The first part of this paper explores the general issues in using Artificial Life techniques to program actual mobile robots. In particular it explores the difficulties inherent in transferring programs evolved in a simulated environment to run on an actual robot. It examines the dual evolution of organism morphology and nervous systems in biology. It proposes techniques to capture some of the search space pruning that dual evolution offers in the domain of robot programming. It explores the (...) relationship between robot morphology and program structure, and techniques for capturing regularities across this mapping. (shrink)

What is artificial life? Much has been said about this interesting collection of efforts to artificially simulate and synthesize lifelike behavior and processes, yet we are far from having a robust philosophical understanding of just what Alifers are doing and why it ought to interest philosophers of science, and philosophers of biology in particular. In this paper, I first provide three introductory examples from the particular subset of artificial life I focus on, known as ‘soft Alife’ (...) (s-Alife), and follow up with a more in-depth review of the Avida program, which serves as my case study of s-Alife. Next, I review three well-known accounts of thought experiments, and then offer my own synthesized account, to make the argument that s-Alife functions as thought experimentation in biology. I draw a comparison between the methodology of the thought-experimental world that yields real-world results, and the s-Alife research that informs our understanding of natural life. I conclude that the insights provided by s-Alife research have the potential to fundamentally alter our understanding of the nature of organic life and thus deserve the attention of both philosophers and natural scientists. (shrink)

What is life? Is it just the biologically familiar--birds, trees, snails, people--or is it an infinitely complex set of patterns that a computer could simulate? What role does intelligence play in separating the organic from the inorganic, the living from the inert? Does life evolve along a predestined path, or does it suddenly emerge from what appeared lifeless and programmatic? In this easily accessible and wide-ranging survey, Claus Emmeche outlines many of the challenges and controversies involved in the (...) dynamic and curious science of artificial life. Emmeche describes the work being done by an international network of biologists, computer scientists, and physicists who are using computers to study life as it could be, or as it might evolve under conditions different from those on earth. Many artificial-life researchers believe that they can create new life in the computer by simulating the processes observed in traditional, biological life-forms. The flight of a flock of birds, for example, can be reproduced faithfully and in all its complexity by a relatively simple computer program that is designed to generate electronic "boids." Are these "boids" then alive? The central problem, Emmeche notes, lies in defining the salient differences between biological life and computer simulations of its processes. And yet, if we can breathe life into a computer, what might this mean for our other assumptions about what it means to be alive? The Garden in the Machine touches on every aspect of this complex and rapidly developing discipline, including its connections to artificial intelligence, chaos theory, computational theory, and studies of emergence. Drawing on the most current work in the field, this book is a major overview of artificial life. Professionals and nonscientists alike will find it an invaluable guide to concepts and technologies that may forever change our definition of life. (shrink)

This article concerns the claim that it is possible to create living organisms, not merely models that represent organisms, simply by programming computers. I ask what sort of things these computer-generated organisms are supposed to be. I consider four possible answers to this question: The organisms are abstract complexes of pure information; they are material objects made of bits of computer hardware; they are physical processes going on inside the computer; and they are denizens of an entire artificial (...) world, different from our own, that the programmer creates. I argue that could not be right, that collapses into, and that would make strong alife either absurd or uninteresting. Thus, "virtual" strong alife amounts to the claim that, by programming a computer, one can literally bring bits of its hardware to life. (shrink)

Alan M. Turing, pioneer of computing and WWII codebreaker, is one of the most important and influential thinkers of the twentieth century. In this volume for the first time his key writings are made available to a broad, non-specialist readership. They make fascinating reading both in their own right and for their historic significance: contemporary computational theory, cognitive science, artificial intelligence, and artificial life all spring from this ground-breaking work, which is also rich in philosophical and logical (...) insight. An introduction by leading Turing expert Jack Copeland provides the background and guides the reader through the selection. About Alan Turing Alan Turing FRS OBE, (1912-1954) studied mathematics at King's College, Cambridge. He was elected a Fellow of King's in March 1935, at the age of only 22. In the same year he invented the abstract computing machines - now known simply as Turing machines - on which all subsequent stored-program digital computers are modelled. During 1936-1938 Turing continued his studies, now at Princeton University. He completed a PhD in mathematical logic, analysing the notion of 'intuition' in mathematics and introducing the idea of oracular computation, now fundamental in mathematical recursion theory. An 'oracle' is an abstract device able to solve mathematical problems too difficult for the universal Turing machine. In the summer of 1938 Turing returned to his Fellowship at King's. When WWII started in 1939 he joined the wartime headquarters of the Government Code and Cypher School (GC&CS) at Bletchley Park, Buckinghamshire. Building on earlier work by Polish cryptanalysts, Turing contributed crucially to the design of electro-mechanical machines ('bombes') used to decipher Enigma, the code by means of which the German armed forces sought to protect their radio communications. Turing's work on the version of Enigma used by the German navy was vital to the battle for supremacy in the North Atlantic. He also contributed to the attack on the cyphers known as 'Fish'. Based on binary teleprinter code, Fish was used during the latter part of the war in preference to morse-based Enigma for the encryption of high-level signals, for example messages from Hitler and other members of the German High Command. It is estimated that the work of GC&CS shortened the war in Europe by at least two years. Turing received the Order of the British Empire for the part he played. In 1945, the war over, Turing was recruited to the National Physical Laboratory (NPL) in London, his brief to design and develop an electronic computer - a concrete form of the universal Turing machine. Turing's report setting out his design for the Automatic Computing Engine (ACE) was the first relatively complete specification of an electronic stored-program general-purpose digital computer. Delays beyond Turing's control resulted in NPL's losing the race to build the world's first working electronic stored-program digital computer - an honour that went to the Royal Society Computing Machine Laboratory at Manchester University, in June 1948. Discouraged by the delays at NPL, Turing took up the Deputy Directorship of the Royal Society Computing Machine Laboratory in that year. Turing was a founding father of modern cognitive science and a leading early exponent of the hypothesis that the human brain is in large part a digital computing machine, theorising that the cortex at birth is an 'unorganised machine' which through 'training' becomes organised 'into a universal machine or something like it'. He also pioneered Artificial Intelligence. Turing spent the rest of his short career at Manchester University, being appointed to a specially created Readership in the Theory of Computing in May 1953. He was elected a Fellow of the Royal Society of London in March 1951 (a high honour). (shrink)

