The imaginative context in which artificial intelligence is embedded remains a crucial touchstone from which to understand and critique both the histories and prospective futures of an AI-driven world. A recent article from Cave and Dihal sets out a narrative schema of four hopes and four corresponding fears associated with intelligent machines and AI. This article seeks to respond to the work of Cave and Dihal by presenting a gendered reading of this schema of hopes and fears. I offer (...) a brief genealogy of narratives which feature female automata, before turning to examine how gendered technology today—particularly AI assistants like Siri and Alexa—reproduces the historical narratives associated with intelligent machines in new ways. Through a gendered reading of the hopes and fears associated with AI, two key responses arise. First, that the affective reactions to intelligent machines cannot be readily separated where such machines are gendered female. And second, that the gendering of AI technologies today can be understood as an attempt to reconcile the opposing hopes and fears AI produces, and that this reconciliation is based on the association of such technologies with traditional notions of femininity. Critically, a gendered reading enables us to problematize the narratives associated with AI and expose the power asymmetries that lie within, and the technologies which arise out of, such narratives. (shrink)

review of Stefano Franchi and Güven Güzeldere, eds., Mechanical Bodies, Computational Minds: Artificial Intelligence from Automata to Cyborgs.

Believing that the enterprise of constructing "artificial intelligence" transcends the bounds of any one discipline, the editors of Mechanical Bodies, Computational Minds have brought together researchers in AI and scholars in the humanities to reexamine the fundamental assumptions of both areas. The AI community, for example, could benefit from explorations of human intelligence and creativity by philosophers, psychologists, anthropologists, literary critics, and others, while analysis of AI's theoretical struggles and technical advances could yield insights into such traditional humanist concerns as (...) the nature of rationality and the mind-body dichotomy.The contributions include a continuation of the famous Hubert Dreyfus-Daniel Dennett debate over Kasparov's defeat by IBM's Deep Blue; Philip Agre's tracing of difficulties in AI research to the inherited tensions of Cartesian dualism; Evelyn Fox Keller's examination of the development of computer technology in relation to biology; Douglas Hofstadter's argument that thinking is more than the theorem-solving activities of AI; and Alison Adam's discussion of the implicitly male universal subject used in AI. (shrink)

This book brings together researchers from a variety of fields to jointly present and discuss some of the most relevant problems around the conscious mind. This academic plurality perfectly characterizes the complexity with which a current researcher is confronted to discuss and work on this topic. The volume is organized as follows: Part I introduces the general problems of Philosophy of Mind and some historical perspectives. Part II focuses on understanding the input that the empirical sciences can offer to the (...) theoretical problems. Part III discusses some of the core concepts of the field, namely, perception, memory and experience. Part IV debates human and artificial intelligence and, finally, Part V deliberates about the computation and the ethics of big data and artificial intelligence. The book contains valuable material for researchers in several fields such as Cognitive Science and Neuroscience, Psychology and Artificial Intelligence, and Philosophy. It can also be used as a guide to some courses at various levels, from BAs to MAs and PhD courses of several fields. It is our belief, as it is claimed in the preface by Georg Northoff, that there is an urgent need for a truly transdisciplinary exchange between philosophy and the sciences in order to stimulate some real progress. We hope that this book will become a sound step for such an interdisciplinary enterprise. (shrink)

IT is the major stumbling block to the claim that machines could one day possess true intelligence. The question is not whether machines would be able to produce outputs indistinguishable from those of a person, as proponents of “artificial intelligence” have traditionally maintained. Searle has shown, rather, that the real question is whether machines could ever be conscious of objects in the way we know ourselves to be. That would seem to make it, at least in part, a phenomenological problem. (...) By means of microphenomenology, then, I shall try to show that the basic structure of IT, as detected in reflection, can be analyzed in terms of an even more primitive factor, FA. Since attentional processes can be correlated with neurological selectivity, it will be argued that any machine constructed to perform such processes would be capable of IT. I shall, in short, attempt to support the possibility of creating automata capable of intentional activities by trying to describe how they occur in ourselves. (shrink)

The animation-effect of the movement-image constitutes not only a form of life but also a machinic analogue for Husserl's and Kant's accounts of temporality, engendering what Bernard Stiegler calls ‘a cinematography of consciousness’. If autonomous movement is the hallmark of the living being as well as the inanimate mechanism, the movement-image likewise subtends scenes of human and artificial intelligence. Pairing a cybernetic reading of Lacan's mirror stage essay with reflections on the self-recognition dance of Machina Speculatrix (an early example of (...) a biomimetic robot), this essay considers how exosomatic feedback loops enable a kind of ipseity for machinic life as well as the human being as technical being. Despite adopting Derrida's ideas of originary prostheticity and automaticity, rendering living beings as always-already machinic life, Stiegler sets arche-cinema against arche-writing. (shrink)

