores the evolution of consciousness and subjectivity through a biological framework for understanding the universe. It posits that functional patterns in biological systems mirror cosmic mathematical principles, defining our objective reality. Similar to wave and Fibonacci patterns in different physical phenomena, biological patterns are intrinsic to all things and can be quantified using Dedre Gentner’s approach to analogy. For example, Earth’s ocean currents and the melting and freezing of Antarctica resemble the circulatory system and heart, (...) while the production of music from instruments is analogous to ribosomal protein synthesis. Shelves, tables, and chairs function like cytosol by holding objects in space, and a coffee cup mirrors red blood cell distribution. These analogies reveal a universal order rooted in biology’s functional patterns, essential for shaping the emergence and evolution of life. The paper traces the development of consciousness from its rudimentary cellular states to complex human cognition, highlighting the role of biologically-patterned environments in driving evolutionary changes. Organisms that recognized and organized according to these patterns evolved as “pattern recognition engines” crucial for survival—thus, Life (survival) being the primary measure of consciousness. Humans advanced this capacity, gaining cognitive freedom by insulating themselves from environmental constraints, but faced increased subjectivity complexity. Consciousness, while inherently subjective and necessary for cognitive development, evolves in humans to understand objective reality and its biological nature, so to understand and navigate complexities of subjectivity. Ultimately, the paper asserts consciousness is the ability to recognize and adhere to life-sustaining patterns and principles. Successful adherence deems them worthy of continued existence, while failure leads to demise. Parallels with historical concepts like Atman and Brahman in Hinduism suggest ancient recognition of the correspondence between human and universal patterns. This ancient understanding, coupled with modern scientific evidence, reveals the interconnectedness and intrinsic biological nature of reality. (shrink)

Fitness plays many roles throughout evolutionary theory, from a measure of populations in the wild to a central element in abstract theoretical presentations of natural selection. It has thus been the subject of an extensive philosophical literature, which has primarily centered on the way to understand the relationship between fitness values and reproductive outcomes. If fitness is a probabilistic or statistical quantity, how is it to be defined in general theoretical contexts? How can it be measured? Can a single conceptual (...) model for fitness be offered that applies in all biological cases, or must fitness measures be case-specific? Philosophers have explored these questions over the last several decades, largely in the context of an influential definition of fitness proposed in the late 1970s: the propensity interpretation. This interpretation as first described undeniably suffers from significant difficulties, and debate regarding the tenability of amendments and alternatives to it remains unsettled. (shrink)

Animal welfare has a long history of disregard. While in recent decades the study of animal welfare has become a scientific discipline of its own, the difficulty of measuring animal welfare can still be vastly underestimated. There are three primary theories, or perspectives, on animal welfare - biological functioning, natural living and affective state. These come with their own diverse methods of measurement, each providing a limited perspective on an aspect of welfare. This paper describes a perspectival pluralist (...) account of animal welfare, in which all three theoretical perspectives and their multiple measures are necessary to understand this complex phenomenon and provide a full picture of animal welfare. This in turn will offer us a better understanding of perspectivism and pluralism itself. (shrink)

There are many bodies, neurons, interacting in a brain. For bodies and interactions to produce consciousness might depend on specific matter and matter interactions, such as specifically those of the neural grey matter and voltages of the brain, or abstract representations and information patterns, such as just the neural firing patterns or those that can be simulated on GPUs. My flipbook thought experiment, elaborated on later in this work, reduces the latter possibility to absurdity. We're able to feel complex emotional (...) experiences at the same time, and observe many concurrent phenomena, including, for example, the visual image before our eyes. This singular observation might be an illusion, or might be a literal singularization of phenomena into a single observer. My physics explanation for how this singularization might happen, elaborated on later in this work, is evidenced by a measured phenomenon in standard physics. Thus, the best explanation for consciousness remaining will be specific physical matter and modes of interactions (via biological neurons and reactions) and singularization (via my hypothesized physics theory, lacking any other). Then one more point is made about how assuming consciousness as a fundamental property of the universe leads to a new answer to the mystery of cosmogenesis. That answer is specified. Finally, all of this together paints a strongly evidenced theory of consciousness, as well as cosmogenesis, whose alternatives have much less justification. (shrink)

