The history of British cybernetics offers us a different form of science and engineering, one that does not seek to dominate nature through knowledge. I want to say that one can distinguish two different paradigms in the history of science and technology: the one that Heidegger despised, which we could call the Modern paradigm, and another, cybernetic, nonModern, paradigm that he might have approved of. This essay focusses on work in the 1950s and early 1960s by two of Britain’s leading (...) cyberneticians, Stafford Beer and Gordon Pask, in the field of what one can call biological computing. My object is to get as clear as I can on what Beer and Pask were up to. At the end, I will discuss Beer’s hylozoist ontology of matter, mind and spirit. This material is not easy to get the hang of—but that is what one should expect from an unfamiliar paradigm. (shrink)

The central paradigm of arti?cial intelligence is rapidly shifting toward biological models for both robotic devices and systems performing such critical tasks as network management, vehicle navigation, and process control. Here we use a recent mathematical analysis of the necessary conditions for consciousness in humans to explore likely failure modes inherent to a broad class of biologically inspired computing machines. Analogs to developmental psychopathology, in which regulatory mechanisms for consciousness fail progressively and subtly understress, and toinattentional blindness, where (...) a narrow 'syntactic band pass' de?ned by the rate distortion manifold of conscious attention results in pathological ?xation, seem inevitable. Similar problems are likely to confront other possible architectures, although their mathematical description may be far less straightforward. Computing devices constructed on biological paradigms will inevitably lack the elaborate, but poorly understood, system of control mechanisms which has evolved over the last few hundred million years to stabilize consciousness in higher animals. This will make such machines prone to insidious degradation, and, ultimately, catastrophic failure. (shrink)

The integration of computer science, biology, and engineering has resulted in the emergence of rapidly growing interdisciplinary fields such as bioinformatics, bioengineering, DNA computing, and systems and synthetic biology. Ideas derived from computer science and engineering can provide innovative solutions to biological problems and advance research in new directions. Although interdisciplinary research has become increasingly prevalent in recent years, the scientists contributing to these efforts largely remain specialists in their original disciplines and are not fully capable of covering (...) the many facets of multidisciplinary problems, which impedes the development of truly integrated solutions. It would be .. (shrink)

This article is about the power of critical thinking through embryos and embryology in bioart. In this instance, critical thinking does not promise revolution or a takedown of bioengineering, but basic empowerment through scientific knowledge. I argue that the use of embryos in Jill Scott’s Somabook (2011) and Adam Zaretsky’s DIY Embryology (2015) constitutes an instance of what Philip Galanter identifies as complexism. In turn, the complexism of embryology reveals two modes of critical thinking. First, embryology distils the awe and (...) wonder that come with basic scientific literacy. In turn, scientific literacy provides agency for individuals through a trifecta of feeling, belief and pragmatism: based on the frisson of curiosity and wonder that comes with recognizing biological complexity, it frees individuals from the bounds of superstition and metaphysics while building a path to fact-based problem solving. Second, as works of art bearing embryos they are part of the politics and history of embryology that emerged in contrast to genetics almost a century ago. Distinct from the coding of genetics as nucleus-centric, separate, homogeneous, a matter of being, and male, embryology was coded as cytoplasmic, interactive, heterogeneous, a matter of becoming, and feminist. (shrink)

Offering a novel and pragmatic perspective, this timely book critically examines the development of a culture of machinist regulation and questions whether this approach is appropriate in an era of rising biological technologies. Adopting an ontological approach, James Griffin considers how current regulatory frameworks favour digital technology and how this may change in the future. Griffin adeptly investigates how regulation can impact the nature of new technologies, especially as biological computing is becoming more commonplace. Chapters provide a (...) wealth of critical analysis, considering cutting-edge technologies such as AI, prosthesis, and biological computing. Griffin outlines a proposed reformative system which focuses on the biological substrate in the creation of cultural works. The book serves to highlight the ever-increasing need for awareness of the importance of biological substrates and for a regulatory system which reflects this. The State of Cultural Biology will be an essential read for academics and students interested in intellectual property law, law and technology, legal philosophy and law's role in society. It will also prove invaluable to policymakers and professionals looking to broaden their knowledge on the regulation of modern technology. (shrink)