In this paper, we present an intelligent tutoring system developed to help students in learning Computer Theory. The Intelligent tutoring system was built using ITSB authoring tool. The system helps students to learn finite automata, pushdown automata, Turing machines and examines the relationship between these automata and formal languages, deterministic and nondeterministic machines, regular expressions, context free grammars, undecidability, and complexity. During the process the intelligent tutoring system gives assistance and feedback of many types (...) in an intelligent manner according to the behavior of the student. An evaluation of the intelligent tutoring system has revealed reasonably acceptable results in terms of its usability and learning abilities are concerned. (shrink)

As machines have become increasingly smart and have entangled human thinking with artificial intelligences, it seems no longer possible to distinguish among levels of decision-making that occur in the newly formed space between critical reasoning, logical inference and sheer calculation. Since the 1980s, computational systems of information processing have evolved to include not only deductive methods of decision, whereby results are already implicated in their premises, but have crucially shifted towards an adaptive practice of learning from data, an inductive method (...) of retrieving information from the environment and establishing general premises. This shift in logical methods of decision-making does not simply concern technical apparatuses, but is a symptom of a transformation in logical thinking activated with and through machines. This article discusses the pioneering work of Katherine Hayles, whose study of the cybernetic and computational infrastructures of our culture particularly clarifies this epistemological transformation of thinking in relation to machines. (shrink)

Our narratives about intelligent machines reprise the same modes in which humans have historically dealt with "other" groups of humans, especially during the era of colonialism. Addressing unconscious assumptions involving race, gender, hierarchy, power, imperialism, and capitalism in the post-colonial world, this book argues that cultural narratives regarding intelligent machines have much to do with colonial attitudes and mindsets. Human attitudes toward intelligent machines, colored by such ideological and cultural biases, cumulatively manifest themselves as cultural narratives of (...) a racialized Machine Other. This book explores how examining the emotions underlying our narratives about intelligent machines can provide insights into the human psyche and be a catalyst for authentic encounters with intelligent machines. It will beckon you to question long-held assumptions, confront the complexities of AI and racial dynamics, and embark on a quest for deeper understanding of yourself. (shrink)

In this paper I explore the question of how artificial life might be used to get a handle on philosophical issues concerning the mind-body problem. I focus on questions concerning what the physical precursors were to the earliest evolved versions of intelligent life. I discuss how cellular automata might constitute an experimental platform for the exploration of such issues, since cellular automata offer a unified framework for the modeling of physical, biological, and psychological processes. I discuss what (...) it would take to implement in a cellular automaton the evolutionary emergence of cognition from non-cognitive artificial organisms. I review work on the artificial evolution of minimally cognitive organisms and discuss how such projects might be translated into cellular automata simulations. (shrink)

The paradox of biological diversity is the key problem of theoretical ecology. The paradox consists in the contradiction between the competitive exclusion principle and the observed biodiversity. The principle is important as the basis for ecological theory. On a relatively simple model we show a mechanism of indefinite coexistence of complete competitors which violates the known formulations of the competitive exclusion principle. This mechanism is based on timely recovery of limiting resources and their spatio-temporal allocation between competitors. Because of limitations (...) of the black-box modeling there was a problem to formulate the exclusion principle correctly. Our white-box multiscale model of two-species competition is based on logical deterministic individual-based cellular automata. This approach provides an automatic deductive inference on the basis of a system of axioms, and gives a direct insight into mechanisms of the studied system. It is one of the most promising methods of artificial intelligence. We reformulate and generalize the competitive exclusion principle and explain why this formulation provides a solution of the biodiversity paradox. In addition, we propose a principle of competitive coexistence. (shrink)

El objetivo de este artículo es mostrar los fundamentos de la investigación en la cual se ha desarrollado Silogismos, un autómata que realiza la inferencia, identifica figura y modo de los silogismos, reconoce y diferencia entimemas y sofismas; éste fue desarrollado en Prolog -una plataforma de Inteligencia Artificial (IA)- como parte de un proyecto de investigación tendiente a representar computacionalmente la mente tal y como la concibió Aristóteles, para el caso de la lógica en el Órganon, para el caso de (...) la persuasión en la Retórica, etcétera. En el §1 se presenta el contexto de esta investigación; en el §2. de manera particular, se caracteriza el aporte de la silogística a la IA y a la filosofía de la mente, en el §3 se establecen las limitaciones de la lógica aristotélica para su automatización; en el §4 se estudia la perspectiva de investigación abierta con los proyectos de automatización. (shrink)

