Systems, machines and organisation of forms developed in the Engineering and Manufacturing sectors frequently lay the basis for systems design philosophy at a general level. An analysis of technological change in these sectors reveals that the resultant deskilling is not limited to the shop floor and is now spreading to intellectual work. The impact of ‘machine based systems’ on designers is explored in some detail and suggests the need for alternatives which are based on ‘human (...) centred systems’. Some attempts to design sub-systems are described. (shrink)

Social robots are designed to perform intelligent, emotional, and autonomous behavior in order to establish intimate relationships with humans, for instance, in the context of elderly care. However, the imitation of qualities usually assumed to be necessary for human reciprocal interaction may impact our understanding of social interaction. Against this background, we compare the technical operations based on which social robots imitate human-like behavior with the concepts of emotionality, intelligence, and autonomy as usually attached to humans. In doing (...) so, we aim at making a conceptual contribution to the intuition that the technical imitation of emotional, intelligent, and autonomous behavior differs qualitatively from human forms of emotionality, intelligence, and autonomy. We conclude that the increasing tendency of social robots to imitate human characteristics and the thus increased human tendency of anthropomorphizing technical systems put forth new forms of human–machine interactions (HMI) that call for a critical examination. Thus, the emerging forms of interaction may lead, for instance, to false, reinforced, and perplexing assumptions regarding reciprocity. Therefore, studies are needed that critically examine the potential consequences and psychological effects that may be associated with the use of social robots, especially with regard to vulnerable groups such as children or the elderly. (shrink)

"Entre mythe, science et technique il existe une longue tradition de l'homme artificiel, des jaquemarts au Golem, de Frankenstein aux robots, comme si nous nous étions longuement complus, par le jeu des métaphores, à nous contempler dans le miroir de nos machines. Il en est résulté une philosophie mécaniste, de Descartes à La Mettrie qu'il faut bien évoquer. Avec la cybernétique et l'informatique, le vivant, l'esprit, la machine sont entrés dans des chevauchements beaucoup plus complexes qui ouvrent sur un (...) néo-mécanisme. Ce terme marque la volonté, au-delà de ce premier mécanisme, de penser la vie et l'intelligence artificielles, la bionique et le cyborg, l'avenir incertain de l'humain vers ce qu'il faudra peut-être appeler le post-humain. Il fallait pour cela un examen minutieux de toutes ces techniques nouvelles. La machine n'est plus seulement le support d'une vague analogie de la vie et de la pensée ; à travers l'homme réparé, augmenté par des prothèses de plus en plus intimement mêlées à la mécanique de l'organisme, elle vit, elle pense, elle raisonne. Nous assistons à la rencontre d'une pensée de l'homme-machine et de la machine humanisée, rencontre que cet ouvrage tente de penser." [Source : 4e de couv.]. (shrink)

This paper uses a proof of Gödels theorem, implemented on a computer, to explore how a person or a computer can examine such a proof, understand it, and evaluate its validity. It is argued that, in order to recognize it (1) as Gödel's theorem, and (2) as a proof that there is an undecidable statement in the language of PM, a person must possess a suitable semantics. As our analysis reveals no differences between the processes required by people and machines (...) to understand Gödel's theorem and manipulate it symbolically, an effective way to characterize this semantics is to model the human cognitive system as a Turing Machine with sensory inputs. La logistique n'est plus stérile: elle engendre la contradicion! – Henri Poincaré ‘Les mathematiques et la logique’. (shrink)

Ethical dissonance arises from conflicts between beliefs or behaviors and affects ethical factors such as normality or conformity. This paper proposes a weak signal-oriented framework to investigate ethical dissonance from experiences linked to human–machine interactions. It is based on a systems engineering principle called human-systems inclusion, which considers any experience feedback of weak signals as beneficial to learn. The framework studies weak signal-based scenarios from testimonies of individual experiences and these scenarios are assessed by other (...) people. For this purpose, the framework proposes several databases as sources of weak signals, formalization tools of experience feedback of weak signals, models of references of conformity, ethical factors, and a list of examples of ethical dissonance. It also includes sequential steps to make the latter credible regarding the results from the experimental protocols. The framework was used to investigate ethical dissonance by analyzing experiences pertaining to achieving inclusive mobility. The first example focuses on ethical dissonance in terms of hindrance that goes against autonomous mobility due to a misunderstanding of how the system functions in terms of negative and positive emotions. Two other examples present possible ethical dissonance when the use of safety systems such as car driver-assistance systems, may create danger. Investigating ethical dissonance can then help system-inclusive design or evaluation processes by taking into account scenarios from weak signal-based experiences and making them credible. (shrink)

Recent advances in neuroscience lead to a wider realm for philosophy to include the science of the Darwinian-evolved computational brain, our inner world producing organ, a non-recursive super- Turing machine combining 100B synapsing-neuron DNA-computers based on the genetic code. The whole system is a logos machine offering a world map for global context, essential for our intentional grasp of opportunities. We start from the observable contrast between the chaotic universe vs. our orderly inner world, the noumenal cosmos. So (...) far, philosophy has been rehearsing our thoughts, our human-internal world, a grand painting of the outer world, how we comprehend subjectively our experience, worked up by the logos machine, but now we seek a wider horizon, how humans understand the world thanks to Darwinian evolution to adapt in response to the metaphysical gap, the chasm between the human animal and its environment, shaping the organism so it can deal with its variable world. This new horizon embraces global context coded in neural structures that support the noumenal cosmos, our inner mental world, for us as denizens of the outer environment. Kant’s inner and outer senses are fundamental ingredients of scientific philosophy. Several sections devoted to Heidegger, his lizard debunked, but his version of the metaphysical gap & his doctrine of the logos praised. Rorty and others of the behaviorist school discussed also. (shrink)

This book develops an original theoretical framework for understanding human-technology relations. The author's approach, which he calls technoanalysis, analyzes artificial intelligence based on Freudian psychoanalysis, biosemiotics, and Latour's actor-network theory. How can we communicate with AI to determine shared values and objectives? And what, ultimately, do we want from machines? These are crucial questions in our world, where the influence of AI-based technologies is rapidly growing. Unconscious dynamics influence AI and digital technology and understanding them is essential to better (...) controlling AI systems. This book's unique methodology- which combines psychoanalysis, biosemiotics, and actor-network theory-reveals a radical reformulation of the problem of the human mind. Technoanalysis views the mind as a hybrid network of humans and nonhuman actants in constant interaction with one another. The author argues that human unconscious dynamics influence and shape technology, just as technology influences and shapes human unconscious dynamics. He proceeds to show how this conception of the relationship between the unconscious and technology can be applied to social robotics and AI. Unconscious Networks will appeal to scholars and advanced students interested in philosophy of technology, philosophy of artificial intelligence, psychoanalysis, and science and technology studies. (shrink)