"All-and-Nought" is the 2nd Edition of a series of books that study the nature of Reality and Being. The first edition of the book, "The Metaphysics of All-and-None", was published by Edwin Mellen Press in January 2022; since then the book has been under severe investigations and reviews by many scholars and pundits worldwide. The 2nd edition of the book contains the original text plus a foreword by Professor Richard Howells from King’s College London and some reports by Physicists, Biologists, (...) and others. Journal of Mind, one the most important journals in Philosophy, paid attention to the book and in its critical review article October 2022, encourages all philosophers and pundits to study the book. -/- The book's core concept is a Scientific/Mathematical, a-priori/synthetic theory called All'n'None Theory. It studies the Symmetry and Asymmetry in Reality and points to a state that indicates the deep Symmetry between "All Beings" and "Nothingness". It deeply studies the relationships between being and non-being from the perspective of Symmetry and symmetry failure and offers a measurement tool and a new method of studding phenomena. -/- It seems All`n`None Theory is a scientific breakthrough and discovery. The book methodologically applies Physics, Conceptual philosophy, Mathematics, and jurisprudence analysis both inductively and deductively to prove its theory. It is the first and the only Theory for Explaining the nature of Existence (being) and provides a technique to measure the amount of existence in each being. -/- Through understanding Existence, the book explains Creation, Cosmos, Consciousness, Mind, Spirit, and Soul scientifically. It is deep enough to initially encompass and then merge all modern Sciences (Physics, Philosophy, Complexity, System Theory, Information Theory, Psychology, Biology, Humanities, Economy, and Management) with Buddhism, Hinduism, Judaism, Christianity, and Islam (Theology) and makes the image of Reality clearer for readers. -/- The book proves chaos management in the depth of creation and shows how people can use the only law of creation for their own success and salvation. Therefore the book is an inspirational one too. Readers by reading the book and understanding it not only gain scientific knowledge but also find profound wisdom that heals them. They feel they are enlightened and motivated to construct their meaning of life. Readers can recognize their self/ego structure of being and enjoy the passion to improve. -/- The book tries to explain the mechanism of Thinking with respect to Symmetry and the failure of Symmetry as the foundation of Categorization, Mentalization, and Cognition. By understanding the mechanism of cognition it can study Epistemology and explain the Believing Mechanism and the nature of Beliefs as a kind of being. The theory claims no matter the beliefs originated from Science or Religion the mechanisms that govern both of them are the same. Based on the theory, “Knower or Observer”, “Known or Observed”, and “knowing or observation” are rooted in Symmetry and its failure. The tone, language, and structure of the book are unique to itself. It is not an entertainment or commercial book. The book is written for readers who plan to spend enough time to think about its content. (shrink)

