In sociology, there has been a controversy about whether there is any essential difference between a human being and a tool, or if the tool–user relationship can be defined by co-actor symmetry. This issue becomes more complex when we consider examples of AI and robots, and even more so following progress in the development of various bio-machine hybrid technologies, such as robots that include organic parts, human brain implants, and adaptive prosthetics. It is argued that a concept of autonomous (...) agency based on organismic embodiment helps to clarify the situation. On this view, agency consists of an asymmetrical relationship between an organism and its environment, because the continuous metabolic and regulatory activity of the organism gives rise to its own existence, and hence its specific behavioral domain. Accordingly, most of current technologies are excluded from the class of autonomous agents. Instead, they are better conceptualized as interfaces that mediate our interactions with the world. This has important implications for design: Rather than trying to help humans to achieve their goals by duplicating their agency in artificial systems, it would be better to empower humans directly by enhancing their existing agency and lived experience with technological interfaces that can be incorporated into their embodiment. This incorporation might be especially facilitated by bio-machine hybrid technology that is designed according the principles of biological autonomy and multi-agent coordination dynamics. (shrink)

The emerging field of synthetic biology aims to engineer novel biological entities. The envisioned future bio-based economy builds largely on “cell factories”: organisms that have been metabolically engineered to sustainably produce substances for human ends. In this paper, we argue that synthetic biology’s goal of creating efficient production vessels for industrial applications implies a set of ontological assumptions according to which living organisms are machines. Traditionally, a machine is understood as a technological, isolated and controllable production unit consisting of (...) parts. But modified organisms, or hybrids, require us to think beyond the machine paradigm and its associated dichotomies between artificial and natural, organisms and artefacts. We ask: How may we conceptualise hybrids beyond limiting ontological categories? Our main claim is that the hybrids created by synthetic biology should be considered not as machines but as metabolic systems. We shall show how the philosophical account of metabolism can inform an ontology of hybrids that moves beyond what we call the “machine ontology”, considering that metabolism enables thinking beyond the dominant dichotomies and allows us to understand and design lifeforms in a bio-based economy. Thus, the aim of this paper is twofold: first, to develop the philosophical ontology of hybrids, and second, to move synthetic biology beyond the problematically limiting view of hybrids. (shrink)

The paper develops two related thought experiments exploring variations on an ‘animat’ theme. Animats are hybrid devices with both artificial and biological components. Traditionally, ‘components’ have been construed in concrete terms, as physical parts or constituent material structures. Many fascinating issues arise within this context of hybrid physical organization. However, within the context of functional/computational theories of mentality, demarcations based purely on material structure are unduly narrow. It is abstract functional structure which does the key work in characterizing the respective (...) ‘components’ of thinking systems, while the ‘stuff’ of material implementation is of secondary importance. Thus the paper extends the received animat paradigm, and investigates some intriguing consequences of expanding the conception of bio-machine hybrids to include abstract functional and semantic structure. In particular, the thought experiments consider cases of mind-machine merger where there is no physical Brain-Machine Interface: indeed, the material human body and brain have been removed from the picture altogether. The first experiment illustrates some intrinsic theoretical difficulties in attempting to replicate the human mind in an alternative material medium, while the second reveals some deep conceptual problems in attempting to create a form of truly Artificial General Intelligence. (shrink)

Electronic machinic phenomena yield fascinating links with biological processes. Either in the macro-micro-structure of binary encoded information ‐ bytes on media ‐ to the processual flow programs execute on hardware while operating it. Observing micro-electronic worlds akin to living entities: electronic voltages running throughout electronic architectures pipelining data to memory registers; operating systems executing programs on electronic substrates; data flows taking place in machines and in communications protocols within networks. Static art-sci constructs explore and visualize these observations as 2D drawings (...) (Neon Paleolitikos Drawings, 2017‐present) or 3D sculptures (Binary and Biological Sculpture Series, 2018‐present), creatively exposing their inherent rhythmic organization of information, while dynamic installations (Phoenix.Wolfanddotcom.info, Wolfanddotcom, Half-Plant, 2017, Ant Ennae Labyrinths, 2019‐present) propose immersive interference mechanisms that attempt user entanglement in non-human environments. Seven aesthetic case examples are introduced and explored, observing and seeking resonances between micro-granular electronic, biological and hybrid data as source synthesis. This research proposes a look at bio-electronic aggregates on Neon Paleolitikos strata. After the Anthropocene, Neon Paleolitikos is an imaginary epoch dating since the decline of mankind until the zenith of bio-electronic life forms: operational symbioses combined among ruins of silica, transistors, algorithms, cells, plants, animals and electricity. (shrink)

The Chinese Room Argument purports to show that‘ syntax is not sufficient for semantics’; an argument which led John Searle to conclude that ‘programs are not minds’ and hence that no computational device can ever exhibit true understanding. Yet, although this controversial argument has received a series of criticisms, it has withstood all attempts at decisive rebuttal so far. One of the classical responses to CRA has been based on equipping a purely computational device with a physical robot body. This (...) response, although partially addressed in one of Searle’s original contra arguments - the ‘robot reply’ - more recently gained friction with the development of embodiment and enactivism1, two novel approaches to cognitive science that have been exciting roboticists and philosophers alike. Furthermore, recent technological advances - blending biological beings with computational systems - have started to be developed which superficially suggest that mind may be instantiated in computing devices after all. This paper will argue that (a) embodiment alone does not provide any leverage for cognitive robotics wrt the CRA, when based on a weak form of embodiment and that (b) unless they take the body into account seriously, hybrid bio-computer devices will also share the fate of their disembodied or robotic predecessors in failing to escape from Searle’s Chinese room. (shrink)