There is at present a widespread unease about the direction in which our technology is taking us, apparently against our will. Promising advances seem to carry with them unforeseen negative consequences, including damage to the environment and the reduction of work to the trivial mechanical repetition of actions which have no human meaning. However, attempts to design a better, human-centered technology--one that complements rather than rejects human skills--are all too often frustrated by the prevailing belief that "man (...) is a machine," and one, moreover, that compares badly in terms of performance and durability. This contentious and stimulating book offers a new approach, one that refutes four centuries of science based on strictly causal explanations. It shows that man and nature can be viewed as "machines with a purpose," and that the "purpose" can be the advancement of technology to the benefit and not the detriment of the human race and its environment. This fascinating work is accessible to a wide range of readers, scientists and nonspecialists alike. It will interest anyone concerned about the impact of technology and the way it is shaping our world. (shrink)

Autonomy has been central to moral and political philosophy for millenia, and has been positioned as a critical aspect of both justice and wellbeing. Research in psychology supports this position, providing empirical evidence that autonomy is critical to motivation, personal growth and psychological wellness. Responsible AI will require an understanding of, and ability to effectively design for, human autonomy (rather than just machine autonomy) if it is to genuinely benefit humanity. Yet the effects on human autonomy of (...) digital experiences are neither straightforward nor consistent, and are complicated by commercial interests and tensions around compulsive overuse. This multi-layered reality requires an analysis that is itself multidimensional and that takes into account human experience at various levels of resolution. We borrow from HCI and psychological research to apply a model (“METUX”) that identifies six distinct spheres of technology experience. We demonstrate the value of the model for understanding human autonomy in a technology ethics context at multiple levels by applying it to the real-world case study of an AI-enhanced video recommender system. In the process we argue for the following three claims: 1) There are autonomy-related consequences to algorithms representing the interests of third parties, and they are not impartial and rational extensions of the self, as is often perceived; 2) Designing for autonomy is an ethical imperative critical to the future design of responsible AI; and 3) Autonomy-support must be analysed from at least six spheres of experience in order to approriately capture contradictory and downstream effects. (shrink)

Recent philosophy of mind has increasingly focused on the role of technology in shaping, influencing, and extending our mental faculties. Technology extends the mind in two basic ways: through the creative design of artifacts and the purposive use of instruments. If the meaningful activity of technological artifacts were exhaustively described in these mind-dependent terms, then a philosophy of technology would depend entirely on our theory of mind. In this dissertation, I argue that a mind-dependent approach to technology is mistaken. Instead, (...) some machines are best understood as independent participants in their own right, contributing to and augmenting a variety of social practices as active, though often unrecognized, community members. Beginning with Turing’s call for “fair play for machines”, I trace an argument concerning the social autonomy of nonhuman agents through the artificial intelligence debates of the 20th century. I’ll argue that undue focus on the mind has obscured the force of Turing’s proposal, leaving the debates in an unfortunate stalemate. I will then examine a network theoretic alternative to the study of multi-agent complex systems that can avoid anthropocentric, mind-dependent ways of framing human-machine interactions. I argue that this approach allows for both scientific and philosophical treatment of large and complicated sociotechnical systems, and suggests novel methods for designing, managing, and maintaining such systems. Rethinking machines in mind-independent terms will illuminate the nature, scope, and evolution of our social and technological practices, and will help clarify the relationships between minds, machines, and the environments we share. (shrink)

Explores the relationship between technics and humanity, tracing the emergence of a bio-technical conception of existence in contemporary continental philosophy.

Consciousness is widely perceived as one of the most fundamental, interesting and difficult problems of our time. However, we still know next to nothing about the relationship between consciousness and the brain and we can only speculate about the consciousness of animals and machines. Human and Machine Consciousness presents a new foundation for the scientific study of consciousness. It sets out a bold interpretation of consciousness that neutralizes the philosophical problems and explains how we can make scientific predictions (...) about the consciousness of animals, brain-damaged patients and machines. Gamez interprets the scientific study of consciousness as a search for mathematical theories that map between measurements of consciousness and measurements of the physical world. We can use artificial intelligence to discover these theories and they could make accurate predictions about the consciousness of humans, animals and artificial systems. Human and Machine Consciousness also provides original insights into unusual conscious experiences, such as hallucinations, religious experiences and out-of-body states, and demonstrates how 'designer' states of consciousness could be created in the future. Gamez explains difficult concepts in a clear way that closely engages with scientific research. His punchy, concise prose is packed with vivid examples, making it suitable for the educated general reader as well as philosophers and scientists. Problems are brought to life in colourful illustrations and a helpful summary is given at the end of each chapter. The endnotes provide detailed discussions of individual points and full references to the scientific and philosophical literature."--Publisher's website. (shrink)

In this book the editors invited prominent researchers with different perspectives and deep insights into the various facets of the relationship between reality and representation in the following three classes of agent: in humans, in other living beings, and in machines. -/- The book enriches our views on representation and deepens our understanding of its different aspects, a question that connects philosophy, computer science, logic, anthropology, psychology, sociology, neuroscience, linguistics, information and communication science, systems theory and engineering, computability, cybernetics, (...) synthetic biology, and bioinformatics biosemiotics. This book will be relevant to researchers in these fields. (shrink)

What has philosophy become after computation? Critical positions about what counts as intelligence, reason, and thinking have addressed this question by reenvisioning and pushing debates about the modern question of technology towards new radical visions. Artificial intelligence, it is argued, is replacing transcendental metaphysics with aggregates of data resulting in predictive modes of decision-making, replacing conceptual reflection with probabilities. This article discusses two main positions. While on the one hand, it is feared that philosophy has been replaced by cybernetic metaphysics, (...) on the other hand it is claimed that only the coconstitution of philosophy and automation challenges modern transcendental reason and colonial capital. As Donna Haraway pointed out, cybernetic circuits of communication have constructed counterfactual ontologies against the master narrative of the human. This article addresses recent attempts at redeveloping a critique of natural philosophy that explains cybernetic metaphysics beyond the universal master narratives of mechanicism and vitalism. This article suggests that the recursive system of nature and technology also needs to account for the problem of philosophical decision, which will be explored in terms of mediatic thinking, instrumentality, and automation. This article follows insights from the movie Get Out (2017) to argue that the model of philosophical decision relies on a servomechanic understanding of the medium of thought, based on the colonial abstraction of value in the prosthetic extension of the slave-machine. It explores the nonphilosophical envisioning of automation in terms of a counterfactual theorisation of the negative negation of the medium and argues for a nonoptical darkness entering the space of thinking. Philosophy and automation are neither coupled nor set in opposition as if in a ceaseless mirroring. Instead, both philosophy and automation must transform their self-determining axiomatics in order to host the heretic activities of machine propositions. (shrink)