A major stream of Artificial Life research aims to build synthetic life forms, operating in virtual worlds, implemented as computer programs. A clear long-term target for this research is the evolution of digital life-forms with a complexity of structure and behaviour analogous to biological life-forms, potentially exhibiting intelligence and self-awareness. The creation of intelligent, self-aware digital life-forms has clear ethical implications, but there is no current research into how these ethical issues might be addressed. (...) This paper argues that such ethical research is needed. Furthermore, it describes our future research plans to build a solid philosophical foundation for the consideration of these ethical issues. (shrink)

Artificial intelligence systems have been widely applied to various contexts, including high-stake decision processes in healthcare, banking, and judicial systems. Some developed AI models fail to offer a fair output for specific minority groups, sparking comprehensive discussions about AI fairness. We argue that the development of AI systems is marked by a central paradox: the less participation one stakeholder has within the AI system’s life cycle, the more influence they have over the way the system will function. This (...) means that the impact on the fairness of the system is in the hands of those who are less impacted by it. However, most of the existing works ignore how different aspects of AI fairness are dynamically and adaptively affected by different stages of AI system development. To this end, we present a use case to discuss fairness in the development of corporate wellness programs using smart wearables and AI algorithms to analyze data. The four key stakeholders throughout this type of AI system development process are presented. These stakeholders are called service designer, algorithm designer, system deployer, and end-user. We identify three core aspects of AI fairness, namely, contextual fairness, model fairness, and device fairness. We propose a relative contribution of the four stakeholders to the three aspects of fairness. Furthermore, we propose the boundaries and interactions between the four roles, from which we make our conclusion about the possible unfairness in such an AI developing process. (shrink)

The Joint International Conference on Logic Programming, sponsored by the Association for Logic Programming, is a major forum for presentations of research, applications, and implementations in this important area of computer science. Logic programming is one of the most promising steps toward declarative programming and forms the theoretical basis of the programming language Prolog and its various extensions. Logic programming is also fundamental to work in artificial intelligence, where it has been used for (...) nonmonotonic and commonsense reasoning, expert systems implementation, deductive databases, and applications such as computer-aided manufacturing. Krzysztof R. Apt is project leader at the Centre for Mathematics and Computer Science in Amsterdam and part-time Professor in Computer Science at the University of Amsterdam. Topics covered: Theory Foundations. Programming Languages. Implementation. Programming Methodologies and Tools. Applications. Deductive Databases. Artificial Intelligence. Parallelism. (shrink)

Large sets of elements interacting locally and producing specific architectures reliably form a category that transcends the usual dividing line between biological and engineered systems. We propose to call them morphogenetically architected complex systems (MACS). While taking the emergence of properties seriously, the notion of MACS enables at the same time the design (or “meta-design”) of operational means that allow controlling and even, paradoxically, programming this emergence. To demonstrate our claim, we first show that among all the self-organized systems (...) studied in the field of Artificial Life, the specificity of MACS essentially lies in the close relation between their emergent properties and functional properties. Second, we argue that to be a MACS a system does not need to display more than weak emergent properties. Third, since the notion of weak emergence is based on the possibility of simulation, whether computational or mechanistic via machines, we see MACS as good candidates to help design artificial self-architected systems (such as robotic swarms) but also harness and redesign living ones (such as synthetic bacterial films). (shrink)

The First International Workshop brings together researchers from the theoretical ends of the logic programming and artificial intelligence communities to discuss their mutual interests. Logic programming deals with the use of models of mathematical logic as a way of programming computers, where theoretical AI deals with abstract issues in modeling and representing human knowledge and beliefs. One common ground is nonmonotonic reasoning, a family of logics that includes room for the kinds of variations that can be (...) found in human reasoning. Topics covered: Stable Semantics. Default Logic. AutoEpistemic Logic. Truth Maintenance Systems. Implementation Issues. Diagnosis. Applications. Inheritance Reasoning. Logics of Belief. Inconsistency and Non-Monotonicity. (shrink)

Large sets of elements interacting locally and producing specific architectures reliably form a category that transcends the usual dividing line between biological and engineered systems. We propose to call them morphogenetically architected complex systems. While taking the emergence of properties seriously, the notion of MACS enables at the same time the design of operational means that allow controlling and even, paradoxically, programming this emergence. To demonstrate our claim, we first show that among all the self-organized systems studied in the (...) field of Artificial Life, the specificity of MACS essentially lies in the close relation between their emergent properties and functional properties. Second, we argue that to be a MACS a system does not need to display more than weak emergent properties. Third, since the notion of weak emergence is based on the possibility of simulation, whether computational or mechanistic via machines, we see MACS as good candidates to help design artificial self-architected systems but also harness and redesign living ones. (shrink)