John Searle’s Chinese Room Argument purports to demonstrate that syntax is not sufficient for semantics, and, hence, because computation cannot yield understanding, the computational theory of mind, which equates the mind to an information processing system based on formal computations, fails. In this paper, we use the CRA, and the debate that emerged from it, to develop a philosophical critique of recent advances in robotics and neuroscience. We describe results from a body of work that contributes to blurring the divide (...) between biological and artificial systems; so-called animats, autonomous robots that are controlled by biological neural tissue and what may be described as remote-controlled rodents, living animals endowed with augmented abilities provided by external controllers. We argue that, even though at first sight, these chimeric systems may seem to escape the CRA, on closer analysis, they do not. We conclude by discussing the role of the body–brain dynamics in the processes that give rise to genuine understanding of the world, in line with recent proposals from enactive cognitive science. (shrink)

In the field of cybernetic systems and more specifically in robotics, one of the fundamental objectives is the detection of anomalies in order to minimize loss of time. Following this idea, this paper proposes the implementation of a Hybrid Intelligent System in four steps to impute the missing values, by combining clustering and regression techniques, followed by balancing and classification tasks. This system applies regression models to each one of the clusters built on the instances of data set. Subsequently, a (...) variety of balancing techniques are applied to improve the classifier’s ability to discern whether it is in an error or a normal state. These techniques support to obtain better classification ratios in which a robot is close to error and allow us to bring the behavior back to a normal state. The experimentation is performed using a modern and public data set, which has been extracted from a component-based robotic system, in which different anomalies are induced by software in their components. (shrink)

We have been accustomed at least since Kant and mainstream history of philosophy to distinguish between the ‘mechanical’ and the ‘teleological’; between a fully mechanistic, quantitative science of Nature exemplified by Newton and a teleological, qualitative approach to living beings ultimately expressed in the concept of ‘organism’ – a purposive entity, or at least an entity possessed of functions. The beauty of this distinction is that it seems to make intuitive sense and to map onto historical and conceptual constellations in (...) medicine, physiology and the related natural -philosophical discussions on the status of the body versus that of the machine. In this presentation I argue that the distinction between mechanism and teleology is imprecise and flawed, on the basis of a series of examples: the presence of ‘functional’ or ‘purposive’ features even in Cartesian physiology; work such as that of Richard Lower’s on animal respiration; the fact that the model of the ‘body-machine’ is not at all a mechanistic reduction of organismic properties to basic physical properties but on the contrary a way of emphasizing the uniqueness of organic life; and the concept of ‘animal economy’ in vitalist medical theory, which I present as a kind of ‘teleo-mechanistic’ concept of organism – neither mechanical nor teleological. (shrink)

We propose a novel edge detector in the presence of Gaussian noise with the use of proximal support vector machine (PSVM). The edges of a noisy image are detected using a two-stage architecture: smoothing of image is first performed using regularized anisotropic diffusion, followed by the classification using PSVM, termed as regularized anisotropic diffusion-based PSVM (RAD-PSVM) method. In this process, a feature vector is formed for a pixel using the denoised coefficient’s class and the local orientations to detect edges (...) in all possible directions in images. From the experiments, conducted on both synthetic and benchmark images, it is observed that our RAD-PSVM approach outperforms the other state-of-the-art edge detection approaches, both qualitatively and quantitatively. (shrink)

Due to the inherent chaotic and fractal dynamics in the price series of Bitcoin, this paper proposes a two-stage Bitcoin price prediction model by combining the advantage of variational mode decomposition and technical analysis. VMD eliminates the noise signals and stochastic volatility in the price data by decomposing the data into variational mode functions, while technical analysis uses statistical trends obtained from past trading activity and price changes to construct technical indicators. The support vector regression accepts input from a hybrid (...) of technical indicators and reconstructed variational mode functions. The model is trained, validated, and tested in a period characterized by unprecedented economic turmoil due to the COVID-19 pandemic, allowing the evaluation of the model in the presence of the pandemic. The constructed hybrid model outperforms the single SVR model that uses only TI and rVMF as features. The ability to predict a minute intraday Bitcoin price has a huge propensity to reduce investors’ exposure to risk and provides better assurances of annualized returns. (shrink)

The present study addresses the fluid transport behaviour of the flow of gold -copper /biomagnetic blood hybrid nanofluid in an inclined irregular stenosis artery as a consequence of varying viscosity and Lorentz force. The nonlinear flow equations are transformed into dimensionless form by using nonsimilar variables. The finite-difference technique is involved in computing the nonlinear transport dimensionless equations. The significant parameters like angle parameter, the Hartmann number, changing viscosity, constant heat source, the Reynolds number, and nanoparticle volume fraction on the (...) flow field are exhibited through figures. Present results disclose that the Lorentz force strongly lessens the hybrid nanofluid velocity. Elevating the Grashof number values enhances the rate of blood flow. Growing values of the angle parameter cause to reduce the resistance impedance on the wall. Hybrid nanoparticles have a superior wall shear stress than copper nanoparticles. The heat transfer rate is amplifying at the axial direction with the growing values of nanoparticles concentration. The applied Lorentz force significantly reduces the hybrid and unitary nanofluid flow rate in the axial direction. The hybrid nanoparticles expose a supreme rate of heat transfer than the copper nanoparticles in a blood base fluid. Compared to hybrid and copper nanofluid, the blood base fluid has a lower temperature. (shrink)