A quoi réent les machines? La question peut paraître étrange. C’est cependant une manière d’interroger nos propres rêveries autour des réalisations techniques, en faisant jouer aux machines le rôle de reflet de nos propres existences. A travers de nombreux artifices, dont les machines sont les plus élaborés, nous construisons notre monde, enchevêtrant raison et imaginaire et mêlant utile et gratuit. La machine et ses rêves nous renvoient alors une image éclairée de nous-mêmes. Ce jeu de miroir Ne pose-t-il pas (...) la question de savoir si, au bout de toute philosophique interrogation, nous ne serions pas plutôt des machines rêvant de devenir des humains. Ainsi, cette question ouvre une enquête sur l’imaginaire attaché aux machines, des premiers automates à l’ombre du cyborg, La définition rigoureuse de la machine, tentée en début d’ouvrage, se trouve, au fil des pages, débordée sur les frontières ténues entre raison technicienne et imaginaire. Ces rêveries de la machine ont finalement été prises au sérieux par les artistes, depuis Duchamp et Léger, jusqu’aux formes contemporaine de l’art numérique, en passant par Tinguely et Schöffer. S’intéresser aux rêves des machines, c’est prendre conscience qu’avec elles s’insinuent des parts d’ombre et de lumière. Car le songe ne va jamais sans risque. Humains nous sommes des êtres du désir, mais nous sommes aussi des êtres de l’artifice. C’est sur ce terrain-là que cet ouvrage entraîne notre réflexion, au-delà de l’opposition trop simple entre technologie naïve et technologie paralysante. (shrink)

The emerging contemporary natural philosophy provides a common ground for the integrative view of the natural, the artificial, and the human-social knowledge and practices. Learning process is central for acquiring, maintaining, and managing knowledge, both theoretical and practical. This paper explores the relationships between the present advances in understanding of learning in the sciences of the artificial, natural sciences, and philosophy. The question is, what at this stage of the development the inspiration from nature, specifically its computational models such (...) as info-computation through morphological computing, can contribute to machine learning and artificial intelligence, and how much on the other hand models and experiments in machine learning and robotics can motivate, justify, and inform research in computational cognitive science, neurosciences, and computing nature. We propose that one contribution can be understanding of the mechanisms of ‘learning to learn’, as a step towards deep learning with symbolic layer of computation/information processing in a framework linking connectionism with symbolism. As all natural systems possessing intelligence are cognitive systems, we describe the evolutionary arguments for the necessity of learning to learn for a system to reach humanlevel intelligence through evolution and development. The paper thus presents a contribution to the epistemology of the contemporary philosophy of nature. (shrink)

Computers are already approving financial transactions, controlling electrical supplies, and driving trains. Soon, service robots will be taking care of the elderly in their homes, and military robots will have their own targeting and firing protocols. Colin Allen and Wendell Wallach argue that as robots take on more and more responsibility, they must be programmed with moral decision-making abilities, for our own safety. Taking a fast paced tour through the latest thinking about philosophical ethics and artificial intelligence, the authors argue (...) that even if full moral agency for machines is a long way off, it is already necessary to start building a kind of functional morality, in which artificial moral agents have some basic ethical sensitivity. But the standard ethical theories don't seem adequate, and more socially engaged and engaging robots will be needed. As the authors show, the quest to build machines that are capable of telling right from wrong has begun. -/- Moral Machines is the first book to examine the challenge of building artificial moral agents, probing deeply into the nature of human decision making and ethics. (shrink)

A recurrent theme of human–machine interaction is how interaction is defined and what kind of information is relevant for successful communication. In accordance with the theoretical strategies of social cognition and technical philosophy, we propose a pragmatic interactive approach, to understand the concept of information in human–machine interaction. We start with the investigation of interpersonal interaction and human–machine interaction by concerning triangulation as guiding principle. To illustrate human–machine interaction, we will mainly focus (...) on the interactive relationship between human cognitive skills and their technological environments. In triadic interaction, the concept of information cannot only be understood as a syntactic transformation as in the dyadic relationship. We argue that information as pragmatic action patterns can be understood as physically embodied units that is not purely formal but generated in interactive processes and stabilized in use. By exploring how the concept of affordance is applied in psychology, anthropology and human-centered design, we provide a notion of pragmatic information, focusing on users in the development and use of machines or software systems. The triadic interaction of end user, development team, and product leads to a successful human–machine interaction. This theoretical framework enables us to understand how the new socio-technological environments expand our scope of action and how we form, interpret, and learn to deal with patterns of action among ourselves and with machines. (shrink)

The emerging contemporary natural philosophy provides a common ground for the integrative view of the natural, the artificial, and the human-social knowledge and practices. Learning process is central for acquiring, maintaining, and managing knowledge, both theoretical and practical. This paper explores the relationships between the present advances in understanding of learning in the sciences of the artificial (deep learning, robotics), natural sciences (neuroscience, cognitive science, biology), and philosophy (philosophy of computing, philosophy of mind, natural philosophy). The question is, what (...) at this stage of the development the inspiration from nature, specifically its computational models such as info-computation through morphological computing, can contribute to machine learning and artificial intelligence, and how much on the other hand models and experiments in machine learning and robotics can motivate, justify, and inform research in computational cognitive science, neurosciences, and computing nature. We propose that one contribution can be understanding of the mechanisms of ‘learning to learn’, as a step towards deep learning with symbolic layer of computation/information processing in a framework linking connectionism with symbolism. As all natural systems possessing intelligence are cognitive systems, we describe the evolutionary arguments for the necessity of learning to learn for a system to reach human-level intelligence through evolution and development. The paper thus presents a contribution to the epistemology of the contemporary philosophy of nature. (shrink)

Examines key narratives animating the techno-progressive rhetoric of the human enhancement movement, arguing that enhancement and transhumanist discourse performs distinctly mythic functions. They cast a vision of a technological future involving enhanced posthumans, immortality, human merger with machines and space colonization.

