Computationalism

Искусственный интеллект – последняя, хотя и иллюзорная надежда продажных и провалившихся режимов как на Западе, так и на Востоке остаться на плаву: ведь тонущий хватается и за соломинку. Но всё течёт и всё изменяется, и никаким деспотиям и деспотам не удастся остановить ход истории, как бы они этого не желали и тому не противились. Хотя у истории нет конца, но их история и история совершённых ими предательств уже закончилась. Plaudite, cives, plaudite, amici, finita est comoedia: „Рукоплещите, граждане, друзья, комедия окончена.“.

This is an introduction to the 80 articles on philosophy in MITECS.

Fodor's thinking on modularity has been influential throughout a range of the areas studying cognition, chiefly as a prod for positive work on modularity and domain-specificity. In _The Mind Doesn't Work That Way_, Fodor has developed the dark message of _The Modularity of Mind_ regarding the limits to modularity and computational analyses. This paper offers a critical assessment of Fodor's scepticism with an eye to highlighting some broader issues in play, including the nature of computation and the role of recent (...) empirical developments in the cognitive sciences in assessing Fodor's position. (shrink)

Physical Computation is the summation of Piccinini’s work on computation and mechanistic explanation over the past decade. It draws together material from papers published during that time, but also provides additional clarifications and restructuring that make this the definitive presentation of his mechanistic account of physical computation. This review will first give a brief summary of the account that Piccinini defends, followed by a chapter-by-chapter overview of the book, before finally discussing one aspect of the account in more critical detail.

Report for "The Reasoner" on the conference "Philosophy and Theory of Artificial Intelligence", 3 & 4 October 2011, Thessaloniki, Anatolia College/ACT, http://www.pt-ai.org. --- Organization: Vincent C. Müller, Professor of Philosophy at ACT & James Martin Fellow, Oxford http://www.sophia.de --- Sponsors: EUCogII, Oxford-FutureTech, AAAI, ACM-SIGART, IACAP, ECCAI.

Immanuel Kant famously defined philosophy to be about three questions: “What can I know? What should I do? What can I hope for?” (KrV, B833). I want to suggest that the three questions of our course on the philosophy of computing are: What is computing? What should we do with computing? What could computing do?

1 Οι Αρχές - 2 Η δοκιμασία του Turing - 3 Η κλασική τεχνητή νοημοσύνη - 4 Η τεχνητή νοημοσύνη σήμερα - 5 Η τεχνητή νοημοσύνη του μέλλοντος - Με τις τεχνολογίες του παρόντος μάλλον θα δυσκολευτούμε να φτάσουμε στην κατασκευή μηχανών με τεχνητή νοημοσύνη. Κατά την γνώμη μου, θα δούμε άλλες τεχνικές λύσεις με την κλασική τεχνητή νοημοσύνη και μέθοδο «από κάτω προς τα πάνω», αλλά δεν περιμένω να υπάρξει ριζοσπαστική πρόοδος πριν μάθουμε πολλά παραπάνω για τον εγκέφαλό μας. (...) Υπάρχουν πολύ καλοί λόγοι για να λέμε ότι το μυαλό μας δεν είναι υπολογιστής και δεν περιμένω να μπορούμε να φτιάχνουμε νόηση μόνο με υπολογιστή. Αλλά θα μπορούσαμε με άλλα μηχανήματα, γιατί όχι;. (shrink)

Floridi and Taddeo propose a condition of “zero semantic commitment” for solutions to the grounding problem, and a solution to it. I argue briefly that their condition cannot be fulfilled, not even by their own solution. After a look at Luc Steels' very different competing suggestion, I suggest that we need to re-think what the problem is and what role the ‘goals’ in a system play in formulating the problem. On the basis of a proper understanding of computing, I come (...) to the conclusion that the only sensible ground-ing problem is how we can explain and re-produce the behavioral ability and function of meaning in artificial computational agents. (shrink)

In most accounts of realization of computational processes by physical mechanisms, it is presupposed that there is one-to-one correspondence between the causally active states of the physical process and the states of the computation. Yet such proposals either stipulate that only one model of computation is implemented, or they do not reflect upon the variety of models that could be implemented physically. -/- In this paper, I claim that mechanistic accounts of computation should allow for a broad variation of models (...) of computation. In particular, some non-standard models should not be excluded a priori. The relationship between mathematical models of computation and mechanistically adequate models is studied in more detail. (shrink)

[Müller, Vincent C. (ed.), (2016), Fundamental issues of artificial intelligence (Synthese Library, 377; Berlin: Springer). 570 pp.] -- This volume offers a look at the fundamental issues of present and future AI, especially from cognitive science, computer science, neuroscience and philosophy. This work examines the conditions for artificial intelligence, how these relate to the conditions for intelligence in humans and other natural agents, as well as ethical and societal problems that artificial intelligence raises or will raise. The key issues this (...) volume investigates include the relation of AI and cognitive science, ethics of AI and robotics, brain emulation and simulation, hybrid systems and cyborgs, intelligence and intelligence testing, interactive systems, multi-agent systems, and superintelligence. Based on the 2nd conference on “Theory and Philosophy of Artificial Intelligence” held in Oxford, the volume includes prominent researchers within the field from around the world. (shrink)