I examine the branch of evolutionary epistemology which tries to account for the character of cognitive mechanisms in animals and humans by extending the biological theory of evolution to the neurophysiological substrates of cognition. Like Plotkin, I construe this branch as a struggling science, and attempt to characterize the sort of theory one might expect to find this truly interdisciplinary endeavor, an endeavor which encompasses not only evolutionary biology, cognitive psychology, and developmental neuroscience, but also and especially, the computational modeling (...) of artificial life programming; I suggest that extending Schaffner''s notion of interlevel theories to include both horizontal and vertical levels of abstraction best fits the theories currently being developed in cognitive science. Finally, I support this claim with examples drawn from computational modeling data using the genetic algorithm. (shrink)

Wittgenstein’s Private Language Argument holds that language requires rule-following, rule following requires the possibility of error, error is precluded in pure introspection, and inner mental life is known only by pure introspection, thus language cannot exist entirely within inner mental life. Fodor defends his Language of Thought program against the Private Language Argument with a dilemma: either privacy is so narrow that internal mental life can be known outside of introspection, or so broad that computer language serves (...) as a counter-example. I suggest that the developing field of artificial intelligence (deep learning neural networks) tends to vitiate Fodor’s defense and hence vindicate the Private Language Argument. The first horn of Fodor’s dilemma requires language to encompass genuinely internal mental life, i.e. non-projected intentional states, which are not exhibited in classical machine learning but only by deep learning neural networks (artificial intelligence). Such networks act as black boxes, however, whose state cannot be understood by tracking the changes in their supervenience bases without shared context, and that shared context introduces the possibility of error. The language of artificial intelligence is not private. (shrink)

Current research in artificial intelligence (AI) sheds light on algorithmic bias embedded in AI systems. The underrepresentation of women in the AI design sector of the tech industry, as well as in training datasets, results in technological products that encode gender bias, reinforce stereotypes and reproduce normative notions of gender and femininity. Biased behaviour is notably reflected in anthropomorphic AI systems, such as personal intelligent assistants (PIAs) and chatbots, that are usually feminized through various design parameters, such as names, (...) voices and traits. Gendering of AI entities, however, is often reduced to the encoding of stereotypical behavioural patterns that perpetuate normative assumptions about the role of women in society. The impact of this behaviour on social life increases, as human-to-(anthropomorphic)machine interactions are mirrored in human-to-human social interactions. This article presents current critical research on AI bias, focusing on anthropomorphic systems. Moreover, it discusses the significance of women’s engagement in AI design and programming, by presenting selected case studies of contemporary female media artists and designers. Finally, it suggests that women, through their creative practice, provide feminist and critical approaches to AI design which are essential for imagining alternative, inclusive, ethic and de-biased futures for anthropomorphic AIs. (shrink)

When posing the question "is artificial life possible?", our immediate answer is that on the one hand : of course it is - people make it, and indeed very interesting and even breathtaking structures have already been constructed, such as `aminats', self-reproducing patterns and the other things, we have seen already. In this sense we are forced to take artificial life as a fact (at least as a fact about a new branch of research), nearly in (...) the same way that the philosopher Kant took the theoretical physics of his days, Newtonian physics, as a matter of fact, and then asked: What are the conditions of possibility for this kind of theoretical science? On the other hand: The situation differs from Kant's. Artificial Life does not confront us with an analogy of theoretical mechanics within the field of biology. We face a curious situation: It is not obvious to the majority of biologists that Artificial Life is possible at all, at least in the purely computational sense of `software life'. Probably, most biologists would never call these artificial constructs `living'. Why not? Because the intuitive notions of life and living systems within biology implies, among other things, that living beings are a result of a long, ongoing evolutionary process that have created autonomous organisms, single-celled and multi-celled, that are highly organized, open (non-equilibrium), material thermodynamic systems based on metabolism and some kind of genetic information supported by macromolecules, that only metaphorically resemble a computer program. It is not that.. (shrink)

This paper describes and defends the view that minimal chemical life essentially involves the chemical integration of three chemical functionalities: containment, metabolism, and program (Rasmussen et al. in Protocells: bridging nonliving and living matter, 2009a ). This view is illustrated and explained with the help of CMP and Rasmussen diagrams (Rasmussen et al. In: Rasmussen et al. (eds.) in Protocells: bridging nonliving and living matter, 71–100, 2009b ), both of which represent the key chemical functional dependencies among containment, metabolism, (...) and program. The CMP model of minimal chemical life gains some support from the broad view of life as open-ended evolution, which I have defended elsewhere (Bedau in The philosophy of artificial life, 1996 ; Bedau in Artificial Life, 4:125–140, 1998 ). Further support comes from the natural way the CMP model resolves the puzzle about whether life is a matter of degree. (shrink)