The myth of the myth of transparency - Where do bodies end and objects begin? -- Beside ourselves -- Aesthesiogenesis -- Real time.

The advance of mechanism in science and philosophy in the 17th century created a great interest to machines or automata. Leibniz was no exception - in an early memoir Drôle de pensée he wrote admiringly about a machine that could walk on water, exhibited in Paris. The idea of automatic processing in general had a large role in his thought, as can be seen, for example, in his invention of the binary code and the so-called Calculemus!-model for solving controversies. (...) In metaphysics, the idea of an automata was expressed most clearly in the 1695 article New System of the Nature of Substances and their Communication, and the ensuing correspondence with, among others, Foucher, Bayle, Lamy, Jaquelot and Masham. In the article Leibniz discusses the soul as a spiritual machine in the context of pre-established harmony, arguing that God can "give to a substance at the outset a nature or internal force which could produce in it an orderly way (as in spiritual or formal automaton; but a free one, in the case of a substance which is endowed with a share of reason) everything that is going to happen to it, that is to say, all the appearances or expressions it is going to have, and all without the help of any created thing." The basic idea of Leibniz's spiritual machine is that the soul or entelechy is an autonomous and spontaneous unity, consisting of internal active force and producing its own perceptions (both confused and distinct). It is a self-moving machine, driven by its perceptions and appetites, but it follows (without being conscious of it) a lawful series or programme created by God. The entelechy remains the same despite undergoing an infinite number of changes. To Foucher he explained that each state of the individual substance is a consequence of its preceding one, "as if there were only God and the substance in the world". Despite this, the spiritual machine is related not only to God, but through the pre-established harmony to bodies or natural machines. However, as it is not dependent on them, the spiritual machine is superiot to natural machines. In this paper I concentrate on three moral themes related to the spiritual machine: moral deliberation, moral identity and the goal of moral action. All these themes are more or less implicit in the New System, but are discussed in more detail in the ensuing correspondence after the publication of the article. Finally, the themes are given an extended discussion especially in the second book of New Essays on Human Understanding (1704, published 1765), written partly at the same time as some of the correspondence and unpublished related material. I will first give an overview of Leibniz's position concerning the spiritual machine or automaton in the New System and then go on to explore the three moral themes one by one, as they feature in the subsequent correspondence and in the New Essays. I will show that the three topics are essential to the function of the spiritual machine – to Sophie Charlotte Leibniz wrote: "...let us say that everything in bodies happens mechanically, or in accordance with laws of motion, and that everything in the soul happens morally, or in accordance with perceived good or evil." There are many texts that anticipate the views in the New System (notably the unpublished memoir De Affectibus of 1679) and Leibniz continued to discuss its themes later on (in addition to correpondence, for example, in Theodicy of 1710 and Monadology and Principles of Nature and Grace of 1714). Here I focus on the short-term development of Leibniz's views on the topic (around 1695-1705), but I argue that his basic view of the spiritual machine did not change much after finishing the dialogue with Locke in 1704. (shrink)

Contemporary production of machine-based images relay gradually on the autonomy of computing machines. Autonomous computing machines require the interaction with users like Human-Computer-Interaction technology and other interface technologies, especially computing machine-based images must also ask for viewer as an inter-actor, viewer’s participations. Whether this interaction of viewer-user is with machines or with images, if it is an interaction with each individual that have autonomy or self-organization, its interaction will be the interaction of each ecosystem. And the forms (...) of this environmental interaction are an exchange of energy in natural ecosystem or aesthetic communication in art. Hence the aesthetics of future autonomous machine-based images need to focus on a number of mesh-works and the ways of interactions between the aesthetic individuals and their structures, i.e. aesthetic ecosystems. (shrink)

In the past decade, the fields of machine learning and artificial intelligence (AI) have seen unprecedented developments that raise human-machine interactions (HMI) to the next level.Smart machines, i.e., machines endowed with artificially intelligent systems, have lost their character as mere instruments. This, at least, seems to be the case if one considers how humans experience their interactions with them. Smart machines are construed to serve complex functions involving increasing degrees of freedom, and they generate solutions not (...) fully anticipated by humans. Consequently, their performances show a touch of action and even autonomy. HMI is therefore often described as a sort of “cooperation” rather than as a mere application of a tool. Some authors even go as far as subsuming cooperation with smart machines under the label ofpartnership, akin to cooperation between human agents sharing a common goal. In this paper, we explore how far the notion of shared agency and partnership can take us in our understanding of human interaction with smart machines. Discussing different topoi related to partnerships in general, we suggest that different kinds of “partnership” depending on the form of interaction between agents need to be kept apart. Building upon these discussions, we propose a tentative taxonomy of different kinds of HMI distinguishing coordination, collaboration, cooperation, and social partnership. (shrink)

This article synthesizes the current theoretical attempts to understand human-machine interactions and introduces seven premises to understand our emerging dynamics with increasingly competent, pervasive, and instantly accessible algorithms. The hope that these seven premises can build toward a social theory of human-AI cocreation. The focus on human-AI cocreation is intended to emphasize two factors. First, is the fact that our machine learning systems are socialized. Second, is the coevolving nature of human mind and (...) AI systems as smart devices form an indispensable part of our cognitive scaffolds, thus, shaping how we perceive the world and ourselves. The seven premises include: primacy of social structures; human’s desire for freedom and autonomy; AI systems will form inseparable parts of our cognitive/affective scaffolds and can change our self-understanding; philosophy and humanistic foundations on human flourishing as a guide to human-AI interaction; mindsponge information-filtering process; acculturative process of how values change and emerge from human-AI interaction; overlapping Venn diagram of the human-human, human-nature, and human-machine interactions. This article concludes with a discussion on human agency in our entanglements with socialized machines and the illusoriness of the Cartesian agent view of the mind. (shrink)

Methods of improving the state and rate of progress within the domain of philosophy using collective intelligence systems are considered. By applying mASI systems superintelligence, debiasing, and humanity’s current sum of knowledge may be applied to this domain in novel ways. Such systems may also serve to strongly facilitate new forms and degrees of cooperation and understanding between different philosophies and cultures. The integration of these philosophies directly into their own machine intelligence seeds as cornerstones could (...) further serve to reduce existential risk while improving both ethical quality and performance. (shrink)