In this chapter we explore basic mathematical and other constraints which limit the often novel uses of computation employed in modern computational system biology. These constraints generate substantial obstacles for one goal prominent in the field; namely, the goal of producing models valid for predictive uses in clinical and other contexts. However on closer examination many applications of computation and simulation in the field have more pragmatic or investigative goals in mind, suggesting an important role for rationalizing uses of computation (...) in systems biology and elsewhere as investigative tools. We discuss the concept of an “investigative tool”, and what insights it might offer our understanding of modern computational strategies and the bases for them. (shrink)

T he term emergence is used to describe the appearance of new properties that arise when a system exceeds a certain level of size or complexity, properties that are absent from the constituents of the system. It is a concept often summed up by the phrase that “the whole is greater than the sum of its parts,” and it is a key notion in the burgeoning field of complexity science. Life is often cited as a classic example of an emergent (...) phenomenon: no atoms of my body are living, yet I am living (see, for example, Morowitz [1]). Biological organisms depend on the processes of their constituent parts, yet they nevertheless exhibit a degree of autonomy from their parts (see, for example, Kauffman [2]). How can this be? These seem to be contradictory properties. (shrink)

In this philosophical paper, we explore computational and biological analogies to address the fine-tuning problem in cosmology. We first clarify what it means for physical constants or initial conditions to be fine-tuned. We review important distinctions such as the dimensionless and dimensional physical constants, and the classification of constants proposed by Lévy-Leblond. Then we explore how two great analogies, computational and biological, can give new insights into our problem. This paper includes a preliminary study to examine the two (...) analogies. Importantly, analogies are both useful and fundamental cognitive tools, but can also be misused or misinterpreted. The idea that our universe might be modelled as a computational entity is analysed, and we discuss the distinction between physical laws and initial conditions using algorithmic information theory. Smolin introduced the theory of "cosmological natural selection" with a biological analogy in mind. We examine an extension of. (shrink)

The distinction between phenomenal (P) and access (A) consciousness arises from the battle between biological and computational approaches to the mind. If P = A, the computationalists are right; but if not, the biological nature of P yields its scientific nature.

Background: how mind functions is subject to continuing scientific discussion. A simplistic approach says that, since no convincing way has been found to model subjective experience, mind cannot exist. A second holds that, since mind cannot be described by classical physics, it must be described by quantum physics. Another perspective concerns mind's hypothesized ability to interact with the world of quanta: it should be responsible for reduction of quantum wave packets; physics producing 'Objective Reduction' is postulated to form the basis (...) for mind-matter interactions. This presentation describes results derived from a new approach to these problems. It is based on well-established biology involving physics not previously applied to the fields of mind, or consciousness studies, that of critical feedback instability. -/- Methods: 'self-organized criticality' in complexity biology places system loci of control at critical instabilities, physical properties of which, including information properties, are presented. Their elucidation shows that they can model hitherto unexplained properties of experience. -/- Results: All results depend on physical properties of critical instabilities. First, at least one feed-back or feed-forward loop must have feedback gain, g = 1: information flows round the loop impress perfect images of system states back on themselves: they represent processes of perfect self-observation. This annihilates system quanta: system excitations are instability fluctuations, which cannot be quantized. Major results follow: -/- 1. Information vectors representing criticality states must include at least one attached information loop denoting self-observation. -/- 2. Such loop structures are attributed a function, 'registering the state's own existence', explaining -/- a. Subjective 'awareness of one's own presence' -/- b. How content-free states of awareness can be remembered (Jon Shear) -/- c. Subjective experience of time duration (Immanuel Kant) -/- d. The 'witness' property of experience – often mentioned by athletes 'in the zone' -/- e. The natural association between consciousness and intelligence -/- This novel, physically and biologically sound approach seems to satisfactorily model subjectivity. -/- Further significant results follow: -/- 1. Registration of external information in excited states of systems at criticality reduces external wave-packets: the new model exhibits 'Objective Reduction' of wave packets. -/- 2. High internal coherence (postulated by Domash & Penrose) leading to a. Non-separable information vector bundles. b. Non-reductive states (Chalmers's criterion for experience). -/- 3. Information that is: a. encoded in coherence negentropy; b. non-digitizable, and therefore c. computationally without digital equivalent (posited by Penrose). -/- Discussion and Conclusions: instability physics implies anharmonic motion, preventing excitation quantization, and totally different from the quantum physics of simple harmonic motion at stability. Instability excitations are different from anything hitherto conceived in information science. They can model aspects of mind never previously treated, including genuine subjectivity, objective reduction of wave-packets, and inter alia all properties given above. (shrink)