PurposeThis paper aims to demonstrate the relevance of worldviews of the global south to debates of artificial intelligence, enhancing the human rights debate on artificial intelligence (AI) and critically reviewing the paper of UNESCO Commission on the Ethics of Scientific Knowledge and Technology (COMEST) that preceded the drafting of the UNESCO guidelines on AI. Different value systems may lead to different choices in programming and application of AI. Programming languages may acerbate existing biases as a people’s (...) worldview is captured in its language. What are the implications for AI when seen from a collective ontology? Ubuntu (I am a person through other persons) starts from collective morals rather than individual ethics.Design/methodology/approachLiterature overview on the African philosophy of Ubuntu as applied to artificial intelligence. Application of it to the United Nations Educational, Scientific and Cultural Organisation (UNESCO) debates on establishing guidelines to the ethics of artificial intelligence.FindingsMetaphysically, Ubuntu and its conception of social personhood (attained during one’s life) largely rejects transhumanism. When confronted with economic choices, Ubuntu favors sharing above competition and thus an anticapitalist logic of equitable distribution of AI benefits, humaneness and nonexploitation. When confronted with issues of privacy, Ubuntu emphasizes transparency to group members, rather than individual privacy, yet it calls for stronger (group privacy) protection. In democratic terms, it promotes consensus decision-making over representative democracy. Certain applications of AI may be more controversial in Africa than in other parts of the world, like care for the elderly, that deserve the utmost respect and attention, and which builds moral personhood. At the same time, AI may be helpful, as care from the home and community is encouraged from an Ubuntu perspective. The report on AI and ethics of the UNESCO World COMEST formulated principles as input, which are analyzed from the African ontological point of view. COMEST departs from “universal” concepts of individual human rights, sustainability and good governance which are not necessarily fully compatible with relatedness, including future and past generations. Next to rules based approaches, which may hamper diversity, bottom-up approaches are needed with intercultural deep learning algorithms.Research limitations/implicationsThere is very few existing literature on AI and Ubuntu. Therefore, this paper is of an explorative nature.Practical implicationsThe ethics of Ubuntu offers unique vantage points in looking at the organization of society and economics today, which are also relevant for development of AI, especially in its tenet of relatedness rather than individuality (and practical use of AI for individuals), taking responsibility for society as a whole (such as analyzing the benefit of AI for all strata of society), and embodying true inclusiveness. Whether looking at top-down guidelines for the development and implementation of AI or the bottom-up ethical learning process of AI (deep learning), ethics of the Global South can have an important role to play to combat global individualist tendencies and inequity, likely reinforced by AI. This warrants far more research.Social implicationsApplications of AI in Africa are not contextualized, do not address the most pressing needs of the African continent, lead to cybersecurity issues and also do not incorporate African ethics. UNESCO’s work in this regard is important but expert inputs are largely centered around Western “universal” principles and Organisation for Economic Cooperation and Development and EU precedence. African ethics have, so far, a small role to play in global ethics and philosophy and therefore risk to be overlooked in the discussion on AI and ethics. This is why the consultation process of UNESCO on ethics of AI was of paramount importance. However, it does not automatically lead to consultation of African philosophers or sages, as many are educated in Western (ized) education systems. See further details under practical implications.Originality/valueThis is a new area of research in which little work has been done so far. This paper offers the opportunity to widen the debate on AI and ethics beyond the conventional discourse, involving multiple worldviews, of which Ubuntu is just one. (shrink)

"The Bush administration and Congress are in concert on the goal of developing a fleet of unmanned aircraft that can reduce both defense costs and aircrew losses in combat by taking on at least the most dangerous combat missions. Unmanned combat aerial vehicles (UCAVs) will be neither inexpensive enough to be readily expendable nor-- at least in early development-- capable of performing every combat mission alongside or in lieu of manned sorties. Yet the tremendous potential of such systems is widely (...) recognized, and allies as well as potential adversaries are moving quickly to mount their own research and development programs. The United States is committed to fielding UCAV capabilities by 2010, principally for the missions of suppression of enemy air defense and deep strike, which are among the highest risk tasks for the Air Force and naval aviation."--Overview. (shrink)

This chapter uncovers the complex negotiations for authority in various representations about futures of life which have been advanced by different branches of the sciences, and have culminated in the emerging concept of life as algorithm. It charts the historical shifts in expertise and representations of life, from naturalists, to mathematical modellers, and specialists in computation, and argues that physicists, game theorists, and economists now take a leading role in explaining and projecting futures of life. The (...) chapter identifies Richard Dawkins and Max Tegmark at the forefront of the concept of life as algorithm: the first inspired by game theory as a means to study evolution; the second proposing that a materialist basis of life could place humans and artificial intelligence on an equal footing. Through close reading of their respective texts, the chapter demonstrates that both thinkers consider life as an algorithm programmed to achieve success in survival and reproduction. (shrink)

Charles Babbage began the quest to build an intelligent machine in the nineteenth century. Despite finishing neither the Difference nor the Analytical engine, he was aware that the use of mental language for describing the functioning of such machines was figurative. In order to reverse this cautious stance, Alan Turing postulated two decisive ideas that contributed to give birth to Artificial Intelligence: the Turing machine and the Turing test. Nevertheless, a philosophical problem arises from regarding intelligence simulation and make-believe (...) as sufficient to establish that programmed computers are intelligent and have mental states, especially given the nature of mind and its characteristic first-person viewpoint. The origin of Artificial Intelligence is undoubtedly linked to the accounts that inspired John Searle to coin the term strong AI ―or the view that simply equates computers and minds. Especially emphasising the divergence between algorithmic processes and intentional mental states, the Chinese Room thought experiment shows that, since the mind is embodied and able to realise when linguistic understanding takes place, mental states require material implementation, a point that directly conflicts with the accounts that reduce the mind to the functioning of a programmed computer. The experience of linguistic understanding with its typical quale leads to other important philosophical issues. Searle’s theory of intentionality holds that intentional mental states have conditions of satisfaction and appear in semantic networks; thus people know when they understand and what terms are about. In contrast, a number of philosophers maintain that consciousness is only an illusion and that it plays no substantial biological role. However, consciousness is a built-in feature of the system. Moreover, neurological evidence suggests that conscious mental states, qualia and emotions enhance survival chances and are an important part of the phenomenal side of mental life and its causal underpinnings. This renders an important gap between simulating a mind and replicating the properties that allow having mental states and consciousness. On this score, the Turing test and the evidence it offers clearly overestimate simulation and verisimilar make-believe, since such evidence is insufficient to establish that programmed computers have mental life. In summary, this dissertation criticises views which hold that programmed computers are minds and minds are nothing but computers. Despite the arguments in favour of such an equation, they all fail to properly reduce the mind and its first-person viewpoint. Accordingly, the burden of proof still lies with the advocates of strong AI and with those who are willing to deny fundamental parts of the mind to make room for machine intelligence. (shrink)