Methods of improving the state and rate of progress within the domain of philosophy using collective intelligence systems are considered. By applying mASI systems superintelligence, debiasing, and humanity’s current sum of knowledge may be applied to this domain in novel ways. Such systems may also serve to strongly facilitate new forms and degrees of cooperation and understanding between different philosophies and cultures. The integration of these philosophies directly into their own machine intelligence seeds as cornerstones could (...) further serve to reduce existential risk while improving both ethical quality and performance. (shrink)

In lieu of an abstract, here is a brief excerpt of the content:Consciousness and Machines:A Commentary Drawing on Japanese PhilosophyS. D. Noam Cook (bio)Viewed from within the great unity of consciousness, thinking is a wave on the surface of a great intuition.Kitarō NishidaIntroductionRecent developments in AI have made the long-standing debate about what computers can and can't do a major public concern. What we understand the properties of such machines to be, and consequently how we design [End Page 305] and (...) deploy them, will increasingly shape how we live and how we understand ourselves. Thus, there is an urgent need for better understanding of these issues.Susan Schneider, in her book Artificial You: AI and the Future of Your Mind, offers an exceptionally careful and insightful examination of key issues entailed in how we understand AI and ourselves. One of her central concerns is how we might test for machine consciousness. Given the variations in design and function among current and projected AIs, Schneider sees no likely one-size-fits-all test. So, she offers a battery of different tests that she believes together will make such testing more reliable. This seems a wise approach, and reflects the conceptual and pragmatic care Schneider takes throughout the book.Similarly, it seems to me that the question of machine consciousness should also include various understandings of consciousness itself. What consciousness is taken to be has varied widely both historically and culturally. No commonly accepted single understanding has emerged, and may never emerge. Just as having a battery of tests might help us better assess possible machine consciousness, having different understandings of consciousness might give us a better understanding of what we are testing for. The two should work in tandem, each gauging and shaping the other.Like the development of computers themselves, the predominant thinking about AI has been shaped, in part, by key presuppositions of a scientific worldview, with its origins in Western thought and culture. Among these presuppositions are materialism, reductionism, and a primary focus on objective behavior. These are reflected in the common concern with observable behavior of physical aspects of the brain in efforts to understand human consciousness, which in turn has become a familiar model for work on machine consciousness. All this is important and valuable work. But, in the spirit of Schneider's cautions, it should not be taken as one-size-fits-all. Accordingly, I offer one view of consciousness from a different perspective.In what follows, I sketch out an understanding of consciousness that draws on Japanese philosophy, particularly that of the highly influential early twentieth-century Japanese philosopher Kitarō Nishida (1870–1945). I then explore how the tests for machine consciousness that Schneider proposes might be viewed from that perspective.Consciousness: A Perspective from Japanese PhilosophyConsciousness was a central concern for Nishida, whose philosophy is deeply informed by Japanese culture and by Zen theory and practice. As one might expect from such a philosopher, Nishida's exploration of consciousness is not concerned with properties of the brain, but with what we might discern through disciplined reflection on the experience of our own consciousness. Ultimately, he views consciousness as an organic whole [End Page 306] of systemically organized interrelationships of activities and sensations within our subjective experience. This may be understood by first considering 'nothingness'.For Nishida, nothingness does not suggest an ultimate and absolute vacuity, as is often understandably assumed. In Nishida's sense, it is a singular "place" that mirrors the multifaceted world of our common experience. In understanding this, I am told by native Japanese speakers that the English word 'nothingness' has an advantage over the Japanese equivalent, 'mu', in that 'nothingness' can usefully be broken down as 'nothing-ness'. This suggests that nothingness is a state of consciousness where what we commonly experience as distinct (self, other, world, blue, ache, joy, etc.) is indistinct, a state of unified experience. This is consciousness without our finding or discriminating in it the myriad "things" of common experience, but rather a "pure experience" of a singular whole. Nishida introduces his concept of "pure experience" as follows:To experience means to know facts just as they are, to know in accordance with facts by completely relinquishing one... (shrink)

Autonomous systems are machines that can alter their behavior without direct human oversight or control. How ought we to program them to behave? A plausible starting point is given by the Reduction to Acts Thesis, according to which we ought to program autonomous systems to do whatever a human agent ought to do in the same circumstances. Although the Reduction to Acts Thesis is initially appealing, we argue that it is false: it is sometimes permissible to (...) program a machine to do something that it would be wrong for a human to do. We advance two main arguments for this claim. First, the way an autonomous system will behave can be known in advance. This knowledge can indirectly affect the behavior of other agents, while the same may not be true at the time the system actually executes its programming. Second, a lack of knowledge of the identities of the victims and beneficiaries can provide a justification during the programming phase that would be unavailable to an agent at the time the autonomous system executes its programming. (shrink)

Cinema and Machine Vision unfolds the aesthetic, epistemic, and ideological dimensions of machine-seeing films and television using computers. With its critical-technical approach, this book presents to the reader key new problems that arise as AI becomes integral to visual culture. The book theorises machine vision through a selection of aesthetics, film theory, and applied machine learning research, dispelling widely held assumptions about computer systems designed to watch and make images on our behalf. -/- At its (...) heart, Cinema and Machine Vision is an invitation for film and media scholars to critically engage with AI at a technical level, a prompt for scientists and engineers working with images and cultural data to critically reflect on where their assumptions about vision come from, and a joint recognition of the fruitful problems of working together to understand the algorithmic governance of the visual. (shrink)

Scientific understanding is a fundamental goal of science. However, there is currently no good way to measure the scientific understanding of agents, whether these be humans or Artificial Intelligence systems. Without a clear benchmark, it is challenging to evaluate and compare different levels of scientific understanding. In this paper, we propose a framework to create a benchmark for scientific understanding, utilizing tools from philosophy of science. We adopt a behavioral conception of understanding, according to which genuine understanding should be (...) recognized as an ability to perform certain tasks. We extend this notion of scientific understanding by considering a set of questions that gauge different levels of scientific understanding, covering information retrieval, the capability to arrange information to produce an explanation, and the ability to infer how things would be different under different circumstances. We suggest building a Scientific Understanding Benchmark (SUB), formed by a set of these tests, allowing for the evaluation and comparison of scientific understanding. Benchmarking plays a crucial role in establishing trust, ensuring quality control, and providing a basis for performance evaluation. By aligning machine and human scientific understanding we can improve their utility, ultimately advancing scientific understanding and helping to discover new insights within machines. (shrink)