Both Putnam and Searle have argued that that every abstract automaton is realized by every physical system, a claim that leads to a reductio argument against Cognitivism or Strong AI: if it is possible for a computer to be conscious by virtue of realizing some abstract automaton, then by Putnam’s theorem every physical system also realizes that automaton, and so every physical system is conscious—a conclusion few supporters of Strong AI would be willing to accept. Dennett has suggested a criterion (...) of reverse engineering for identifying “real patterns,” and I argue that this approach is also very effective at identifying “real realizations.” I focus on examples of real-world implementations of complex automata because previous attempts at answering Putnam’s challenge have been overly restrictive, ruling out some realizations that are in fact paradigmatic examples of practical automaton realization. I also argue that some previous approaches have at the same time been overly lenient in accepting counter-intuitive realizations of trivial automata. I argue that the reverse engineering approach avoids both of these flaws. Moreover, Dennett’s approach allows us to recognize that some realizations are better than others, and the line between real realizations and non-realizations is not sharp. (shrink)

I shall argue that software agents can be attributed cognitive states, since their behaviour can be best understood by adopting the intentional stance. These cognitive states are legally relevant when agents are delegated by their users to engage, without users’ review, in choices based on their the agents’ own knowledge. Consequently, both with regard to torts and to contracts, legal rules designed for humans can also be applied to software agents, even though the latter do not have rights and duties (...) of their own. The implications of this approach in different areas of the law are then discussed, in particular with regard to contracts, torts, and personality. (shrink)

The notion of “responsibility gap” with artificial intelligence (AI) was originally introduced in the philosophical debate to indicate the concern that “learning automata” may make more difficult or impossible to attribute moral culpability to persons for untoward events. Building on literature in moral and legal philosophy, and ethics of technology, the paper proposes a broader and more comprehensive analysis of the responsibility gap. The responsibility gap, it is argued, is not one problem but a set of at least four (...) interconnected problems – gaps in culpability, moral and public accountability, active responsibility—caused by different sources, some technical, other organisational, legal, ethical, and societal. Responsibility gaps may also happen with non-learning systems. The paper clarifies which aspect of AI may cause which gap in which form of responsibility, and why each of these gaps matter. It proposes a critical review of partial and non-satisfactory attempts to address the responsibility gap: those which present it as a new and intractable problem (“fatalism”), those which dismiss it as a false problem (“deflationism”), and those which reduce it to only one of its dimensions or sources and/or present it as a problem that can be solved by simply introducing new technical and/or legal tools (“solutionism”). The paper also outlines a more comprehensive approach to address the responsibility gaps with AI in their entirety, based on the idea of designing socio-technical systems for “meaningful human control", that is systems aligned with the relevant human reasons and capacities. (shrink)

The Turing Machine presents itself as the very landmark and initial design of digital automata present in all modern general-purpose digital computers and whose design on computable numbers implies deeply ontological as well as epistemological foundations for today’s computers. These lines of work attempt to briefly analyze the fundamental epistemological problem that rose in the late 19th and early 20th century whereby “machine cognition” emerges. The epistemological roots addressed in the TM and notably in its “Halting Problem” uncovers the (...) tension between determinism and uncertainty, regarded here as the primal and inherent features of machine cognition. Resumen La Máquina de Turing se presenta como el hito y el diseño inicial de un autómata digital presente en todas las computadoras digitales modernas de propósito general y cuyo diseño en números computables establece bases profundamente ontológicas y epistemológicas para las computadoras de hoy. Estas líneas de trabajo intentan analizar brevemente el problema epistemológico fundamental que surgió a finales del siglo XIX y principios del XX mediante el cual emerge la “cognición de la máquina”. Las raíces epistemológicas que se abordan en la TM y, en particular, en su “Problema de detención” ponen al descubierto la tensión entre el determinismo y la incertidumbre, consideradas aquí, como las características primordiales e inherentes de la cognición de la máquina. (shrink)

Artificial intelligence (AI) technologies are increasingly creeping into the work sphere, thereby gradually questioning and/or disturbing the long-established moral concepts and norms communities have been using to define what makes work good. Each community, and Muslims make no exception in this regard, has to revisit their moral world to provide well-thought frameworks that can engage with the challenging ethical questions raised by the new phenomenon of AI-mediated work. For a systematic analysis of the broad topic of AI-mediated work ethics from (...) an Islamic perspective, this article focuses on presenting an accessible overview of the “moral world” of work in the Islamic tradition. Three main components of this moral world were selected due to their relevance to the AI context, namely (1) Work is inherently good for humans, (2) Practising a religiously permitted profession and (c) Maintaining good relations with involved stakeholders. Each of these three components is addressed in a distinct section, followed by a sub-section highlighting the relevance of the respective component to the particular context of AI-mediated work. The article argues that there are no unsurmountable barriers in the Islamic tradition against the adoption of AI technologies in work sphere. However, important precautions should be considered to ensure that embracing AI will not be at the cost of work-related moral values. The article also highlights how important lessons can be learnt from the positive historical experience of automata that thrived in the Islamic civilization. (shrink)