Artificial intelligence is among the fastest developing areas of advanced technology in medicine. The most important qualia of AI which makes it different from other advanced technology products is its ability to improve its original program and decision-making algorithms via deep learning abilities. This difference is the reason that AI technology stands out from the ethical issues of other advanced technology artifacts. The ethical issues of AI technology vary from privacy and confidentiality of personal data to ethical status and (...) value of AI entities in a wide spectrum, depending on their capability of deep learning and scope of the domains in which they operate. Developing ethical norms and guidelines for planning, development, production, and usage of AI technology has become an important issue to overcome these problems. In this respect three outstanding documents have been produced:1. The Montréal Declaration for Responsible Development of Artificial Intelligence2. Ethics Guidelines for Trustworthy AI3. Asilomar Artificial Intelligence PrinciplesIn this study, these three documents will be analyzed with respect to the ethical principles and values they involve, their perspectives for approaching ethical issues, and their prospects for ethical reasoning when one or more of these values and principles are in conflict. Then, the sufficiency of these guidelines for addressing current or prospective ethical issues emerging from the existence of AI technology in medicine will be evaluated. The discussion will be pursued in terms of the ambiguity of interlocutors and efficiency for working out ethical dilemmas occurring in practical life. (shrink)

This paper investigates the concept of behavioral autonomy in Artificial Life by drawing a parallel to the use of teleological notions in the study of biological life. Contrary to one of the leading assumptions in Artificial Life research, I argue that there is a significant difference in how autonomous behavior is understood in artificial and biological life forms: the former is underlain by human goals in a way that the latter is not. While (...) behavioral traits can be explained in relation to evolutionary history in biological organisms, in synthetic life forms behavior depends on a design driven by a research agenda, further shaped by broader human goals. This point will be illustrated with a case study on a synthetic life form. Consequently, the putative epistemic benefit of reaching a better understanding of behavioral autonomy in biological organisms by synthesizing artificial life forms is subject to doubt: the autonomy observed in such artificial organisms may be a mere projection of human agency. Further questions arise in relation to the need to spell out the relevant human aims when addressing potential social or ethical implications of synthesizing artificial life forms. (shrink)

Heuristic programming was the first area in which AI methods were tested. The favourite case-studies were fairly simple toy- problems, such as cryptarithmetic, games, such as checker or chess, and formal problems, such as logic or geometry theorem-proving. These problems are well-defined, roughly speaking, at least in comparison to real-life problems, and as such have played the role of Drosophila in early AI. In this chapter I will investigate the origins of heuristic programming and the shift to (...) more knowledge-based and real-life problem solving. (shrink)

Kazuo Ishiguro’s novel Klara and the Sun (2021) philosophizes on how in the current technologically saturated culture, the gradual evolution of the empathetic humanoids has, on one hand, problematized our normative notions of cognitive and affective categories, and on the other, has triggered an order of emotional uncanniness due to our reliance on hyperreal real objects for receiving solace and companionship. The novel may be conceived to be a commentary on the emerging discourse in the domain of cognitive and emotional (...) computing that aspires to transform the inner life and social relationships of the human community. The novelty of the paper lies in its ability to showcase how Kazuo Ishiguro’s Klara and the Sun (2021) creates a rupture in the existing research and literary narrative by critiquing the theoretical underpinnings of emotional computing that optimistically foresees a future where simulated empathetic minds will be able to decode the complexities of the human emotions. It discusses how literature turns into an apt tool to reflect on the limitations of the programmed machines to decode the elusiveness of the human mind that defies the one-to-one correlation between words, multiple connotations, and their underlying emotions. Through the lenses of the fictional narrative, the paper foregrounds how the concept of the social robot designed to offer empathy, care, and companionship turns into a failed project. The paper draws on critical perspectives from disposability theory, posthuman affect, and immaterial bodies to foreground the noncodified feature of affective experientialities that emerge as a result of the interface between humans and nonanimate beings. (shrink)

Mimicry is common among animals, plants, and other kingdoms of life. Humans in late capitalism, however, have devised an unique method of mimicking the signs that trigger evolutionarily-programmed instincts of their own species in order to manipulate them. Marketing and advertising are the most pervasive and sophisticated forms of known human mimicry, deliberately hijacking our instincts in order to select on the basis of one dimension only: profit. But marketing and advertising also strangely undermine their form of mimicry, deceiving (...) both the intended targets and the signaler simultaneously. Human forms of mimicry have the regular consequence of deceiving the imitator, reducing meta-cognitive awareness of the act and intentions surrounding such deception. Therefore, the deceiver in the end deceives himself as well as intended targets. Drawing on scholarship applying Niko Tinbergen’s ethological discovery of supernormal stimuli in animals to humans, this article analyzes sophisticated mass mimicry in contemporary culture, in both intended and unintended forms. (shrink)