Drawing on a global sample of microfinance institutions (MFIs), this paper offers insights into the trade-off versus synergy debate of adopting multiple institutional goals in hybrid organisations. Additionally, it unravels which organisation- and country-specific determinants associate with top joint performance using machine-learning techniques. We find that the synergy versus trade-off debate is not dichotomous. Rather, MFIs can be strong both socially and financially but not while charging low interest rates. In our sample, 17% of MFIs serve a low-income clientele (...) in need with a diverse range of services while remaining financially sustainable and ask a close-to-average interest rate. These organisations are larger and more mature as well as financially prudent in that they minimize both financial and credit risk. Moreover, they are located in countries where their services can create larger benefits regarding their underlying goals. (shrink)

A prominent objection to non-cognitive moral bio-enhancements is that they would compromise the recipient’s ‘freedom to fall’. I begin by discussing some ambiguities in this objection, before outlining an Aristotelian reading of it. I suggest that this reading may help to forestall Persson and Savulescu’s ‘God-Machine’ criticism; however, I suggest that the objection still faces the problem of explaining why the value of moral conformity is insufficient to outweigh the value of the freedom to fall itself. I also question (...) whether the objection is compatible with Neil Levy’s parity principle. Accordingly, I go on to consider an alternative relational freedom-based objection to NCMBEs that aims to explain the fundamental moral importance of the freedom that NCMBEs would violate. I argue that although this strategy might allow the critic of NCMBEs to bypass a powerful criticism of Harris’ objection, it also weakens the freedom-based objection’s compatibility with the parity principle. (shrink)

Surveillance programs supporting the management of One Health issues such as antibiotic resistance are complex systems in themselves. Designing ethical surveillance systems is thus a complex task (retroactive and iterative), yet one that is also complicated to implement and evaluate (e.g., sharing, collaboration, and governance). The governance of health surveillance requires attention to ethical concerns about data and knowledge (e.g., performance, trust, accountability, and transparency) and empowerment ethics, also referred to as a form of responsible self-governance. Ethics in reflexive governance (...) operates as a systematic critical-thinking procedure that aims to define its value: What are the “right” criteria to justify how to govern “good” actions for a “better” future? The objective is to lay the foundations for a methodological framework in empirical bioethics, the rudiments of which have been applied to a case study to building reflexive governance in One Health. This ongoing critical thinking process involves “mapping, framing, and shaping” the dynamics of interests and perspectives that could jeopardize a “better” future. This paper proposes to hybridize methods to combine insights from collective deliberation and expert evaluation through a reflexive governance functioning as a community-based action-ethics methodology. The intention is to empower individuals and associations in a dialogue with society, which operation is carried out using a case study approach on data sharing systems. We based our reasoning on a feasibility study conducted in Québec, Canada (2018–2021), envisioning an antibiotic use surveillance program in animal health for 2023. Using the adaptive cycle and governance techniques and perspectives, we synthesize an alternative governance model rooted in the value of empowerment. The framework, depicted as a new “research and design (R&D)” practice, is linking operation and innovation by bridging the gap between Reflexive, Evaluative, and Deliberative reasonings and by intellectualizing the management of democratizing critical thinking locally (collective ethics) by recognizing its context (social ethics). Drawing on the literature in One Health and sustainable development studies, this article describes how a communitarian and pragmatic approach can broaden the vision of feasibility studies to ease collaboration through public-private-academic partnerships. The result is a process that “reassembles” the One Health paradigm under the perspective of global bioethics to create bridges between the person and the ecosystem through pragmatic ethics. (shrink)

Cervical spinal cord injuries often lead to loss of motor function in both hands and legs, limiting autonomy and quality of life. While it was shown that unilateral hand function can be restored after SCI using a hybrid electroencephalography/electrooculography brain/neural hand exoskeleton, it remained unclear whether such hybrid paradigm also could be used for operating two hand exoskeletons, e.g., in the context of bimanual tasks such as eating with fork and knife. To test whether EEG/EOG signals allow for fluent and (...) reliable as well as safe and user-friendly bilateral B/NHE control, eight healthy participants as well as four chronic tetraplegics performed a complex sequence of EEG-controlled bilateral grasping and EOG-controlled releasing motions of two exoskeletons visually presented on a screen. A novel EOG command performed by prolonged horizontal eye movements to the left or right was introduced as a reliable switch to activate either the left or right exoskeleton. Fluent EEG control was defined as average “time to initialize” grasping motions below 3 s. Reliable EEG control was assumed when classification accuracy exceeded 80%. Safety was defined as “time to stop” all unintended grasping motions within 2 s. After the experiment, tetraplegics were asked to rate the user-friendliness of bilateral B/NHE control using Likert scales. Average TTI and accuracy of EEG-controlled operations ranged at 2.14 ± 0.66 s and 85.89 ± 15.81% across healthy participants and at 1.90 ± 0.97 s and 81.25 ± 16.99% across tetraplegics. Except for one tetraplegic, all participants met the safety requirements. With 88 ± 11% of the maximum achievable score, tetraplegics rated the control paradigm as user-friendly and reliable. These results suggest that hybrid EEG/EOG B/NHE control of two assistive devices is feasible and safe, paving the way to test this paradigm in larger clinical trials performing bimanual tasks in everyday life environments. (shrink)