We introduce the notion of complexity, first at an intuitive level and then in relatively more concrete terms, explaining the various characteristic features of complex systems with examples. There exists a vast literature on complexity, and our exposition is intended to be an elementary introduction, meant for a broad audience. -/- Briefly, a complex system is one whose description involves a hierarchy of levels, where each level is made of a large number of components interacting among themselves. The time evolution (...) of such a system is of a complex nature, depending on the interactions among subsystems in the next level below the one under consideration and, at the same time, conditioned by the level above, where the latter sets the context for the evolution. Generally speaking, the interactions among the constituents of the various levels lead to a dynamics characterized by numerous characteristic scales, each level having its own set of scales. What is more, a level commonly exhibits ‘emergent properties’ that cannot be derived from considerations relating to its component systems taken in isolation or to those in a different contextual setting. In the dynamic evolution of some particular level, there occurs a self-organized emergence of a higher level and the process is repeated at still higher levels. -/- The interaction and self-organization of the components of a complex system follow the principle commonly expressed by saying that the ‘whole is different from the sum of the parts’. In the case of systems whose behavior can be expressed mathematically in terms of differential equations this means that the interactions are nonlinear in nature. -/- While all of the above features are not universally exhibited by complex systems, these are nevertheless indicative of a broad commonness relative to which individual systems can be described and analyzed. There exist measures of complexity which, once again, are not of universal applicability, being more heuristic than exact. The present state of knowledge and understanding of complex systems is itself an emerging one. Still, a large number of results on various systems can be related to their complex character, making complexity an immensely fertile concept in the study of natural, biological, and social phenomena. -/- All this puts a very definite limitation on the complete description of a complex system as a whole since such a system can be precisely described only contextually, relative to some particular level, where emergent properties rule out an exact description of more than one levels within a common framework. -/- We discuss the implications of these observations in the context of our conception of the so-called noumenal reality that has a mind-independent existence and is perceived by us in the form of the phenomenal reality. The latter is derived from the former by means of our perceptions and interpretations, and our efforts at sorting out and making sense of the bewildering complexity of reality takes the form of incessant processes of inference that lead to theories. Strictly speaking, theories apply to models that are constructed as idealized versions of parts of reality, within which inferences and abstractions can be carried out meaningfully, enabling us to construct the theories. -/- There exists a correspondence between the phenomenal and the noumenal realities in terms of events and their correlations, where these are experienced as the complex behavior of systems or entities of various descriptions. The infinite diversity of behavior of systems in the phenomenal world are explained within specified contexts by theories. The latter are constructs generated in our ceaseless attempts at interpreting the world, and the question arises as to whether these are reflections of `laws of nature' residing in the noumenal world. This is a fundamental concern of scientific realism, within the fold of which there exists a trend towards the assumption that theories express truths about the noumenal reality. We examine this assumption (referred to as a ‘point of view’ in the present essay) closely and indicate that an alternative point of view is also consistent within the broad framework of scientific realism. This is the view that theories are domain-specific and contextual, and that these are arrived at by independent processes of inference and abstractions in the various domains of experience. Theories in contiguous domains of experience dovetail and interpenetrate with one another, and bear the responsibility of correctly explaining our observations within these domains. -/- With accumulating experience, theories get revised and the network of our theories of the world acquires a complex structure, exhibiting a complex evolution. There exists a tendency within the fold of scientific realism of interpreting this complex evolution in rather simple terms, where one assumes (this, again, is a point of view) that theories tend more and more closely to truths about Nature and, what is more, progress towards an all-embracing ‘ultimate theory’ -- a foundational one in respect of all our inquiries into nature. We examine this point of view closely and outline the alternative view -- one broadly consistent with scientific realism -- that there is no ‘ultimate’ law of nature, that theories do not correspond to truths inherent in reality, and that successive revisions in theory do not lead monotonically to some ultimate truth. Instead, the theories generated in succession are incommensurate with each other, testifying to the fact that a theory gives us a perspective view of some part of reality, arrived at contextually. Instead of resembling a monotonically converging series successive theories are analogous to asymptotic series. -/- Before we summarize all the above considerations, we briefly address the issue of the complexity of the {\it human mind} -- one as pervasive as the complexity of Nature at large. The complexity of the mind is related to the complexity of the underlying neuronal organization in the brain, which operates within a larger biological context, its activities being modulated by other physiological systems, notably the one involving a host of chemical messengers. The mind, with no materiality of its own, is nevertheless emergent from the activity of interacting neuronal assemblies in the brain. As in the case of reality at large, there can be no ultimate theory of the mind, from which one can explain and predict the entire spectrum of human behavior, which is an infinitely rich and diverse one. (shrink)

According to one large family of views, scientific explanations explain a phenomenon (such as an event or a regularity) by subsuming it under a general representation, model, prototype, or schema (see Bechtel, W., & Abrahamsen, A. (2005). Explanation: A mechanist alternative. Studies in History and Philosophy of Biological and Biomedical Sciences, 36(2), 421–441; Churchland, P. M. (1989). A neurocomputational perspective: The nature of mind and the structure of science. Cambridge: MIT Press; Darden (2006); Hempel, C. G. (1965). Aspects of (...) scientific explanation. In C. G. Hempel (Ed.), Aspects of scientific explanation (pp. 331–496). New York: Free Press; Kitcher (1989); Machamer, P., Darden, L., & Craver, C. F. (2000). Thinking about mechanisms. Philosophy of Science, 67(1), 1–25). My concern is with the minimal suggestion that an adequate philosophical theory of scientific explanation can limit its attention to the format or structure with which theories are represented. The representational subsumption view is a plausible hypothesis about the psychology of understanding. It is also a plausible claim about how scientists present their knowledge to the world. However, one cannot address the central questions for a philosophical theory of scientific explanation without turning one’s attention from the structure of representations to the basic commitments about the worldly structures that plausibly count as explanatory. A philosophical theory of scientific explanation should achieve two goals. The first is explanatory demarcation. It should show how explanation relates with other scientific achievements, such as control, description, measurement, prediction, and taxonomy. The second is explanatory normativity. It should say when putative explanations succeed and fail. One cannot achieve these goals without undertaking commitments about the kinds of ontic structures that plausibly count as explanatory. Representations convey explanatory information about a phenomenon when and only when they describe the ontic explanations for those phenomena. (shrink)