Reports of the successful creation of artificial life usually garner considerable interest from philosophers. This paper argues that the worries philosophers have about artificial life do not, for the most part, depend on the artificiality of a given organism. In particular advances in synthetic biology will make the distinction between artificial and natural life a difficult and fluid one. Philosophers should hence refrain from making their arguments depend on a distinction between artificial and (...) natural life. (shrink)

In this paper I provide an epistemological context for Artificial Life projects. Later on, the insights which such projects will exhibit may be used as a general direction for further Artificial Life implementations. The purpose of such a model is to demonstrate by way of simulation how higher cognitive structures may emerge from building invariants by simple sensorimotor beings. By using the bottom-up methodology of Artificial Life, it is hoped to overcome problems that arise (...) from dealing with complex systems, such as the phenomenon of cognition. The research will lead to both epistemological and technical implications. The proposed ALife model is intended to point out the usefulness of an interdisciplinary approach including methodological approaches from disciplines such as Artificial Intelligence, Cognitive Science, Theoretical Biology, and Artificial Life. I try to put them in one single context. The epistemological background which is necessary for this purpose comes from the ideas developed in both epistemological and psychological Constructivism. The model differs from other ALife approaches— and is somewhat radical in this sense—as it tries to start on the lowest possible level, i.e. avoids several a priori assumptions and anthropocentric ascriptions. Due to this characterization, the project may be alternatively viewed as testing the complementary relationship between epistemology and methodology. (shrink)

Artificial life (also known as “ALife”) is a broad, interdisciplinary endeavor that studies life and life-like processes through simulation and synthesis. The goals of this activity include modelling and even creating life and life-like systems, as well as developing practical applications using intuitions and methods taken from living systems. Artificial life both illuminates traditional philosophical questions and raises new philosophical questions. Since both artificial life and philosophy investigate the essential nature (...) of certain fundamental aspects of reality like life and adaptation, artificial life offers philosophy a new perspective on these phenomena. This chapter provides an introduction to current research in artificial life and explains its philosophical implications. (shrink)

The purpose of this study was to evaluate the effectiveness of an educational intervention regarding end-of-life discussion directed at older Japanese adults and their attitude to and acceptance of this intervention. A quasi-experimental design was used. A total of 121 older adults, aged 65 years and over, consented to participate. Data from 55 intervention and 57 control participants were used for the analysis. The intervention consisted of an education program comprising a video, a lecture using a handout, and discussion (...) among participants. The control group received only the handout. Both groups were followed up after one month. The intervention group’s attitude became more favorable towards advance directives, especially living wills (P = 0.024). In addition, their expression of preference for life-sustaining treatment by means of artificial nutrition was less at follow up, demonstrating that these older adults had become more autonomous (P = 0.008). There was greater acceptance of the intervention as a whole by the intervention group compared with the control group (P = 0.011). Although few participants overall completed living wills, at follow up twice as many in the intervention group had discussed end-of-life matters with family members and/or their physician. (shrink)

Recent efforts in soft robotics and Artificial Life are attempting to construct homeostatically functioning machines with ‘feeling’ analogues. Such robots are designed to be ‘vulnerable’ and, thus, depart from traditional approaches to machine design and construction. In this paper, I explore a representative proposal by Antonio Damasio and Kingson Man, and ask how we can understand the deconstruction of ‘life’ in Derrida, Stiegler, Malabou and Wills to relate to such efforts. I argue that the adoption of biological (...) and phenomenological principles in machine design calls for attention to the precise extent that it may not result in robots that adhere either to biological or to mechanical models. It is with this admission, of the essentially unknowable character of what may result from these efforts, that deconstruction can assist roboticists and synthetic biologists today. (shrink)

To introduce this collection of research studies, which stem from the pro grams conducted by The World Phenomenology Institute, we need say a few words about our aims and work. This will bring to light the significance of the present volume. The phenomenological philosophy is an unprejudiced study of experience in its entire range: experience being understood as yielding objects. Experi ence, moreover, is approached in a specific way, such a way that it legitima tizes itself naturally in immediate evidence. (...) As such it offers a unique ground for philosophical inquiry. Its basic condition, however, is to legitimize its validity. In this way it allows a dialogue to unfold among various philosophies of different methodologies and persuasions, so that their basic assumptions and conceptions may be investigated in an objective fashion. That is, instead of comparing concepts, we may go below their differences to seek together what they are meant to grasp. We may in this way come to the things them selves, which are the common objective of all philosophy, or what the great Chinese philosopher Wang Yang Ming called "the investigation of things". It is in this spirit that the Institute's programs include a "cross-cultural" dialogue meant to bring about a profound communication among philosophers in their deepest concerns. Rising above artificial cultural confinements, such dialogues bring scholars, thinkers and human beings together toward a truly human community of minds. Our Institute unfolds one consistent academic program. (shrink)