Today, new artistic practices incorporate scientific techniques linked to medical research that modify the body’s biological performance in vivo, transforming it into a singular laboratory object. In this way, some artists are making works of their bodies by subjecting them to various biotechnological procedures, often invasive. Augmented, the biological body of these performance artists becomes a site for experimentation. DIY (Do It Yourself) enthusiasts or accompanied by biologists and doctors, are these ‘bio-artists’ evidence of the changes brought about by a (...) new mechanisation of the human body, the complexity of which we are only just beginning to understand? Could there be, in the name of art, reasons that justify the creation of utopian bodies that are not eschatological, and that could make us believe in the worst or the best of all worlds? Based on performances by Stelarc, Yann Marussich, Marion Laval-Jeantet and the Quimera Rosa duo, our aim is to analyse what is at stake in this new fabrication of the body outside its biological limits. (shrink)

As machines take over more tasks previously done by humans, artistic creation is also considered as a candidate to be automated. But, can machines create art? This paper offers a conceptual framework for a philosophical discussion of this question regarding the status of machine art and machine creativity. It breaks the main question down in three sub-questions, and then analyses each question in order to arrive at more precise problems with regard to machine art and machine (...) creativity: What is art creation? What do we mean by art? And, what do we mean by machines create art? This then provides criteria we can use to discuss the main question in relation to particular cases. In the course of the analysis, the paper engages with theory in aesthetics, refers to literature on computational creativity, and contributes to the philosophy of technology and philosophical anthropology by reflecting on the role of technology in art creation. It is shown that the distinctions between process versus outcome criteria and subjective versus objective criteria of creativity are unstable. It is also argued that we should consider non-human forms of creativity, and not only cases where either humans or machines create art but also collaborations between humans and machines, which makes us reflect on human-technology relations. Finally, the paper questions the very approach that seeks criteria and suggests that the artistic status of machines may be shown and revealed in the human/non-human encounter before any theorizing or agreement takes place; an experience which then is presupposed when we theorize. This hints at a more general model of what happens in artistic perception and engagement as a hybrid human-technological and emergent or even poetic process, a model which leaves more room for letting ourselves be surprised by creativity—human and perhaps non-human. (shrink)

Until now, the mass spread of fake news and its negative consequences have implied mainly textual content towards a loss of citizens' trust in institutions. Recently, a new type of machine learning framework has arisen, Generative Adversarial Networks (GANs) – a class of deep neural network models capable of creating multimedia content (photos, videos, audio) that simulate accurate content with extreme precision. While there are several areas of worthwhile application of GANs – e.g., in the field of audio-visual production, (...) human-computer interactions, satire, and artistic creativity – their deceptive uses, at least as currently foreseeable, are just as numerous and worrying. The main concern is linked to the so-called “deepfakes”, fake images or videos that simulate real events with extreme precision. When trained on a human face, GANs can make the face assume hyper-realistic movements, expressions and (verbal and non-verbal) communication abilities. This technology poses an urgent threat to the governance of democratic processes concerning the production of public opinions and political discourses, with significant potential for reality-altering and disinformation. After a short introduction of their current technical state-of-the-art, in this paper we want to enquire the GANs` socio-technical system alongside different and intertwined philosophical accounts. Firstly, we will argue about the conditions that make perceived a GANs-generated content as trustworthy, arguing also about the general effects GANs might have on the perceived trustworthiness of individuals. Thereafter, we will discuss about the inadequacy to approach GANs only as perception-altering technology. Against this backdrop, we will propose a theoretical turn that considers the human-machine relationships of trustworthiness as elements of a broader hybrid socio-technical systems. This turn come up with political repercussions that we will discuss in the last part of the paper. (shrink)

In Weaving the Web, Berners-Lee defines Social Machines as biotechnologically hybrid Web-processes on the basis of which, “high-level activities, which have occurred just within one human’s brain, will occur among even larger more interconnected groups of people acting as if the shared a larger intuitive brain”. The analysis and design of Social Machines has already started attracting considerable attention both within the industry and academia. Web science, however, is still missing a clear definition of what a Social Machine is, (...) which has in turn resulted in several calls for a “philosophical engineering” ; Halpin et al. 2010). This paper is a first attempt to respond to this call, by combining contemporary philosophy of mind and cognitive science with epistemology. The idea of philosophical engineering implies that a sufficiently good conception of Social Machines should be of both theoretical and practical advantage. To demonstrate how the present approach can satisfy both objectives it will be used in order to address one of Wikipedia’s most worrying concerns—i.e., the current and ongoing decline in the number of its active contributors. (shrink)

This article provides an extract from the second half of Lestel's book Animality . His book is divided into two parts. In the first part Lestel considers a number of ways in which humans and animals have been represented, particularly with respect to their supposed differences and borderline cases, over the course of Western history. To this end one reads of various depictions, construc- tions, and erasures of animals, including those of feral children, the animal-machines of Des- cartes and company, (...) animals of ethological study, as well as artistic animals, suffering animals, speaking animals, cultural animals, and more. The first part is largely devoted, then, to past representations of animals as seen through Lestel's unique perspective. The second part, much of which is translated here, conveys Lestel's own observations, as developed most explicitly in his concept of “hybrid com- munities” between humans and animals. It is equal parts evolutionary and cultural anthropol- ogy, ethologi.. (shrink)