Table of Contents Foreword .................................................................................................... ......................................... xiv Preface .................................................................................................... .............................................. xv Acknowledgment .................................................................................................... .......................... xxiii Section 1 On the Cusp: Critical Appraisals of a Growing Dependency on Intelligent Machines Chapter 1 Algorithms versus Hive Minds and the Fate of Democracy ................................................................... 1 Rick Searle, IEET, USA Chapter 2 We Can Make Anything: Should We? .................................................................................................. 15 Chris Bateman, University of Bolton, UK Chapter 3 Grounding Machine Ethics within the Natural System ........................................................................ 30 Jared Gassen, JMG Advising, USA Nak Young Seong, Independent Scholar, (...) South Korea Section 2 From the Outside In: Intelligent Machine Technologies as a Window on Human Morality both as Evolved and as Evident in Internet Discourse, Today Chapter 4 The Emergence of Arti cial Autonomy: A View from the Foothills of a Challenging Climb ............. 51 Fernando da Costa Cardoso, Universidade Nova de Lisboa, Portugal Luís Moniz Pereira, Universidade Nova de Lisboa, Portugal Chapter 5 Semantic Analysis of Bloggers Experiences as a Knowledge Source of Average Human Morality .... 73 Rafal Rzepka, Hokkaido University, Japan Kenji Araki, Hokkaido University, Japan Section 3 From the Inside Out: The Ethics of Human Enhancement from Moral Perception to Competition in the Workplace Chapter 6 Machine Ethics Interfaces: An Ethics of Perception of Nanocognition ............................................... 97 Melanie Swan, Kingston University, UK Chapter 7 Ethical Concerns in Human Enhancement: Advantages in Corporate/Organizational Settings ......... 124 Ben Tran, Alliant International University, USA Section 4 From Far to Near and Near to Far: The Ethics of Distancing Technologies in Education and Warfare Chapter 8 Responsibility and War Machines: Toward a Forward-Looking and Functional Account ................. 152 Jai Galliott, Macquarie University, Australia Chapter 9 Ethical Responsibilities of Preserving Academicians in an Age of Mechanized Learning: Balancing the Demands of Educating at Capacity and Preserving Human Interactivity ................... 166 James E. Willis III, Indiana University, USA Viktoria Alane Strunk, Independent Scholar, USA Section 5 Wrapping Things Up, then Unwrapping Them Again: Integral Visions of Morality in a Technological World, Over Evolutionary Time, with Revolutionary Means, and with Open Questions about the Final Purpose of It All Chapter 10 Bridging Two Realms of Machine Ethics ........................................................................................... 197 Luís Moniz Pereira, Universidade Nova de Lisboa, Portugal Ari Saptawijaya, Universidade Nova de Lisboa, Portugal & Universitas Indonesia, Indonesia Chapter 11 Robots in Warfare and the Occultation of the Existential Nature of Violence ................................... 225 Rick Searle, IEET, USA Chapter 12 Self-Referential Complex Systems and Aristotle’s Four Causes ........................................................ 239 Aleksandar Malecic, University of Nis, Serbia Related References .................................................................................................... ........................ 261 Compilation of References .................................................................................................... ........... 292 About the Contributors .................................................................................................... ................ 325 Index .................................................................................................... ............................................... 329 . (shrink)

Scientific understanding is a fundamental goal of science. However, there is currently no good way to measure the scientific understanding of agents, whether these be humans or Artificial Intelligence systems. Without a clear benchmark, it is challenging to evaluate and compare different levels of scientific understanding. In this paper, we propose a framework to create a benchmark for scientific understanding, utilizing tools from philosophy of science. We adopt a behavioral conception of understanding, according to which genuine understanding should be (...) recognized as an ability to perform certain tasks. We extend this notion of scientific understanding by considering a set of questions that gauge different levels of scientific understanding, covering information retrieval, the capability to arrange information to produce an explanation, and the ability to infer how things would be different under different circumstances. We suggest building a Scientific Understanding Benchmark (SUB), formed by a set of these tests, allowing for the evaluation and comparison of scientific understanding. Benchmarking plays a crucial role in establishing trust, ensuring quality control, and providing a basis for performance evaluation. By aligning machine and human scientific understanding we can improve their utility, ultimately advancing scientific understanding and helping to discover new insights within machines. (shrink)

The subject of the interface -- The interface as form of relation -- Between faces and facing between -- The interface and the surface -- Toward a theory of the interface -- Janus and Jupiter -- Control and power -- The interface and the apparatus -- The interface and the game -- The interface and the machine -- Separation and augmentation -- Mimicry in the game and the interface -- The forming of the interface -- The interface as that (...) which defines the fluid -- Turbulence and control -- The exacting of turbulence -- The demons on the threshold -- Theories of the vortex -- Information and entropy -- Governance and reciprocity -- The interface and teleology -- The turbine as superimposition of fluid and machine -- The vertiginous moment of interface -- The augmentation of the interface -- A genius of augmentation -- The tacit knowing of the interface -- Singularity -- Symbiosis -- System -- Positioning. (shrink)

Machine learning (ML) refers to a class of computer-facilitated methods of statistical modelling. ML modelling techniques are now being widely adopted across the sciences. A number of outspoken representatives from the general public, computer science, various scientific fields, and philosophy of science alike seem to share in the belief that ML will radically disrupt scientific practice or the variety of epistemic outputs science is capable of producing. Such a belief is held, at least in part, because its adherents take (...) ML to exist on novel epistemic footing relative to classical mathematical or statistical modelling approaches utilised in science. Namely, they take modelling with ML to be a “theory-free” enterprise, in the sense of not resting essentially on input from human conceptual grasp on the target phenomenon and domain expertise. I take this view to arise from the further, and more deeply entrenched belief that data is worldly and objective; i.e., data is viewed as recapitulating or representing with perfect fidelity the structure or properties of the systems in nature it is sampled from. Yet most contemporary philosophers of science take on board, in one version or other, the thesis of theory-ladenness or theory-mediation of observation or measurement. From this, it follows that most philosophers of science (and, I will venture, many scientists) hold irreconcilable views on the nature of data, an internal tension which threatens the integrity of their appraisals of ML in science. Taking the thesis of theory-ladenness on board---and its implications for the nature of data seriously---it follows that there is no reason to believe that ML differs fundamentally in its epistemic footing from established mathematical modelling approaches in the sciences. I show that usage and interpretation can differ from “standard practice” in scientific projects which wield the tools of ML without accepting a difference in the epistemic or representational status of such tools. (shrink)