In lieu of an abstract, here is a brief excerpt of the content:The Philosophic Foundations of Mimetic Theory and Cognitive Science(Including Artificial Intelligence)Jean-Pierre Dupuy (bio)In the mid 1970s I discovered at the same time cognitive science and mimetic theory. Being a philosopher with a scientific background, I immediately brought them together and tried to reconceptualize the latter in terms of the former. In a sense, I haven't stopped doing that in the last 45 years. That is why I feel (...) fully at home with the goals pursued by the organizers of this conference.I do not believe it is feasible or even desirable to operate the rapprochement between the two disciplines at a global level. The history of cognitive science is exceedingly involved, and the part played by artificial intelligence in it compared to the part played by the neurosciences has varied greatly over time.1 Only a piecemeal approach makes sense. I present here four short case studies that cover the whole period, from the beginnings in cybernetics to today's artificial intelligence (AI).In order to better situate these studies within a broader frame, I propose the diagram in Figure 1. To comment on it would require more time than available for my whole presentation. Let me just say the following. [End Page 1]It is essential to distinguish between two kinds of AI. The first to bear this name was launched by economist Herbert Simon and computer scientist Allan Newell at a Dartmouth conference in 1956. It was based on the premise that thinking is computing, with this computation bearing on sentences of a "language of thought" implementable in a digital computer. It turns out that this AI(1) was progressively substituted from the 1980s onward by an AI(2), which, to some extent, was a return to a fundamental result obtained by cybernetics in 1943. Neurophysiologist Warren McCulloch and mathematician Walter Pitts had constructed a mathematical model of a network of elementary calculators called "neurons" and explored its properties. The capacity to "think" was one of these. It was not situated at the elementary level, as was the case in AI(1), but it emerged at the collective level from the interactions between the neurons.This model was heavily criticized by the supporters of AI(1),2 and its first implementations, in the notorious "Perceptron" in particular (1957), were pitiful failures. However, the emergence of "second-order cybernetics" under the guidance of cybernetician Heinz von Foerster and the theory of complex, self-organizing systems that it helped develop, in cooperation and rivalry with similar efforts in the physical sciences, enabled the neural network model to come to a second life under different names: formal neurons, deep learning, big data, and the like. Together, they constitute AI(2).The following network of influences wouldn't have been possible without its stem, that is, the boxes containing the names of Kurt Gödel and Alan Turing. The former revolutionized logic by showing that reasoning about arithmetic and arithmetic are one and the same, insofar as it is possible to code in a 1-to-1 fashion propositions about integers (for instance, "7 is a prime number") by means of integers. The latter demonstrated that some mechanisms can self-transcend inasmuch as they generate an ensemble of outputs that cannot be defined mechanistically. Later, John von Neumann, who is credited along with Alan Turing with having invented the digital computer, would use this logical possibility to define complexity: A mechanism is complex if it is capable of generating one more complex than itself. The gate was open for the theories of complex, self-organizing systems to thrive and, by way of consequence, for AI(2) to emerge.fascination with modelsHerbert Simon (1916–2001), winner of the Nobel Prize in economics for his work on what he called "bounded rationality," is generally considered to be one [End Page 2] Click for larger view View full resolutionFigure 1.of the founders of artificial intelligence. Some cognitive scientists still rely on the computer program that he devised with Alan Newell to simulate the creative processes of human thought—a program aptly named "General Problem Solver." The title of one of his principal works, The Sciences of the... (shrink)

There are two likely paths for philosophers to follow in their encounters with Artificial Life: they can see it as a new way of doing philosophy, or simply as a new object worthy of philosophical attention using traditional methods. Is Artificial Life best seen as a new philosophical method or a new phenomenon? There is a case to be made for each alternative, but I urge philosophers to take the leap and consider the first to be (...) the more important and promising. (shrink)

The prelims comprise: The Roots of Artificial Life The Methodology of Artificial Life Emergence Adaptationism Evolutionary Progress The Nature of Life Strong Artificial Life Philosophical Methodology.

Recently, biologists and computer scientists who advocate the "strong thesis of artificial life" have argued that the distinction between life and nonlife is important and that certain computer software entities could be alive in the same sense as biological entities. These arguments have been challenged by Sober (1991). I address some of the questions about the rational reconstruction of biology that are suggested by these arguments: What is the relation between life and the "signs of (...) class='Hi'>life"? What work (if any) might the concept of "life" (over and above the "signs of life") perform in biology? What turns on scientific disputes over the utility of this concept? To defend my answers to these questions, I compare "life" to certain other concepts used in science, and I examine historical episodes in which an entity's vitality was invoked to explain certain phenomena. I try to understand how these explanations could be illuminating even though they are not accompanied by any reductive definition of "life.". (shrink)

This volume is the direct result of a conference in which a number of leading researchers from the fields of artificial intelligence and biology gathered to ...

Periodically in science there arrive on the scene what appear to be dramatically new theoretical frameworks (what the philosopher of science Thomas Kuhn has called paradigm shifts). Characteristic of such changes in perspective is the recasting of old problems in new terms. By altering the conceptual vocabulary we use to think about problems, we may discover solutions which were obscured by prior ways of thinking about things. Connectionism, artificial life, and dynamical systems are all approaches to cognition which (...) are relatively new and have been claimed to represent such paradigm shifts. Just how deep the shifts are remains an open question, but each of these approaches certainly seems to offer novel ways of dealing with basic questions in cognitive science. (shrink)

Cyberfeminism and Artificial Life examines construction, manipulation and re-definition of life in contemporary technoscientific culture. It takes a critical political view of the concept of life as information, tracing this through the new biology and the changing discipline of artificial life and its manifestation in art, language, literature, commerce and entertainment. From cloning to computer games, and incorporating an analysis of hardware, software and 'wetware', Sarah Kember demonstrates how this relatively marginal field connects with, (...) and connects up global networks of information systems. As well as offering suggestions for the evolution of [cyber]feminism in Alife environments, the author identifies the emergence of posthumanism; an ethics of the posthuman subject mobilized in the tension between cold war and post-cold war politics, psychological and biological machines, centralized and de-centralized control, top-down and bottom-up processing, autonomous and autopoietic organisms, cloning and transgenesis, species-self and other species. Ultimately, this book aims to re-focus concern on the ethics rather than on the 'nature' of life-as-it-could-be. (shrink)

This new volume in the acclaimed Oxford Readings in Philosophy sereis offers a selection of the most important philosophical work being done in the new and fast-growing interdisciplinary area of artificial life. Artificial life research seeks to synthesize the characteristics of life by artificial means, particularly employing computer technology. The essays here explore such fascinating themes as the nature of life, the relation between life and mind, and the limits of technology.