A new political technology emerged at the heart of Modernity, a machine called bio-power. In fact, preserving living beings is to be ensured by power. This essay aims to describe the main features of this technology of power, beginning with an initial sketch on Michel Foucault's method—a nominalist one—, followed by an examination of three perspectives on power and, finally, showing how something like an explosion and a quick development of several technologies subjugating bodies and controlling population were imposed (...) during the classical period. (shrink)

Grasping the identity of hybrids, that is beings which cross the binarism of nature and technology (e.g. genetically-modified organisms (GMOs), syn-bio inventions, biomimetic projects), is problematic since it is still guided by self-evident dualistic categories, either as artefacts or as natural entities. To move beyond the limitations of such a one-sided understanding of hybrids, we suggest turning towards the categories of affordances and the juxtaposition of needs and patterns of proper use, as inspired by the Heideggerian version of (...) phenomenology. Drawing upon selected concepts by Heidegger, we argue that hybrids can be conceptualised as a regenerative design and use to serve the planet. We argue that the ideal type of non-exploitative account of hybrids consists of the adaptive approach to the environment, which does not, however, exclude the possibility of designing and constructing new beings. We also point out that hybrids undermine the divide of being destructive/regenerative which marks the boundaries of nature and technology. (shrink)

Depression has become one of the most common mental illnesses, and the widespread use of social media provides new ideas for detecting various mental illnesses. The purpose of this study is to use machine learning technology to detect users of depressive patients based on user-shared content and posting behaviors in social media. At present, the existing research mostly uses a single detection method, and the unbalanced class distribution often leads to a low recognition rate. In addition, a large number (...) of irrelevant or redundant features in high-dimensional data sets interfere with the accuracy of recognition. To solve this problem, this paper proposes a hybrid feature selection and stacking ensemble strategy for depression user detection. First, recursive elimination method and extremely randomized trees method are used to calculate feature importance and mutual information value, calculate feature weight vector, and select the optimal feature subset according to the feature weight. Second, naive bayes, k-nearest neighbor, regularized logistic regression and support vector machine are used as base learners, and a simple logistic regression algorithm is used as a combination strategy to build a stacking model. Experimental results show that compared with other machine learning algorithms, the proposed hybrid method, which integrates feature selection and ensemble, has a higher accuracy of 90.27% in identifying online patients. We believe this study will help develop new methods to identify depressed people in social networks, providing guidance for future research. (shrink)

A computer-based language system exploring hybrid invention generation has been developed by Bill Seaman working in conjunction with the programmer Gideon May.1 The project was primarily funded by Intel. This work explores 3D visualization with related generative texts and recombinant audio/music, as well as a series of textual descriptions. Computer-based environmental meaning is explored through the inter-authorship and operative experiential examination of a diverse set of media-elements and media-processes, in this case focusing on the virtual construction of hybrid inventions. Differing (...) sets of media elements in the Hybrid Invention Generator convey their own fields of meaning through the juxtaposition of 3D models, texts and digital audio. Varying combinations of these fields of meaning are experienced through direct interaction with the system. The work explores notions surrounding machinic genetics. Nonsense relations can present seemingly off-kilter juxtapositions, providing the participant with an experience akin to surrealism. Lautréamont’s definition of surrealist beauty - ‘beautiful as the unexpected meeting, on a dissection table, of a sewing machine and an umbrella’ (Waldberg 1965) - describes an experience engendered through a unique juxtaposition of elements not unlike relations encountered within this particular techno-poetic environment. Yet the system can also be used to brainstorm actual devices, as well as their potential conceptual/functional construction. (shrink)

Automatic control of physiological variables is one of the most active areas in biomedical engineering. This paper is centered in the prediction of the analgesic variables evolution in patients undergoing surgery. The proposal is based on the use of hybrid intelligent modelling methods. The study considers the Analgesia Nociception Index to assess the pain in the patient and remifentanil as intravenous analgesic. The model proposed is able to make a one-step-ahead prediction of the remifentanil dose corresponding to the current state (...) of the patient. The input information is the previous remifentanil dose, the ANI variable and the electromyogram signal. Modelling techniques used are Artificial Neural Networks and Support Vector machines for Regression combined with clustering methods. Both training and validation were done with a real dataset from different patients. Results obtained show the potential of this methodology to calculate the drug dose corresponding to a given analgesic state of the patient. (shrink)

With the increasing degrees A.I.s and machines are applied across different social contexts, the need for implementing ethics in A.I.s is pressing. In this paper, we argue for a pluralist hybrid model for the implementation of moral A.I.s. We first survey current approaches to moral A.I.s and their inherent limitations. Then we propose the pluralist hybrid approach and show how these limitations of moral A.I.s can be partly alleviated by the pluralist hybrid approach. The core ethical decision-making capacity of an (...) A.I. based on the pluralist hybrid approach consists of two systems. The first is a deterministic algorithm system that incorporates different moral rules for making explicit moral decisions. The second is a machine learning system that calculates the value of the variables required by the application of moral principles. The pluralist hybrid system is better than the existing proposals as (i) it better addresses the moral disagreement problem of the top-down approach by including different moral principles, while (ii) it reduces the opacity of ethical decision-making compared with a bottom-up system by implementing explicit moral principles for moral decision making. (shrink)