Various threshold Boolean networks, a formalism used to model different types of biological networks, can produce similar dynamics, i.e. share same behaviors. Among them, some are complex, others not. By computing both structural and behavioral complexities, we show that most TBNs are structurally complex, even those having simple behaviors. For this purpose, we developed a new method to compute the structural complexity of a TBN based on estimates of the sizes of equivalence classes of the threshold Boolean functions (...) composing the TBN. (shrink)

Since the 1980s, several studies of visual perception have persuasively argued that important aspects of human vision are best accounted for not by recourse to inner mental representations but rather through socially observable actions and behaviors (e.g. Lynch 1985, Latour 1986, Lynch 1990, Goodwin 1994, Goodwin 1997, Sharrock & Coulter 1998). While there are clearly physiological mechanisms required for vision, psychological accounts of perception in terms of inner mental representations have been dislodged from their position as the basic term in (...) the interface between human beings and their environment and replaced with terms such as "social practice," and "vernacular intelligibility." The focus for these .. (shrink)

An analogy between the evolution of organisms and some complex computational problems (cryptosystem cracking, determination of the shortest path in a graph) is considered. It is shown that in the absence of a priori information about possible species of organisms such a problem is complex (is rated in the class NP) and cannot be solved in a polynomial number of steps. This conclusion suggests the need for re-examination of evolution mechanisms. Ideas of a deterministic approach to the evolution are discussed.

Increasingly, biologists are using computers to model and to create biological representations. However, the exponential growth in available biological dataposes a challenge for experimental and theoretical researchers in both Biology and in Computer Science. In short, when even the simple retrieval of relevant biological information for a researcher becomes a complex task — its analysis and synthesis with other biological information will become even more daunting and unlikely. In this context, specially organized ‘structures of representation’ are (...) needed for the efficient interpretation of experimentally generated data. The “semantic Web” is a recent trend in networking techniques that we will examine here as a possible strategy for the computation of biological data — one that may allow us to take into account both the semiotic dimensions of biological processes, as well as their dynamic organization into stable and systemic levels. Thereupon, we propose that a semantic network for biology could benefit from principles rooted in such previous representation efforts as computer-generated ‘landscapes’ and ‘physical attractors’ — and that such principles could, in turn, then be better integrated into biological research through the development of a more semiotically informed user / computer interface design. (shrink)

Recent technical improvements, such as 3D microscopy imaging, have shown the necessity of studying 3D biological tissue architecture during carcinogenesis. In the present paper a computer simulation model is developed allowing the visualization of the microscopic biological tissue architecture during the development of metaplastic and dysplastic lesions.The static part of the model allows the simulation of the normal, metaplastic and dysplastic architecture of an external epithelium. This model is associated to a knowledge base which contains only data on (...) the nasal epithelium. The latter has been well studied by numerous authors and its lesional states are well known. An inference engine allows the initialization of the static model parameters. A statistical comparison between simulated epithelia and real epithelia is achieved by adjusting the parameter values during the simulation. (shrink)