Artificial life (ALife) is the attempt to create artificial instances of life in a variety of media, but primarily within the digital computer. As such, the field brings together computationally-minded biologists and biologically-minded computer scientists. I argue that this new field is filled with interesting philosophical issues. However, there is a dearth of philosophers actively conducting research in this area. I discuss two books on the new field: Margaret A. Boden's The philosophy of artificial (...) class='Hi'>life and Christopher G. Langton's Artificial life: an overview. They cover three areas of philosophical interest: the definition of life, the relationship between life and mind, and the possibility of creating life within a computational environment. This discussion allows me to critique past work in the philosophy of ALife that tends to see the field as a proving ground for traditional arguments from the philosophy of artificial intelligence. Instead, I suggest, what is interesting about ALife is how it differs from artificial intelligence and that the most interesting philosophical issues in the area are those derived from biology, not psychology. I recommend that these two books taken together constitute an interesting introduction to ALife and the wealth of philosophical issues found therein. (shrink)

This article investigates artificial life image-making in relation to and as constituent of the moving image, specifically artificial life visualized in three-dimensional computer-generated space . Of particular interest in this examination is the view or `window', from the virtual camera, into the artificial life computational model or `world' , and how it organizes a dense field of expectations. Analogous to looking through a telescope or microscope, the view into the artificial life world (...) is monocular and often fixed in the world; in this regime we look `at' computer models, which are often referred to as agents, `creatures', `organisms' or `cyberbeasts'. This tactic of looking through the instrumentality of science, the arts of reality, is parallel to looking through André Bazin's `long take' in cinema and documentary film-making in which we look `at' an unmediated view of reality; in other words, in looking `at' an image of artificial life we look `through' a non-intrinsic regime of seeing. This investigation into the interpretative regime provides only a partial account of the intercultural traffic between artificial life and the moving image. I further this discussion by arguing that artificial life screen-based works are a contemporary extension and reworking of the nature film in that they provide accounts of the `natural' world that are familiar and similar to those of their filmic and cinematic predecessors. I contend that artificial life visualizations and the stories that often accompany the images are the latest manifestation of this photographic and filmic tradition. To illustrate my point I discuss the scientific project Daisyworld, the associated narrative that frames the research, and the researchers' attempt to mathematically model an `imaginary planet [with] a very simple biosphere'. This sets the scene to explore artificial life in relation to Disney wilderness and nature films. (shrink)

Many thinkers believe that the next transformational change in human organisation will be the onset of human-level artificial intelligence, and that the most likely method of achieving this will come through brain emulations or "ems": the ability to scan human brains and program their connections into ever faster computers. Taking this as his starting point, Hanson describes what a world dominated by these ems will be like.

The aim of this chapter is to show how the technological research activity called “artificial life” is shedding new light on human creativity. Artificial life aims to understanding the fundamental behavior of life-like systems by synthesizing that behavior in artificial systems (more on artificial life below). One of the most interesting behaviors of living systems is their creativity. Biological creativity can be found in both individual living organisms and in the whole biosphere—the (...) entire interconnected system comprised of all forms of life—but I will focus in this chapter on the biological creativity exhibited by the evolutionary process. This is the creativity that enabled the earliest simple life forms to spontaneously evolve into the incredibly rich and beautiful diversity of life that now surrounds us. This diversity of life includes the most complex adaptive and intelligent systems in the known universe. This is an amazingly powerful spontaneous creation process, indeed. I will refer to it as hyper-creativity to call attention to the way in which it produces qualitatively new and more complex kinds of adaptations. There is a similar quality in human creativity. I am thinking of the aesthetic and cultural creativity of artists, but also the intellectual creativity of scientists and scholars, as well as the commercial and practical creativity of craftsmen, businessmen, and entrepreneurs. And I want to focus especially on the hyper- creative aspects of human creativity—the way in which human activity can yield qualitatively new and more complex creations. (shrink)

English Abstract In Art as Experience, John Dewey decried the estrangement of art from lived human experience, both by artificial conceptual walls and the physical walls that secluded art within museums. Instead he argued that making and enjoying art are crucial organic functions that sustain communities and integrate individuals within their environments. In the 1920’s Diego Rivera became one of the luminaries of the Mexican muralist movement by creating frescoes that were rooted in Mexican life, both in their (...) subject matter and public location. Rivera and the other artists working within the government cultural program guided by José Vasconcelos created murals that boldly expressed the new values of democracy, peaceful revolution, racial equality and cultural pride. This essay explores the deep resonance between Rivera’s most prominent murals from this period and Dewey’s argument that art is a refined and integral feature of human experience. In particular, this essay will examine the great extent to which these men independently came to the common understanding that for people to thrive and grow they need to create and experience art that grows out of and remains rooted in their culture. Without claiming that either thinker influenced the other, this essay argues that their works mutually inform and enrich each other. Both men sought to free art from the museum, but where Dewey urged us tear down the walls that separated art from lived experience, Rivera transformed walls themselves into murals that unified and educated the people of Mexico and restored their culture. (shrink)