European Computing and Philosophy conference, 2–4 July Barcelona The Seventh ECAP (European Computing and Philosophy) conference was organized by Jordi Vallverdu at Autonomous University of Barcelona. The conference started with the IACAP (The International Association for CAP) presidential address by Luciano Floridi, focusing on mechanisms of knowledge production in informational networks. The first keynote delivered by Klaus Mainzer made a frame for the rest of the conference, by elucidating the fundamental role of complexity of informational structures that can be analyzed (...) on different levels of organization giving place for variety of possible approaches which converge in this cross-disciplinary and multi-disciplinary research field. Keynotes by Kevin Warwick about re-embodiment of rats’ neurons into robots, Raymond Turner on syntax and semantics in programming languages, Roderic Guigo on Biocomputing Sciences and Francesco Subirada on the past and future of supercomputing presented different topics of philosophical as well as practical aspects of computing. Vonference tracks included: Philosophy of Information (Patrick Allo), Philosophy of Computer Science (Raymond Turner), Computer and Information Ethics (Johnny Søraker and Alison Adam), Computational Approaches to the Mind (Ruth Hagengruber), IT and Cultural Diversity (Jutta Weber and Charles Ess), Crossroads (David Casacuberta), Robotics, AI & Ambient Intelligence (Thomas Roth-Berghofer), Biocomputing, Evolutionary and Complex Systems (Gordana Dodig Crnkovic and Søren Brier), E-learning, E-science and Computer-Supported Cooperative Work (Annamaria Carusi) and Technological Singularity and Acceleration Studies (Amnon Eden). (shrink)

The Genetic Algorithm (GA) and Simulated Annealing (SA), two techniques for global optimization, were applied to a reduced (simplified) form of the phase problem (RPP) in computational crystallography. Results were compared with those of "enhanced pair flipping" (EPF), a more elaborate problem-specific algorithm incorporating local and global searches. Not surprisingly, EPF did better than the GA or SA approaches, but the existence of GA and SA techniques more advanced than those used in this study suggest that these techniques still hold (...) promise for phase problem applications. The RPP is, furthermore, an excellent test problem for such global optimization methods. (shrink)

[Müller, Vincent C. (ed.), (2013), Philosophy and theory of artificial intelligence (SAPERE, 5; Berlin: Springer). 429 pp. ] --- Can we make machines that think and act like humans or other natural intelligent agents? The answer to this question depends on how we see ourselves and how we see the machines in question. Classical AI and cognitive science had claimed that cognition is computation, and can thus be reproduced on other computing machines, possibly surpassing the abilities of human intelligence. This (...) consensus has now come under threat and the agenda for the philosophy and theory of AI must be set anew, re-defining the relation between AI and Cognitive Science. We can re-claim the original vision of general AI from the technical AI disciplines; we can reject classical cognitive science and replace it with a new theory (e.g. embodied); or we can try to find new ways to approach AI, for example from neuroscience or from systems theory. To do this, we must go back to the basic questions on computing, cognition and ethics for AI. The 30 papers in this volume provide cutting-edge work from leading researchers that define where we stand and where we should go from here. (shrink)

Existential Cognition, divided into four parts of three chapters each, argues that the mind “is an essentially embedded entity; one such that analyzing it in isolation from the environmental context in which it functions will be fundamentally misleading”. Disputing internalists who accept, and who reject, information processing accounts of the mind, as well as anti-cognitivists who reject internalism, McClamrock argues for an externalist information processing account of mental states and processes.

David Skrbina opens this timely and intriguing text with a suitably puzzling line from the Diamond Sutra: ‘‘Mind that abides nowhere must come forth.’’, and he urges us to ‘‘de-emphasise the quest for the specifically human embodiment of mind’’ and follow Empedocles, progressing ‘‘with good will and unclouded attention’’ into the text which he has drawn together as editor. If we do, we are assured that it will ‘‘yield great things’’ (p. xi). This, I am pleased to say, is not (...) an exercise in hyperbole. (shrink)

Over the past decade or so, a new interdisciplinary field has emerged in the ground between, on the one hand, computer science – and artificial intelligence in particular – and, on the other, the area of philosophy concentrating on the language and structure of argument. There are now hundreds of researchers worldwide who would consider themselves a part of this nascent community. Various terms have been proposed for the area, including "Computational Dialectics," "Argumentation Technology," and "Argument-based Computing," but the term (...) that has stuck is simply Argument & Computation. It encompasses several specific strands of research, such as: . the use of theories of argument, and dialectic in particular, in the design and implementation of protocols for multi-agent action and communication; . the application of theories of argument and rhetoric in natural language processing and affective computing; . the use of argument-based structures for autonomous reasoning in artificial intelligence, and in particular, for defeasible reasoning; . computer-supported collaborative argumentation – the implementation of software tools for enabling online argument in domains such as education and e-government. These strands come together to form the core of a research field that covers parts of artificial intelligence (AI), philosophy, linguistics, and cognitive science, but, increasingly, is building an identity of its own. (shrink)

We argue that A. Damasio’s (1994) Somatic Marker hypothesis can explain why humans don’t generally suffer from the frame problem, arguably the greatest obstacle facing the Computational Theory of Mind. This involves showing how humans with damaged emotional centers are best understood as actually suffering from the frame problem. We are then able to show that, paradoxically, these results provide evidence for the Computational Theory of Mind, and in addition call into question the very distinction between easy and hard problems (...) in the contemporary philosophy of mind. (shrink)

You can survive after death in various kinds of artifacts. You can survive in diaries, photographs, sound recordings, and movies. But these artifacts record only superficial features of yourself. We are already close to the construction of programs that partially and approximately replicate entire human lives (by storing their memories and duplicating their personalities). A digital ghost is an artificially intelligent program that knows all about your life. It is an animated auto-biography. It replicates your patterns of belief and desire. (...) You can survive after death in a digital ghost. We discuss a series of digital ghosts over the next 50 years. As time goes by and technology advances, they are progressively more perfect replicas of the lives of their original authors. (shrink)