Two views of AI in leisure and the work-place and two views of society are discussed. There is a conceptualisation of AI systems enhancing people in their work and leisure and another of AI automata which tends to degrade and replace human activity. Researchers tend to resolve into “Optimists” who work within a micro-sociological view and see AI systems as inevitable and beneficent. Others are “Pessimists” who adopt a macro-sociological view and see AI in its automata role and (...) deliterious social consequences. These polarised perspectives must be integrated as only “enhancing AI” is socially acceptable. (shrink)

This review presents a state of the art in artificial intelligence applied to urban planning and particularly to land-use predictions. In this review, different articles after the year 2016 are analyzed mostly focusing on those that are not mentioned in earlier publications. Most of the articles analyzed used a combination of Markov chains and cellular automata to predict the growth of urban areas and metropolitan regions. We noticed that most of these simulations were applied in various areas of China. (...) An analysis of the publication of articles in the area over time is included. (shrink)

Traditionally, the manufacturer/operator of a machine is held (morally and legally) responsible for the consequences of its operation. Autonomous, learning machines, based on neural networks, genetic algorithms and agent architectures, create a new situation, where the manufacturer/operator of the machine is in principle not capable of predicting the future machine behaviour any more, and thus cannot be held morally responsible or liable for it. The society must decide between not using this kind of machine any more (which is not a (...) realistic option), or facing a responsibility gap, which cannot be bridged by traditional concepts of responsibility ascription. (shrink)

Based on the standpoint close to that of philosophical functionalism, the paper addresses the history and present state of scientific research on artificial reconstruction of some of the rational thinking functions, and acquisition of valid knowledge of phenomenally given actuality, by way of engineering artificial intelligent automata. Thereby, the author examines the settings of emergence of an attendant basic ontology, and the place of logic in the process of knowing, by intelligent automata and humans, accordingly. Analysis (...) and collations are made by proceeding from the phenomenalistic logic and ontology presupposition in the theory of experience and knowing, as previously detailed by the author. Under this presupposition, the actual is considered temporally ordered facts with attached significance used to order them logically, in reciprocally defining them logical relations as a result of phenomenal statements on their identification and re-identification as such. The paper offers an overview of primary logical and ontological foundations for operation of intelligent automata classed as “expert systems” in their collation with a correspondent model of functionally determined meaningful activity of humans, while making the case for the observation on a sufficient functional parallelism between them, against the background of their noted specifics. By moving on to engineering intelligent automata classed as “machine learning systems” grounded on “connectionism”, prospects for overcoming the deficit of reflexive plasticity in “artificial intelligence”, and the effect of fundamental convergence between the human functional intelligence and an “artificial” intelligence, are clarified. Admitting a demonstrated functional success of such intelligent automata in the functional context, along with their logic being affined to that of humans, the notion of intelligence incurs significant de-humanization. Manuscript received 14.02.2020. (shrink)

This presentation discusses a notion encountered across disciplines, and in different facets of human activity: autonomous activity. We engage it in an interdisciplinary way. We start by considering the reactions and behaviors of biological entities to biotechnological intervention. An attempt is made to characterize the degree of freedom of embryos & clones, which show openness to different outcomes when the epigenetic developmental landscape is factored in. We then consider the claim made in programming and artificial intelligence that automata could (...) show self-directed behavior as to the determination of their step-wise decisions on courses of action. This question remains largely open and calls for some important qualifications. We try to make sense of the presence of claims of freedom in agency, first in common sense, then by ascribing developmental plasticity in biology and biotechnology, and in the mapping of programmed systems in the presence of environmental cues and self-referenced circuits as well as environmental coupling. This is the occasion to recall attempts at working out a logical and methodological approach to the openness of concepts that are still to be found, and assess whether they can operate the structuring intelligibility of a yet undeveloped or underdeveloped field of study, where a “bisociation" and a unification of knowledge might be possible. (shrink)

With 500+ papers and 20+ books spanning many scientific disciplines, Mark Burgin has left an indelible mark and legacy for future explorers of human thought and information technology professionals. In this paper, I discuss his contribution to the evolution of machine intelligence using his general theory of information (GTI) based on my discussions with him and various papers I co-authored during the past eight years. His construction of a new class of digital automata to overcome the barrier posed by (...) the Church–Turing Thesis, and his contribution to super-symbolic computing with knowledge structures, cognizing oracles, and structural machines are leading to practical applications changing the future landscape of information systems. GTI provides a model for the operational knowledge of biological systems to build, operate, and manage life processes using 30+ trillion cells capable of replication and metabolism. The schema and associated operations derived from GTI are also used to model a digital genome specifying the operational knowledge of algorithms executing the software life processes with specific purposes using replication and metabolism. The result is a digital software system with a super-symbolic computing structure exhibiting autopoietic and cognitive behaviors that biological systems also exhibit. We discuss here one of these applications. (shrink)