Anthropogenic changes in the biosphere, driven mainly by human cultural habits and technological advances, are altering the direction of evolution on Earth, with ongoing and permanent changes modifying uncountable interactions between organisms, the environment, and humankind itself. While numerous species may go extinct, others will be favored due to strong human influences. The Bio-Evolutionary Anthropocene hypothesizes that directly or indirectly human-driven organisms, including alien species, hybrids, and genetically modified organisms, will have major roles in the evolution of life on (...) Earth, shifting the evolutionary pathways of all organisms through novel biological interactions in all habitats. We anticipate that, in future scenarios, novel organisms will be continuously created, and contemporary native organisms with no obvious economic use will decline—while anthropogenic-favored and novel organisms will spread. The Bio-Evolutionary Anthropocene hypothesis therefore predicts that humankind and novel organisms will interact within a strong evolutionary bias that will lead to unexpected, and probably irreversible, outcomes for the evolution of life on our planet. (shrink)

In recent years, neural networks have attracted much attention in the machine learning and the deep learning technologies. Bio-inspired functions and intelligence are also expected to process efficiently and improve existing technologies. In the visual pathway, the prominent features consist of nonlinear characteristics of squaring and rectification functions observed in the retinal and visual cortex networks, respectively. Further, adaptation is an important feature to activate the biological systems, efficiently. Recently, to overcome short-comings of the deep learning techniques, orthogonality for (...) the weights in the networks has been developed for the signal propagation and the efficient optimization of the learning. In this paper, bio-inspired asymmetric networks with nonlinear characteristics are proposed, which are derived from the retinal networks in the biological visual pathway. The asymmetric network proposed here was verified to detect the movement of the object, efficiently in our previous studies. This paper shows a new characteristic of the adaptive orthogonality in the asymmetric networks. First, it is shown that the asymmetric network with nonlinear characteristics is effective for generating orthogonality. Second, the proposed asymmetric network with Gabor filters is compared with the conventional energy model from the point of the orthogonality characteristics. Finally, the asymmetric networks with nonlinear characteristics can generate the extended orthogonal bases in independent subspaces, which are useful for classification and efficient learning. (shrink)

Clustering is one of the most fundamental and essential data analysis tasks with broad applications. It has been studied in various research fields: data mining, machine learning, pattern recognition and in engineering, economics and biomedical data analysis. Headache is not a disease that typically shortens one’s life, but it can be a serious social as well as a health problem. Approximately 27 billion euros per year are lost through reduced work productivity in the European community. This paper is focused (...) on a new strategy based on a hybrid model for combining fuzzy partition method and maximum likelihood estimation clustering algorithm for diagnosing primary headache disorder. The proposed hybrid system is tested on two data sets for diagnosing headache disorder collected from Clinical Centre of Vojvodina in Serbia. (shrink)

The impact of Online Social Networks on human lives is foreseen to be very large with unprecedented amount of data and users. OSN users share their ideas, photos, daily life events, feelings and news. Since OSNs’ security and privacy challenges are more potential than ever before, it is necessary to enhance the protection and filtering approaches of OSNs contents. This paper explores OSNs’ threats and challenges, and categorize them into: account-based, URL-based and content-based threats. In addition, we analyze the existing (...) protection methods and highlight their limitations and weaknesses. Based on that, we propose a comprehensive, user-level, proactive and real-time OSNs’ protection system, called Hybrid Real-time Social Networks Protector. HRSP has three components; a user-level security protocol and two classification models. The protocol defines a structure for OSN’s cryptographic services, including encryption, access control and users’ authentication. The classification models employ machine learning, black lists, white lists and users’ feedback, in order to classify URLs into: Benign, Risk and Inappropriate classes, and contents into: Benign, Hate speech and Inappropriate classes. We constructed two data sets of 150,000 URLs and 22,000 tweets to build and test the two classification models. Results show an overall accuracy of 93.2% for the URL model and 84.4% for the content model, while the protocol implementation produces compatible size and time overhead. The components of HRSP are integrated and have compatible design with OSN platforms. (shrink)

Due to the huge amount of data being generating from different sources, the analyzing and extracting of useful information from these data becomes a very complex task. The difficulty of dealing with big data optimization problems comes from many factors such as the high number of features, and the existing of lost data. The feature selection process becomes an important step in many data mining and machine learning algorithms to reduce the dimensionality of the optimization problems and increase the (...) performance of the classification or clustering algorithms. In this paper, a set of hybrid and efficient genetic algorithms are proposed to solve feature selection problem, when the handled data has a large feature size. The proposed algorithms use a new gene-weighted mechanism that can adaptively classify the features into strong relative features, weak or redundant features, and unstable features during the evolution of the algorithm. Based on this classification, the proposed algorithm gives the strong features high priority and the weak features less priority when generating new candidate solutions. In the same time, the proposed algorithm tries to more concentrate on unstable features that sometimes appear and sometimes disappear from the best solutions of the population. The performance of proposed algorithms is investigated by using different datasets and feature selection algorithms. The results show that our proposed algorithms can outperform the other feature selection algorithms and effectively enhance the classification performance over the tested datasets. (shrink)