Imagine a world where machines can see and understand the world the way humans do. Rapid progress in artificial intelligence has led to smartphones that recognize faces, cars that detect pedestrians, and algorithms that suggest diagnoses from clinical images, among many other applications. The success of computer vision is founded on a deep understanding of the neural circuits in the brain responsible for visual processing. This book introduces the neuroscientific study of neuronal computations in visual cortex alongside of the psychological (...) understanding of visual cognition and the burgeoning field of biologically-inspired artificial intelligence. Topics include the neurophysiological investigation of visual cortex, visual illusions, visual disorders, deep convolutional neural networks, machine learning, and generative adversarial networks among others. It is an ideal resource for students and researchers looking to build bridges across different approaches to studying and developing visual systems. (shrink)

This reader contains the extended abstracts of the seminars organised for the “Computer Science and IT with/for Biology” Seminar Series, held at the Faculty of Computer Science, Free University of Bozen-Bolzano, from October to December 2005. Slides of the presentations are available online at: www.inf.unibz.it/krdb/biology.

This aricle discusses the similarity between the propagation of pathogens (viruses and worms) on computer networks and the proliferation of pathogens in cellular organisms (organisms with genetic material contained within a membrane-encased nucleus). It introduces several biological mechanisms which are used in these organisms to protect against such pathogens and presents security models for networked computers inspired by several biological paradigms, including genomics (RNA interference), proteomics (pathway mapping), and physiology (immune system). In addition, the study of epidemiological models (...) for disease control can inspire methods for controlling the spread of pathogens across multiple nodes of a network. It also presents results based on the authors’ research in immune system modeling. (shrink)

We present techniques for integrating low‐level neurobiological constraints into high‐level, functional cognitive models. In particular, we use these techniques to construct a model of eyeblink conditioning in the cerebellum based on temporal representations in the recurrent Granule‐Golgi microcircuit.

Though only established as a discipline since the 1970s, philosophy of biology has already triggered investigations about its own history The Oxford handbook of philosophy of biology, Oxford University Press, New York, pp 11–33, 2008). When it comes to assessing the road since travelled—the research questions that have been pursued—manuals and ontologies also offer specific viewpoints, highlighting dedicated domains of inquiry and select work. In this article, we propose to approach the history of the philosophy of biology with a complementary (...) data-driven perspective that makes use of statistical algorithms applied to the complete full-text corpus of one major journal of the field—Biology and Philosophy—from its launch in 1986 up until 2017. By running text-mining and topic-modeling algorithms, we identified 67 key research topics that span across these 32 years. We also investigated the evolution of these topics over time and their fluctuating significance in the journal articles. Our results concur with known episodes or traits of the discipline—for instance, the significance of evolution-related topics or the decrease of articles with a marked historical dimension—but also highlight a diversity of topics that is much richer than what is usually acknowledged. (shrink)

Observability is a modelling property that describes the possibility of inferring the internal state of a system from observations of its output. A related property, structural identifiability, refers to the theoretical possibility of determining the parameter values from the output. In fact, structural identifiability becomes a particular case of observability if the parameters are considered as constant state variables. It is possible to simultaneously analyse the observability and structural identifiability of a model using the conceptual tools of differential geometry. Many (...) complex biological processes can be described by systems of nonlinear ordinary differential equations and can therefore be analysed with this approach. The purpose of this review article is threefold: to serve as a tutorial on observability and structural identifiability of nonlinear systems, using the differential geometry approach for their analysis; to review recent advances in the field; and to identify open problems and suggest new avenues for research in this area. (shrink)

Regulated transport of the plant hormone auxin is central to many aspects of plant development. Directional transport, mediated by membrane transporters, produces patterns of auxin distribution in tissues that trigger developmental processes, such as vascular patterning or leaf formation. Experimentation has produced many, largely qualitative, data providing strong evidence for multiple feedback systems between auxin and its transport. However, the exact mechanisms concerned remain elusive and the experiments required to evaluate alternative hypotheses are challenging. Because of this, computational modelling now (...) plays an important role in auxin transport research. Here we review some current approaches and underlying assumptions of computational auxin transport models. We focus on self‐organising models for polar auxin transport and on recent attempts to unify conflicting mechanistic explanations. In addition, we discuss in general how these computer simulations are proving to be increasingly effective in hypothesis generation and testing, and how simulation can be used to direct future experiments.Editor's suggested further reading in BioEssays Local auxin production: a small contribution to a big field Abstract. (shrink)