As arti® cial intelligence moves ever closer to the goal of producing fully autonomous agents, the question of how to design and implement an arti® cial moral agent (AMA) becomes increasingly pressing. Robots possessing autonomous capacities to do things that are useful to humans will also have the capacity to do things that are harmful to humans and other sentient beings. Theoretical challenges to developing arti® cial moral agents result both from controversies among ethicists about moral theory itself, and from (...) computational limits to the implementation of such theories. In this paper the ethical disputes are surveyed, the possibility of a `moral Turing Test ’ is considered and the computational di culties accompanying the diŒerent types of approach are assessed. Human-like performance, which is prone to include immoral actions, may not be acceptable in machines, but moral perfection may be computationally unattainable. The risks posed by autonomous machines ignorantly or deliberately harming people and other sentient beings are great. The development of machines with enough intelligence to assess the eŒects of their actions on sentient beings and act accordingly may ultimately be the most important task faced by the designers of arti® cially intelligent automata. (shrink)

Cellular Automata, which is a method for analyzing phenomena of complex systems, allows us to construct many kinds of simulators such as road traffic simulators. When we design a CA model, we need a CA simulator for verification of its result. However, at the present, we need to develop a software simulator since CA dedicated computers have not been generalized yet. We need to use a trial and error method with the simulator for design of local rules, which is (...) the main process of making CA models. We have developed an interpreter that makes this process easily. Giving the system a local rule described in a CA dedicated language, the user can instantly confirm the result. When the user change the rules, the system reflects his changes immediately. Our system does not regulate to design the local rules belonging to the CA category because the system is a general purpose CA simulator that adopts the method by description in the special language for definitions of local rules. We can modify a rule dramatically since the system interprets a rule description language in runtime. Furthermore, we can change variable parameters using GUI interfaces. Whereby they iterate to change a rule, a conflictive conditional statement sometimes occurs in a description of local rules. This conflict is far from seeking generally. Our system detects such a conflict automatically and notifies it to users as an error. (shrink)

Artificial intelligence is becoming increasingly entwined with our daily lives: AIs work as assistants through our phones, control our vehicles, and navigate our vacuums. As these objects become more complex and work within our societies in ways that affect our well-being, there is a growing demand for machine ethics—we want a guarantee that the various automata in our lives will behave in a way that minimizes the amount of harm they create. Though many technologies exist as moral artifacts, the (...) development of a truly ethical AI system is highly contentious; theorists have proposed and critiqued countless possibilities for programming these agents to become ethical. Many of these arguments, however, presuppose the possibility that an artificially intelligent system can actually be ethical. In this essay, I will explore a potential path to AI ethics by considering the role of imagination in the deliberative process via the work of John Dewey and his interpreters, showcasing one form of reinforcement learning that mimics imaginative deliberation. With these components in place, I contend that such an artificial agent is capable of something very near ethical behavior—close enough that we may consider it so. (shrink)

To clarify the notion of computation and its role in cognitive science, we need an account of implementation, the nexus between abstract computations and physical systems. I provide such an account, based on the idea that a physical system implements a computation if the causal structure of the system mirrors the formal structure of the computation. The account is developed for the class of combinatorial-state automata, but is sufficiently general to cover all other discrete computational formalisms. The implementation relation (...) is non-vacuous, so that criticisms by Searle and others fail. This account of computation can be extended to justify the foundational role of computation in artificial intelligence and cognitive science. (shrink)

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

In his article “On Mechanical Recognition” R. J. Nelson brings to bear a branch of mathematical logic called automata theory on problems of artificial intelligence. Specifically he attacks the anti-mechanist claim that “[i]nasmuch as human recognition to a very great extent relies on context and on the ability to grasp wholes with some independence of the quality of the parts, even to fill in the missing parts on the basis of expectations, it follows that computers cannot in principle be (...) programmed to recognize or learn to recognize all patterns”, p. 24). Nelson proposes, contrary to this claim, that “gestalt recognition is not beyond digital automata”. in particular, he claims, he will establish by what he calls “Turing machine arguments” that the following four theses are true: automata can recognize different pattern types in one and the same set of instances;automata can recognize the “same” pattern in different sets of instances;automata can recognize incomplete, degraded patterns having missing or indeterminate parts;automata can recognize family resemblances. (shrink)