Advances in machine learning and natural language processing are revolutionizing the way we live, work, and think. As for any science, they are based on assumptions about what the world is, and how humans interact with it. In this paper, I discuss what is potentially one of these assumptions: structuralism, which states that all cultures share a hidden structure. I illustrate this assumption with political footprints: a machine-learning technique using pre-trained word vectors for political discourse analysis. I introduce (...) some of the benefits and limitations of structuralism when applied to machine learning, and the risks of exploiting a technology before establishing the validity of all its hypotheses. I consider how machine-learning techniques could evolve towards hybrid structuralism or post-structuralism, and how deeply these developments would impact cultural studies. (shrink)

It has been argued that prototypes cannot compose, and that for this reason concepts cannot be prototypes (Osherson and Smith in Cognition 9:35–58, 1981; Fodor and Lepore in Cognition 58:253–270, 1996; Connolly et al. in Cognition 103:1–22, 2007). In this paper I examine the intensional and extensional approaches to prototype compositionality, arguing that neither succeeds in their present formulations. I then propose a hybrid extensional theory of prototype compositionality, according to which the extension of a complex concept is determined as (...) a function of what triggers its constituent prototypes. I argue that the theory escapes the problems traditionally raised against extensional theories of compositionality. (shrink)

Umbilical cord blood has become the focus of intense efforts to collect, screen and bank haematopoietic stem cells in hundreds of repositories around the world. UCB banking has developed through a broad spectrum of overlapping banking practices, sectors and institutional forms. Superficially at least, these sectors have been widely distinguished in bioethical and policy literature between notions of the ‘public’ and the ‘private’, the commons and the market respectively. Our purpose in this paper is to reflect more critically on these (...) distinctions and to articulate the complex practical and hybrid nature of cord blood as a ‘bio-object’ that straddles binary conceptions of the blood economies. The paper draws upon Roberto Esposito’s reflections on biopolitics and his attempt to transcend the dualistic polarisations of immunity and community, or the private and the public. We suggest that his thoughts on immunitary hospitality resonate with many of the actual features and realpolitik of a necessarily internationalised and globally distributed UCB ‘immunitary regime’. (shrink)

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

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

Advances in machine learning and natural language processing are revolutionizing the way we live, work, and think. As for any science, they are based on assumptions about what the world is, and how humans interact with it. In this paper, I discuss what is potentially one of these assumptions: structuralism, which states that all cultures share a hidden structure. I illustrate this assumption with political footprints: a machine-learning technique using pre-trained word vectors for political discourse analysis. I introduce (...) some of the benefits and limitations of structuralism when applied to machine learning, and the risks of exploiting a technology before establishing the validity of all its hypotheses. I consider how machine-learning techniques could evolve towards hybrid structuralism or post-structuralism, and how deeply these developments would impact cultural studies. (shrink)

Amongst philosophers, there is ongoing debate about what successful event remembering requires. Causal theorists argue that it requires a causal connection to the past event. Simulation theorists argue, in contrast, that successful remembering requires only production by a reliable memory system. Both views must contend with the fact that people can remember past events they have experienced with varying degrees of accuracy. The debate between them thus concerns not only the account of successful remembering, but how each account explains the (...) various forms of memory error as well. Advancing the debate therefore must include exploration of the cognitive architecture implicated by each view and whether that architecture is capable of producing the range of event representations seen in human remembering. Our paper begins by exploring these architectures, framing casual theories as best suited to the storage of event instances and simulation theories as best suited to store schemas. While each approach has its advantages, neither can account for the full range of our event remembering abilities. We then propose a novel hybrid theory that combines both instance and schematic elements in the event memory. In addition, we provide an implementation of our theory in the context of a cognitive architecture. We also discuss an agent we developed using this system and its ability to remember events in the blocks world domain. (shrink)

The article is based on reports and discussions held during three online events organized by the Russian Research Center for the Internet of Things together with the Department of Philosophy and Sociology of South-West State University during 2021: an open discussion with the famous transhumanist philosopher David Pearce dedicated to the birthday of Jeremiah Bentham on February 15, a round table dedicated to the World Internet of Things Day on April 9, and a session within the first IoT Hot Spots (...) conference on June 16. The main topics for discussion this year were the consideration of the following philosophical and socio-cultural problems and concepts in the light of the development of cyberphysical systems: anthropological differences between the «posthuman» and «metahuman» projects, epistemological aspects of bio- and cybersemiotics in modern hybrid techno-social networks, the cultural dimension of remote proximity in the digital age, the ontology of the quantum complexity of the digital multiverse, the ethical dimensions of the digital economy in the post-covid period, the aesthetics of metamodernism in the smart city, the anthropocene effects of silicon addiction and the race of computing, socio-philosophical problems of management in situations of high uncertainty, political strategies for sustainable development. (shrink)

Longtemps restée marginale à l’intérieur des études théâtrales, la théorie du drame d’Étienne Souriau fait l’objet d’une redécouverte liée à « l’évènement anthropocène ». Souriau fait du théâtre un hybride entre le vivant et la machine et opère un renversement entre la scène et le hors-champ grâce à une théorisation de la « situation » en de nombreux point opposée à celle de Sartre.