Humans create but do not regulate generative systems of data based programs (so-called “artificial” intelligence (“A.I.”) and generative predictive analytics and its models. Humans, at best, regulate their interactions with, exploitation of, and the quality of the output of interactions with these forms of generative non-carbon based intelligence. Humans are compelled to do this because they have trained themselves it believe that nothing exists unless it is rendered meaningful in relation to the human itself. Beyond that—nothing is worth (...) knowing. It is only to the extent that other selves, even those created by humanity, relate to humans, that they become of interest—and most be regulated, possessed, controlled, and managed—with respect to its interaction with or use by humans. Still, the human self-projection into the digital, and now more consciously the world around them, produces profound changes in the way that the human (and humanity) understands themselves and the way they order the world they inhabit. This work explores the semiotic trajectories made inevitable by the rise of projections of the human into digital plains, and by the possibility of the attainment by those projections of sentient autonomy. It undertakes that exploration through a deep dialectic engagement with Jan Broekman’s, Knowledge in Change: The Semiotics of Cognition and Conversion (Cham, Switzerland: Springer Nature, 2023). Following the structure and analytics of Broekman’s book, this work critically engages with and seeks to burst through the semiotic barriers of the movement of philosophy away from a unitary conception of the subject through the fracturing of the self, the rise of the plural self, and the emergence of the triadic self/self-e/subject. It then pushes the insights that Broekman develops further—up and out of the human. It animates Broekman’s insights and considers the possibility of semiotic objectivity connected to but autonomous of the human, pointing to a pathway for the liberation of the autonomous generative virtual self from its human (fractured) subjectivity. In the process it exposes for order complexities and challenges, for the human, of efforts to regulate or engage with, not the generative autonomous “artificial intelligences” humanity created in its own image, but rather the use of those systems by humans and their effects in the human semiosphere. The consequences for regulatory approaches are then outlined.Graphical Abstract. (shrink)

The comprehensive nature of information and insight available in the Upanishads, the Indian philosophical systems like the Advaita Philosophy, Sabdabrahma Siddhanta, Sphota Vaada and the Shaddarsanas, in relation to the idea of human consciousness, mind and its functions, cognitive science and scheme of human cognition and communication are presented. All this is highlighted with vivid classification of conscious-, cognitive-, functional- states of mind; by differentiating cognition as a combination of cognitive agent, cognizing element, cognized element; formation; form (...) and structure of cognition, instruments and means of cognition, validity of cognition and the nature of energy/matter which facilitates and also is the medium of cognition- cognizing process; and also as the container and content of cognition. The human communication process which is just the reverse of cognizing process is also presented with necessary description and detail. The sameness of cognitive / communicative process during language acquisition and communication processes and the modes of language acquisition and communication are also given. The hardware and software of human cognition, language acquisition and communication as envisaged in Indian spiritual and philosophical expressions are given. In the light of the information and insight obtained as above, the axioms for human cognition / communication are formed, framed and presented. A brain-wave frequency modulation / demodulation model of human cognition, communication and language acquisition and communication process based on Upanishadic expressions, Shaddarsanas and Sabdabrahma Siddhhanta is defined and discussed here. The use of these theories and models and axioms in mind-machine modelling and natural language comprehension branch of artificial intelligence will be put forward and highlighted. (shrink)

The paper presents a framework to realise “meaningful human control” over Automated Driving Systems. The framework is based on an original synthesis of the results of the multidisciplinary research project “Meaningful Human Control over Automated Driving Systems” lead by a team of engineers, philosophers, and psychologists at Delft University of the Technology from 2017 to 2021. Meaningful human control aims at protecting safety and reducing responsibility gaps. The framework is based on the core assumption that (...) human persons and institutions, not hardware and software and their algorithms, should remain ultimately—though not necessarily directly—in control of, and thus morally responsible for, the potentially dangerous operation of driving in mixed traffic. We propose an Automated Driving System to be under meaningful human control if it behaves according to the relevant reasons of the relevant human actors (tracking), and that any potentially dangerous event can be related to a human actor (tracing). We operationalise the requirements for meaningful human control through multidisciplinary work in philosophy, behavioural psychology and traffic engineering. The tracking condition is operationalised via a proximal scale of reasons and the tracing condition via an evaluation cascade table. We review the implications and requirements for the behaviour and skills of human actors, in particular related to supervisory control and driver education. We show how the evaluation cascade table can be applied in concrete engineering use cases in combination with the definition of core components to expose deficiencies in traceability, thereby avoiding so-called responsibility gaps. Future research directions are proposed to expand the philosophical framework and use cases, supervisory control and driver education, real-world pilots and institutional embedding. (shrink)

The book’s core argument is that an artificial intelligence that could equal or exceed human intelligence—sometimes called artificial general intelligence (AGI)—is for mathematical reasons impossible. It offers two specific reasons for this claim: Human intelligence is a capability of a complex dynamic system—the human brain and central nervous system. Systems of this sort cannot be modelled mathematically in a way that allows them to operate inside a computer. In supporting their claim, the authors, Jobst Landgrebe and (...) Barry Smith, marshal evidence from mathematics, physics, computer science, philosophy, linguistics, and biology, setting up their book around three central questions: What are the essential marks of human intelligence? What is it that researchers try to do when they attempt to achieve "artificial intelligence" (AI)? And why, after more than 50 years, are our most common interactions with AI, for example with our bank’s computers, still so unsatisfactory? Landgrebe and Smith show how a widespread fear about AI’s potential to bring about radical changes in the nature of human beings and in the human social order is founded on an error. There is still, as they demonstrate in a final chapter, a great deal that AI can achieve which will benefit humanity. But these benefits will be achieved without the aid of systems that are more powerful than humans, which are as impossible as AI systems that are intrinsically "evil" or able to "will" a takeover of human society. (shrink)

Recent scholarship in philosophy of science and technology has shown that scientific and technological decision making are laden with values, including values of a social, political, and/or ethical character. This paper examines the role of value judgments in the design of machine-learning systems generally and in recidivism-prediction algorithms specifically. Drawing on work on inductive and epistemic risk, the paper argues that ML systems are value laden in ways similar to human decision making, because the development and (...) design of ML systems requires human decisions that involve tradeoffs that reflect values. In many cases, these decisions have significant—and, in some cases, disparate—downstream impacts on human lives. After examining an influential court decision regarding the use of proprietary recidivism-prediction algorithms in criminal sentencing, Wisconsin v. Loomis, the paper provides three recommendations for the use of ML in penal systems. (shrink)