Turing tersely mentioned a notion of ``cultural search'' while otherwise deeply engaged in the design and operations of one of the earliest computers. His idea situated the individual squarely within a collaborative intellectual environment, but did he mean to suggest this in the form of a general information system? In the same writing Turing forecast mechanizations of proofs and outlined genetical searches, much later implemented in cellular automata. The conjecture explores the networked data-information-knowledge continuum as the subject of Turing's (...) notions of search and intelligence, using analogous models from library systems theory. Floridi's philosophy of information is posed as a potential guide to applied information services design of the Turing type. The initial problem is to identify a minimal set of assumptions from Turing's essay beyond the general context of computing. This set will form a bridge to an analogous set of principles in library systems models by eliciting supporting evidence in the literature relating the two. Finally it will be shown how Floridi's philosophy of information more fully encompasses Turing's insight in view of the conjecture. (shrink)

Elementary set theory accustoms the students to mathematical abstraction, includes the standard constructions of relations, functions, and orderings, and leads to a discussion of the various orders of infinity. The material on logic covers not only the standard statement logic and first-order predicate logic but includes an introduction to formal systems, axiomatization, and model theory. The section on algebra is presented with an emphasis on lattices as well as Boolean and Heyting algebras. Background for recent research in natural language semantics (...) includes sections on lambda-abstraction and generalized quantifiers. Chapters on automata theory and formal languages contain a discussion of languages between context-free and context-sensitive and form the background for much current work in syntactic theory and computational linguistics. The many exercises not only reinforce basic skills but offer an entry to linguistic applications of mathematical concepts. For upper-level undergraduate students and graduate students in theoretical linguistics, computer-science students with interests in computational linguistics, logic programming and artificial intelligence, mathematicians and logicians with interests in linguistics and the semantics of natural language. (shrink)

The most cursory examination of the history of artificial intelligence highlights numerous egregious claims of its researchers, especially in relation to a populist form of ‘strong’ computationalism which holds that any suitably programmed computer instantiates genuine conscious mental states purely in virtue of carrying out a specific series of computations. The argument presented herein is a simple development of that originally presented in Putnam’s monograph, “Representation & Reality”, which if correct, has important implications for turing machine functionalism and the prospect (...) of ‘conscious’ machines. In the paper, instead of seeking to develop Putnam’s claim that, “everything implements every finite state automata”, I will try to establish the weaker result that, “everything implements the specific machine Q on a particular input set ”. Then, equating Q to any putative AI program, I will show that conceding the ‘strong AI’ thesis for Q opens the door to a vicious form of panpsychism whereby all open systems,, must instantiate conscious experience and hence that disembodied minds lurk everywhere. (shrink)

The primary aim of this paper is twofold: firstly, to argue that we can enter into relation of trust with robots and AI systems (automata); and secondly, to provide a comprehensive description of the underlying mechanisms responsible for this relation of trust. To achieve these objectives, the paper first undertakes a critical examination of the main arguments opposing the concept of a trust-based relation with automata. Showing that these arguments face significant challenges that render them untenable, it thereby (...) prepares the ground for the subsequent positive analysis, proposing a framework in which these challenges can be addressed. According to this framework trust does not originate from mere reliability, but rather from an empathic relation with automata. This initial empathic relation elevates the automata to the status of what I will term "Otheroids." The paper then explores how this human-Otheroid relationship inherently possesses the seeds for the development of trust. Finally, it examines how these seeds can grow into a basic form of trust with Otheroids through the establishment of a rich history of interaction. (shrink)