Investigations into inter-level relations in computer science, biology and psychology call for an *empirical* turn in the philosophy of mind. Rather than concentrate on *a priori* discussions of inter-level relations between 'completed' sciences, a case is made for the actual study of the way inter-level relations grow out of the developing sciences. Thus, philosophical inquiries will be made more relevant to the sciences, and, more importantly, philosophical accounts of inter-level relations will be testable by confronting them with what really happens (...) in science. Hence, close observation of the ever-changing reduction relations in the developing sciences, and revision of philosophical positions based on these empirical observations, may, in the long run, be more conducive to an adequate understanding of inter-level relations than a traditional *a priori* approach. (shrink)

Though only established as a discipline since the 1970s, philosophy of biology has already triggered investigations about its own history The Oxford handbook of philosophy of biology, Oxford University Press, New York, pp 11–33, 2008). When it comes to assessing the road since travelled—the research questions that have been pursued—manuals and ontologies also offer specific viewpoints, highlighting dedicated domains of inquiry and select work. In this article, we propose to approach the history of the philosophy of biology with a complementary (...) data-driven perspective that makes use of statistical algorithms applied to the complete full-text corpus of one major journal of the field—Biology and Philosophy—from its launch in 1986 up until 2017. By running text-mining and topic-modeling algorithms, we identified 67 key research topics that span across these 32 years. We also investigated the evolution of these topics over time and their fluctuating significance in the journal articles. Our results concur with known episodes or traits of the discipline—for instance, the significance of evolution-related topics or the decrease of articles with a marked historical dimension—but also highlight a diversity of topics that is much richer than what is usually acknowledged. (shrink)

Chapter SETTING THE STAGE As is fitting for a beginning chapter, attempts are made here to provide historical perspectives and insights from various vantage ...

The pervasive use of computer simulations in the sciences brings novel epistemological issues discussed in the philosophy of science literature since about a decade. Evolutionary biology strongly relies on such simulations, and in relation to it there exists a research program (Artificial Life) that mainly studies simulations themselves. This paper addresses the specificity of computer simulations in evolutionary biology, in the context (described in Sect. 1) of a set of questions about their scope as explanations, the nature of validation processes (...) and the relation between simulations and true experiments or mathematical models. After making distinctions, especially between a weak use where simulations test hypotheses about the world, and a strong use where they allow one to explore sets of evolutionary dynamics not necessarily extant in our world, I argue in Sect. 2 that (weak) simulations are likely to represent in virtue of the fact that they instantiate specific features of causal processes that may be isomorphic to features of some causal processes in the world, though the latter are always intertwined with a myriad of different processes and hence unlikely to be directly manipulated and studied. I therefore argue that these simulations are merely able to provide candidate explanations for real patterns. Section 3 ends up by placing strong and weak simulations in Levins’ triangle, that conceives of simulations as devices trying to fulfil one or two among three incompatible epistemic values (precision, realism, genericity). (shrink)

David Marr's theory of vision has been a rich source of inspiration, fascination and confusion. I will suggest that some of this confusion can be traced to discrepancies between the way Marr developed his theory in practice and the way he suggested such a theory ought to be developed in his explicit metatheoretical remarks. I will address claims that Marr's theory may be seen as an optimizing theory, along with the attendant suggestion that optimizing assumptions may be inappropriate for cognitive (...) mechanisms just as anti-adaptationists have argued they are inappropriate for other physiological mechanisms. I will discuss the nature of optimizing assumptions and theories. Considering various difficulties in identifying and assessing optimizing assumptions, I will suggest that Marr's theory is not purely an optimizing theory and that reaction to Marr on this issue prompts interesting considerations for the development of inter-disciplinary constraints in the cognitive and brain sciences. (shrink)

"Databases containing the accumulated genomic data of the research community are growing exponentially. This book contains cutting-edge insights from scholars, bioethicists and legal practitioners who work at the ever-changing intersection of law and bioinformatics"--Page 4 of cover.