With a focus in the financial market, stock market dynamics forecasting has received much attention. Predicting stock market fluctuations is usually challenging due to the nonlinear and nonstationary time series of stock prices. The Elman recurrent network is renowned for its capability of dealing with dynamic information, which has made it a successful application to predicting. We developed a hybrid approach which combined Elman recurrent network with factorization machine technique, i.e., the FM-Elman neural network, to predict stock market volatility. (...) In this paper, the Standard & Poor’s 500 Composite Stock Price index, the Dow Jones industrial average index, the Shanghai Stock Exchange Composite index, and the Shenzhen Securities Component Index were used to demonstrate the validity of our proposed FM-Elman model in time-series prediction. The results were compared with predictions obtained from the other two models which are basic BP neural network and the Elman neural network. Some experiments showed that the FM-Elman model outperforms others through different accuracy measures. Furthermore, the effects of volatility degree on prediction performance from different stock indexes were investigated. An interesting phenomenon had been found through some numerical experiments on the effects of different user-specified dimensions on the proposed FM-Elman neural network. (shrink)

In the context of 1960s research on biological membranes, scientists stumbled upon a curiously coloured material substance, which became called the “purple membrane.” Interactions with the material as well as chemical analyses led to the conclusion that the microbial membrane contained a photoactive molecule similar to rhodopsin, the light receptor of animals’ retinae. Until 1975, the find led to the formation of novel objects in science, and subsequently to the development of a field in the molecular life sciences that comprised (...) biophysics, bioenergetics as well as membrane and structural biology. Furthermore, the purple membrane and bacteriorhodopsin, as the photoactive membrane transport protein was baptized, inspired attempts at hybrid bio-optical engineering throughout the 1980s. A central motif of the research field was the identification of a functional biological structure, such as a membrane, with a reactive material substance that could be easily prepared and manipulated. Building on this premise, early purple membrane research will be taken as a case in point to understand the appearance and transformation of objects in science through work with material substances. Here, the role played by a perceptible material and its spontaneous change of colour, or reactivity, casts a different light on objects and experimental practices in the late twentieth century molecular life sciences. With respect to the impact of chemical working and thinking, the purple membrane and rhodopsins represent an influential domain straddling the life and chemical sciences as well as bio- and material technologies, which has received only little historical and philosophical attention. Re-drawing the boundary between the living and the non-enlivened, these researches explain and model organismic activity through the reactivity of macromolecular structures, and thus palpable material substances. (shrink)

Anthropogenic changes in the biosphere, driven mainly by human cultural habits and technological advances, are altering the direction of evolution on Earth, with ongoing and permanent changes modifying uncountable interactions between organisms, the environment, and humankind itself. While numerous species may go extinct, others will be favored due to strong human influences. The Bio-Evolutionary Anthropocene hypothesizes that directly or indirectly human-driven organisms, including alien species, hybrids, and genetically modified organisms, will have major roles in the evolution of life on (...) Earth, shifting the evolutionary pathways of all organisms through novel biological interactions in all habitats. We anticipate that, in future scenarios, novel organisms will be continuously created, and contemporary native organisms with no obvious economic use will decline—while anthropogenic-favored and novel organisms will spread. The Bio-Evolutionary Anthropocene hypothesis therefore predicts that humankind and novel organisms will interact within a strong evolutionary bias that will lead to unexpected, and probably irreversible, outcomes for the evolution of life on our planet. (shrink)

ABSTRACT Scientific advances in genetic analysis have been made possible in recent years by technical developments in computational biology, or bioinformatics. Bioinformatics has opened up the human genome to diverse analyses involving automated laboratory hardware and machine learning algorithms and software. As part of an emerging field of social genomics, recent educational genetics studies using big data have begun to raise challenging findings linking DNA to predicted life outcomes. Bioinformatic technologies and techniques including ‘genome-wide association’ and ‘polygenic scoring’ are (...) producing new kinds of genetic biodata and expert knowledge for rethinking the upbringing and education of children. This article takes as an empirical opening a recent epistemic and ethical controversy over the use of biodata to make genetic predictions about educational, socio-economic and life outcomes, detailing the forms of expert knowledge and technologies involved these predictions, and exploring the social and ethical implications of data-intensive bioinformatics. (shrink)

This paper addresses three aspects of Bio Art: iconography, artificial life, and wetware. The development of models for innovation require hybrid practices which generate knowledge through epistemic experimental practices. The intersection of art and the biological sciences contain both scientific data as well as the visualization of its cultural imagination. In the Bio Art Lab at the School of Visual Arts, artists use the tools of science to make art.

Accurate wind speed forecasting is an effective way to improve the safety and stability of power grid. A novel hybrid model based on twice decomposition, phase space reconstruction, and an improved multiverse optimizer-extreme learning machine is proposed to enhance the performance of short-term wind speed forecasting in this paper. In consideration of the nonstationarity of the wind speed signal, a twice decomposition based on improved complete ensemble empirical mode decomposition with adaptive noise, fuzzy entropy, and variational mode decomposition is (...) proposed to reduce the nonstationarity of the original signal firstly. Then the PSR based on C-C method is employed to reconstitute the decomposed signal as the input of the prediction model. Lastly, an improved multiverse optimizer is proposed to improve the stability and efficiency of ELM which is used as prediction model. Furthermore, two experiments are designed to verify the performance of the proposed method; the results indicate that the wind speed forecasting with twice decomposition of original wind speed signal is better than other once-decomposition methods and much better than forecasting without decomposition; the C-C-PSR method can determine the input dimension of ELM and improve the prediction accuracy of ELM; the IMVO has improved the stability of ELM, and the optimization efficiency is better than other comparison optimization methods. The results show that the proposed hybrid approach is a useful tool for short-term wind speed forecasting. (shrink)