In lieu of an abstract, here is a brief excerpt of the content:Spinoza and the Theory of Organism HANS JONAS I CARTESIANDUALISMlanded speculation on the nature of life in an impasse: intelligible as, on principles of mechanics, the correlation of structure and function became within the res extensa, that of structure-plus-function with feeling or experience (modes of the res cogitans) was lost in the bifurcation, and thereby the fact of life itself became unintelligible at the same time that the explanation (...) of its bodily performance seemed to be assured. The impasse became manifest in Occasionalism : its tour de force of an extraneous, divine "synchronization" of the outer and the inner world (the latter denied to animals) not only suffered from its extreme artificiality, the common failing of such ad hoc constructions, but even at so high a cost failed to accomplish its theoretical purpose by its own terms. For the animal machine, like any machine, raises beyond the question of the "how" that of the "what for" of its functioning---of the purpose for which it had thus been constructed by its maker.1 Its performance, however devoid of immanent teleology, must serve an end, and that end must be someone's end. This end may (directly) be itself, as indeed Descartes had implied when declaring self-preservation to be the effect of the functioning of the organic automaton. In that case the existence as such of the machine would be its end--either terminally, or in turn to benefit something else. In the former case, the machine would have to be more than a machine, for a mere machine cannot enioy its existence. But since, by the rigorous conception of the res extensa, it cannot be more than a machine, its function and/or existence must serve something other than itself. Automata in Descartes ' time were mainly for entertainment (rather than work). But the raison d'etre of the living kingdom could not well be seen in God's indulging his mechanical abilities or in the amusement of celestial spectators--especially since mere complexity of arrangement does not create new quality and thus add something to the unrelieved sameness of the simple substratum that might enrich the spectrum of being. For quality, beyond the primitive determinations of the extended per se, is the subjective creature of sensation, the confused representation of quantity in a mind; and thus organisms cannot harbor it because as mere machines they lack mentality, and pure spirits cannot because they lack sensuality, or the privilege of confusion and thereby of illusion with its possible enjoyment. And as to their intellectual enjoyment, even that, deprived of the thrill of discovery by the same token, would pale in the contemplation of what to sufficiently large The concept of "machine," adopted for its strict confinementto efficientcause, is still a finalisticconcept,even thoughthe final cause is no longer internal to the entity, as a mode of its own operation,but external to it as antecedent design. [43] 44 HISTORY OF PHILOSOPHY intellects is nothing but the ever-repeated exemplification of the same few, elementary (and ultimately trivial) truths. There remained, then, the time-honored--Stoic as well as Christian--idea that plants and animals are for the benefit of Man. Indeed, since the existence of a living world is the necessary condition for the existence of any of its members, the self-justifying nature of at least one such member (= species) would justify the existence of the whole. In Stoicism, Man provided this end by his possession of reason, which makes him the culmination of a terrestrial scale of being that is also self-justifying throughout all its grades (the end as the best of many that are good in degrees) ; in Christianity, by his possession of an immortal soul, which makes him the sole imago Dei in creation (the end as the sole issue at stake) ; and Cartesian dualism radicalized this latter position by making man even the sole possessor of inwardness or "soul" of any kind, thus the only one of whom "end" can meaningfully be predicated as he alone can entertain ends. All other life then, the product of physical necessity, can be considered his means. However, this traditional idea, in its anthropocentric vanity never a... (shrink)

“Articulate models” subservient to formal intelligence are imagined to be heterarchies of automata capable of performing the “symbolic (quasi-spatial) syntheses” of Luria (1973), where “quasi-spatial” points to the abstract core of spatiality: the symbol productions, combinations, and substitutions of algebraic reckoning. The alleged cognitive role of internal “topographic images” and of “efference copies” is confronted with this background and denied.

A core principle of modern science holds that a scientific explanation must not attribute will or agency to natural phenomena.The Restless Clock examines the origins and history of this, in particular as it applies to the science of living things. This is also the story of a tradition of radicals—dissenters who embraced the opposite view, that agency is an essential and ineradicable part of nature. Beginning with the church and courtly automata of early modern Europe, Jessica Riskin guides us (...) through our thinking about the extent to which animals might be understood as mere machines. We encounter fantastic robots and cyborgs as well as a cast of scientific and philosophical luminaries, including Descartes and Leibnitz, Lamarck and Darwin, whose ideas gain new relevance in Riskin's hands. The book ends with a riveting discussion of how the dialectic continues in genetics, epigenetics, and evolutionary biology, where work continues to naturalize different forms of agency.The Restless Clock reveals the deeply buried roots of current debates in artificial intelligence, cognitive science, and evolutionary biology. (shrink)

Hahmottelen tässä artikkelissa tekoälyn historiaa varhaismodernin filosofian aikakaudella 1600–1700-luvuilla. Esittelemäni aiheet ovat hieman erillisiä toisistaan, mutta yhteistä niille on ajatus komputaatiosta tai automaatiosta, eräänlaisesta mekaanisesta laskemisesta tai toiminnasta, jota voi pitää tekoälyn varhaisena lähtökohtana. -/- On kuitenkin huomattava, että pelkkä komputaatio eli informaation käsittely sinänsä ei riitä tekoälylle – kaikkia näitä pyrkimyksiä leimaa tietynlainen epistemologinen optimismi: automatisoidun ajattelun avulla uskotaan saatavan enemmän laadukasta tietoa ja kenties myös uudenlaisia ajatuksia, kun ajatteluprosessi tulee sujuvammaksi. Tekoälyn varhaishistoria liittyy siis nimenomaan inhimillisen ajattelun mekanisoimiseen (...) ja uskoon siitä, että sen avulla voidaan lieventää ihmismielen rajoituksia ja ajatella paremmin. Yhteistä sekä tekoälyn että tietokoneen historialle on kuitenkin laskennan kehitys. (shrink)

SummaryHuman consciousness can be viewed as language‐competence, speaking a language as a rule‐governed social form of behaviour. Explanations of cognitive faculties via comparison with artificial intelligence, however, are misleading, if we neglect that in talking about automata words as “rule”, “to act”, “to say something” and “to know” get a new and too narrow sense.