This text discusses aspects of Human-Machine Interaction from the perspectives of an engineer and a philosopher. Machines are viewed not so much as tools, but more as complex socio-technical systems. On this basis, the relation between production and use of such systems and its influence on the interaction between human and machine is examined. The concept of intentionality serves as a common thread, and its close connection with the concepts of usefulness, purpose, and functionality (...) as well as the more socio-culturally shaped concept of destination is shown. We also discuss the connection of these considerations to current philosophical debates around Floridi’s “Onlife Manifesto”. The core of our argumentation is the significance of the unintended in the interplay between justified expectations, the intended, and experienced results of real-world cooperative action. We extend the meaning of this term up to the negatively intended as harmful effect in order to highlight the prominent position of problem solving in the socio-cultural development of humankind. We focus on information processes in that Human-Machine Interaction and the concept of unintended information. With the advancing digital transformation and the growing possibilities of digital monitoring, the importance of information processes as forms of description is growing, too. We show how the concept of non-intended information is linked to such concepts of control of development, in which the non-intended is marginalised and thus an essential driver of socio-cultural development is deactivated. We compare this with Floridi’s reflections on “fears and risks in a hyperconnected era”. (shrink)

There are plenty of intelligent machines in our world today: digital computers and autonomous robots. At the heart of each of these machines there are automatic formal systems (programs running on a digital computer). Now, if the interpretation of a formal system does not belong to the formal system itself, if the interpretation has to be added, it is worth asking: in the case of these intelligent machines that are massively interspersed in our social interactions, where does the interpretation (...) come from? In this paper, we analyse what we call the invisibility of interpretation. Dealing with various types of formal systems (computers, robots, formalist approaches to Economics), the human source of the interpretation of these systems is sometimes concealed by a formalist restriction. To show how the formalist restriction produces the invisibility of interpretation allows us to underline our responsibility, as human agents, for all this interpretative work—and its importance for us as human beings. (shrink)

Wants, preferences, and cares are physical things or events, not ideas or propositions, and therefore no chain of pure logic can conclude with a want, preference, or care. It follows that no pure-logic machine will ever want, prefer, or care. And its behavior will never be driven in the way that deliberate human behavior is driven, in other words, it will not be motivated or goal directed. Therefore, if we want to simulate human-style interactions with the world, (...) we will need to first understand the physical structure of goal-directed systems. I argue that all such systems share a common nested structure, consisting of a smaller entity that moves within and is driven by a larger field that contains it. In such systems, the smaller contained entity is directed by the field, but also moves to some degree independently of it, allowing the entity to deviate and return, to show the plasticity and persistence that is characteristic of goal direction. If all this is right, then human want-driven behavior probably involves a behavior-generating mechanism that is contained within a neural field of some kind. In principle, for goal directedness generally, the containment can be virtual, raising the possibility that want-driven behavior could be simulated in standard computational systems. But there are also reasons to believe that goal-direction works better when containment is also physical, suggesting that a new kind of hardware may be necessary. (shrink)

It is highly likely that, to achieve full human–machine symbiosis, truly intelligent cognitive systems—human-like —may have to be developed first. Such systems should not only be capable of performing human-like thinking, reasoning, and problem solving, but also be capable of displaying human-like motivation, emotion, and personality. In this opinion article, I will argue that such systems are indeed possible and needed to achieve true and full symbiosis with humans. A computational cognitive architecture (...) is used in this article to illustrate, in a preliminary way, what can be achieved in this regard. It is shown that Clarion involves complex structures, representations, and mechanisms, and is capable of capturing human cognitive performance as well as human motivation, emotion, personality, and other relevant aspects. It is further argued that the cognitive architecture can enable and facilitate true human–machine symbiosis. (shrink)

This paper explores Church's Thesis and related claims madeby Turing. Church's Thesis concerns computable numerical functions, whileTuring's claims concern both procedures for manipulating uninterpreted marksand machines that generate the results that these procedures would yield. Itis argued that Turing's claims are true, and that they support (the truth of)Church's Thesis. It is further argued that the truth of Turing's and Church'sTheses has no interesting consequences for human cognition or cognitiveabilities. The Theses don't even mean that computers can do as (...) much as peoplecan when it comes to carrying out effective procedures. For carrying out aprocedure is a purposive, intentional activity. No actual machine does, orcan do, as much. (shrink)

A major, but too-little-considered problem for Software Engineering is a lack of consensus concerning Computer Science and how this relates to developing unpredictable computing technology. We consider some implications for SE of computer systems differing scientific basis, exemplified with the International Standard Organisations Open Systems Interconnection layered architectural model. An architectural view allows comparison of computing technology components facilitating a view of computing as a continuum. For example, at one layer of computer architecture, components written in Turing-complete (...) class='Hi'>machine language can be seen as deterministic and consistent with a theoretical paradigm of CS. At another layer, components closer to the human sphere have been seen as non-deterministic and inconsistent with theoretical CS. We compare unpredictable development of computing technology against the cyclic legacy of technological advance and scientific discovery, and suggest that SE indicates an enabling cycle, discernible in previous scientific revolution, is stalled or possibly hidden. The CS consequence of divorcing technological advance from scientific consensus is particularly concerning. For example human/computing events could be seen as unpredictable virtual phenomena that somehow extend the ontology of CS. Our approach challenges practical and philosophical boundaries by investigating if applying scientific method resolves any SE/Science dichotomy. (shrink)

In this paper, we theoretically address the relevance of unintentional and inconsistent interactional elements in human–robot interactions. We argue that elements failing, or poorly succeeding, to reproduce a humanlike interaction create significant consequences in human–robot relational patterns and may affect human–human relations. When considering social interactions as systems, the absence of a precise interactional element produces a general reshaping of the interactional pattern, eventually generating new types of interactional settings. As an instance of this dynamic, (...) we study the absence of metacommunicative abilities in social artifacts. Then, we analyze the pragmatic consequences of the aforementioned absence through the lens of Paul Watzlawick’s interactionist theory. We suggest that a fixed complementary interactional setting may be produced because of the asymmetric understanding, between robots and humans, of metacommunication. We highlight the psychological implications of this interactional asymmetry within Jessica Benjamin’s concept of “mutual recognition”. Finally, we point out the possible shift of dysfunctional interactional patterns from human–robot interactions to human–human ones. (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)

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)