The computational metaphor of organisms as phenotypic automata controlled by a genetic programme has been replaced by the cognitive metaphor of organisms as intelligent agents making decisions about how to use their genomic and environmental resources. This metaphor facilitates novel ways of thinking about organisms that defy the assumptions of the old machine metaphor. But like all metaphors, the cognitive metaphor discloses important similarities at the expense of eclipsing significant dissimilarities. I argue that although cognitivism carries with it (...) the crucial insight that living organisms are agents rather than mere automata, this metaphor distorts the nature of biological agency by over-intellectualizing, which risks eliminating the distinction between life and mind. I trace the Cartesian root of these metaphors and argue that it generates a dilemma between mechanism and intellectualism. To capture the middle path that most organisms occupy between these two extremes, I propose an ecological account of natural agency. (shrink)

A brief history of affective responses to AI.

Recent work on representing action and change has introduced high-level action languages which describe the effects of actions as causal laws in a declarative way. Among such action languages, the language A is the first and the most basic language. In dynamic domains, an agent needs the ability to react against changes of environment and to generate robust plans for a long-term goal, and appropriate representation is necessary for this purpose. In real problems, however, it is difficult to describe complete (...) causal laws for the domain, but it is easier to get observations. In this paper, we propose an algorithm to learn causal laws from an incomplete domain description in the language A, given observations after performing action sequences. Our learning algorithm generates causal laws based on an algorithm to learn finite automata. We also prove the correctness of the learning algorithm. From the result in this work, induction of the effects of actions can now be formally characterized within action languages. (shrink)

This paper attempts to answer a central question in unsupervised learning: what does it mean to “make sense” of a sensory sequence? In our formalization, making sense involves constructing a symbolic causal theory that both explains the sensory sequence and also satisfies a set of unity conditions. The unity conditions insist that the constituents of the causal theory – objects, properties, and laws – must be integrated into a coherent whole. On our account, making sense of sensory input is a (...) type of program synthesis, but it is unsupervised program synthesis. Our second contribution is a computer implementation, the Apperception Engine, that was designed to satisfy the above requirements. Our system is able to produce interpretable human-readable causal theories from very small amounts of data, because of the strong inductive bias provided by the unity conditions. A causal theory produced by our system is able to predict future sensor readings, as well as retrodict earlier readings, and impute (fill in the blanks of) missing sensory readings, in any combination. In fact, it is able to do all three tasks simultaneously. We tested the engine in a diverse variety of domains, including cellular automata, rhythms and simple nursery tunes, multi-modal binding problems, occlusion tasks, and sequence induction intelligence tests. In each domain, we test our engine's ability to predict future sensor values, retrodict earlier sensor values, and impute missing sensory data. The Apperception Engine performs well in all these domains, significantly out-performing neural net baselines. We note in particular that in the sequence induction intelligence tests, our system achieved human-level performance. This is notable because our system is not a bespoke system designed specifically to solve intelligence tests, but a general-purpose system that was designed to make sense of any sensory sequence. (shrink)

Descartes held that animals are material automata without minds. However, this raises a puzzle. Descartes’s argument for this doctrine relies on the claims that animals lack language and general intelligence. But these claims seem compatible with the view that animals have minds. As a solution to this puzzle, I defend what I call theintrospective-analogicalinterpretation. According to this interpretation, Descartes employs introspection to show that certain human behaviors do not depend on thought but rather on automatic bodily processes. Descartes then (...) argues that animal behavior resembles only those behaviors that are automatic in humans. Analogy thus supports the view that the behaviors of animals do not depend on thought but are, rather, automatic. And if animal behavior is automatic, then animals are best regarded as automata. (shrink)

The concept of morality underpins the moral responsibility that not only depends on the outward practices (or ‘output,’ in the case of humanoid robots) of the agents but on the internal attitudes (‘input’) that rational and responsible intentioned beings generate. The primary question that has initiated the extensive debate, i.e., ‘Can humanoid robots be moral?’, stems from the normative outlook where morality includes human conscience and socio-linguistic background. This paper advances the thesis that the conceptions of morality and creativity interplay (...) with linguistic human beings instead of non-linguistic humanoid robots, as humanoid robots are indeed docile automata that cannot be responsible for their actions. To eradicate human ethics in order to make way for humanoid robot ethics highlights the moral actions and adequacy that hinges the myth of creative agency and self-dependency, which a humanoid robot can scarcely express. (shrink)