Vincent C. Müller

Einleitung - 1 Erklärung und Referenz (1973) - 2 Sprache und Wirklichkeit (1975) - 3 Was ist ‹Realismus›? (1975) - 4 Modelle und Wirklichkeit (1980) - 5 Referenz und Wahrheit (1980) - 6 Wie man zugleich interner Realist und transzendentaler Idealist sein kann (1980) - 7 Warum es keine Fertigwelt gibt (1982) - 8 Wozu die Philosophen? (1986) - 9 Realismus mit menschlichem Antlitz (1988/90) - 10 Irrealismus und Dekonstruktion (1992) - -/- Bibliographie der Schriften von Hilary Putnam - -/- Literaturverzeichnis - Register -.

Should we do speculative cognitive science? - In present day philosophy, I see a fashion that uses empirical facts (data) to support positions that are not philosophical but empirical in nature. The argumentative structure is classical philosophy, saying that ‘this has to be that way because …’ where the ‘this’ refers to some empirical state of affairs. This kind of philosophy speculates about empirical facts in areas where we do not yet know the facts – the arguments are a priori, supported by a posteriori data. This is precisely what the speculative philosophy of German Idealism was doing, e.g. in the works of Schelling or Hegel

Cognition is commonly taken to be computational manipulation of representations. These representations are assumed to be digital, but it is not usually specified what that means and what relevance it has for the theory. I propose a specification for being a digital state in a digital system, especially a digital computational system. The specification shows that identification of digital states requires functional directedness, either for someone or for the system of which it is a part. In the case or digital representations, to be a token of a representational type, where the function of the type is to represent. [An earlier version of this paper was discussed in the web-conference "Interdisciplines" https://web.archive.org/web/20100221125700/http://www.interdisciplines.org/adaptation/papers/7 ]

[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.

[This is the short version of: Müller, Vincent C. and Bostrom, Nick (forthcoming 2016), ‘Future progress in artificial intelligence: A survey of expert opinion’, in Vincent C. Müller (ed.), Fundamental Issues of Artificial Intelligence (Synthese Library 377; Berlin: Springer).] - - - In some quarters, there is intense concern about high–level machine intelligence and superintelligent AI coming up in a few dec- ades, bringing with it significant risks for human- ity; in other quarters, these issues are ignored or considered science fiction. We wanted to clarify what the distribution of opinions actually is, what probability the best experts currently assign to high–level machine intelligence coming up within a particular time–frame, which risks they see with that development and how fast they see these developing. We thus designed a brief questionnaire and distributed it to four groups of experts. Overall, the results show an agreement among experts that AI systems will probably reach overall human ability around 2040-2050 and move on to superintelligence in less than 30 years thereafter. The experts say the probability is about one in three that this development turns out to be ‘bad’ or ‘extremely bad’ for humanity.

We try to show that there is no difference in principle between communicating a piece of information to a human and to a machine. The argumentation depends on the following theses: Communicating is transfer of information; information has propositional form; propositional form can be modelled as categorization; categorisation can be modelled in a machine; a suitably equipped machine can grasp propositional content designed for human communication. What I suggest is that the discussion should focus on the truth and precise meaning of these statements. However, in case these statements are true it follows that: For any act of communication that successfully transfers a piece of information to a human, that act could also transfer that piece of information to a machine.

There is much discussion about whether the human mind is a computer, whether the human brain could be emulated on a computer, and whether at all physical entities are computers (pancomputationalism). These discussions, and others, require criteria for what is digital. I propose that a state is digital if and only if it is a token of a type that serves a particular function - typically a representational function for the system. This proposal is made on a syntactic level, assuming three levels of description (physical, syntactic, semantic). It suggests that being digital is a matter of discovery or rather a matter of how we wish to describe the world, if a functional description can be assumed. Given the criterion provided and the necessary empirical research, we should be in a position to decide on a given system (e.g. the human brain) whether it is a digital system and can thus be reproduced in a different digital system (since digital systems allow multiple realization).

Concordance of the poetic works of Giorgos Seferis which presents all the principal “words” of the texts in an alphabetical list, stating how often each word occurs, giving a precise location and a relevant piece of text for each occurrence. We found ca. 9500 different Greek words in 39000 different occurrences, so our concordance has 50.000 lines of text. The technical procedure required four main steps: text entry and tagging, production of the concordance, correction of the contexts, formatting for print.

Review of: "Computation, Information, Cognition: The Nexus and the Liminal", Ed. Susan Stuart & Gordana Dodig Crnkovic, Newcastle: Cambridge Scholars Publishing, September 2007, xxiv+340pp, ISBN: 9781847180902, Hardback: £39.99, $79.99 ---- Are you a computer? Is your cat a computer? A single biological cell in your stomach, perhaps? And your desk? You do not think so? Well, the authors of this book suggest that you think again. They propose a computational turn, a turn towards computational explanation and towards the explanation of computation itself. The explanation of computation is the core of the present volume, but the computational turn to regard a wide variety of systems as computational is a potentially very wide-ranging project

May lethal autonomous weapons systems—‘killer robots ’—be used in war? The majority of writers argue against their use, and those who have argued in favour have done so on a consequentialist basis. We defend the moral permissibility of killer robots, but on the basis of the non-aggregative structure of right assumed by Just War theory. This is necessary because the most important argument against killer robots, the responsibility trilemma proposed by Rob Sparrow, makes the same assumptions. We show that the crucial moral question is not one of responsibility. Rather, it is whether the technology can satisfy the requirements of fairness in the re-distribution of risk. Not only is this possible in principle, but some killer robots will actually satisfy these requirements. An implication of our argument is that there is a public responsibility to regulate killer robots ’ design and manufacture

The paper presents a paradoxical feature of computational systems that suggests that computationalism cannot explain symbol grounding. If the mind is a digital computer, as computationalism claims, then it can be computing either over meaningful symbols or over meaningless symbols. If it is computing over meaningful symbols its functioning presupposes the existence of meaningful symbols in the system, i.e. it implies semantic nativism. If the mind is computing over meaningless symbols, no intentional cognitive processes are available prior to symbol grounding. In this case, no symbol grounding could take place since any grounding presupposes intentional cognitive processes. So, whether computing in the mind is over meaningless or over meaningful symbols, computationalism implies semantic nativism.

If the intelligence of artificial systems were to surpass that of humans significantly, this would constitute a significant risk for humanity. Time has come to consider these issues, and this consideration must include progress in AI as much as insights from the theory of AI. The papers in this volume try to make cautious headway in setting the problem, evaluating predictions on the future of AI, proposing ways to ensure that AI systems will be beneficial to humans – and critically evaluating such proposals.

The theory and philosophy of artificial intelligence has come to a crucial point where the agenda for the forthcoming years is in the air. This special volume of Minds and Machines presents leading invited papers from a conference on the “Philosophy and Theory of Artificial Intelligence” that was held in October 2011 in Thessaloniki. Artificial Intelligence is perhaps unique among engineering subjects in that it has raised very basic questions about the nature of computing, perception, reasoning, learning, language, action, interaction, consciousness, humankind, life etc. etc. – and at the same time it has contributed substantially to answering these questions. There is thus a substantial tradition of work, both on AI by philosophers and of theory within AI itself. - The volume contains papers by Bostrom, Dreyfus, Gomila, O'Regan and Shagrir

Dieser Aufsatz ist eine kritische und erkundende Diskussion von Plantingas Behauptung, daß bestimmte Aussagen, aus denen evidentermaßen folgt, daß Gott existiert, berechtigterweise basal sein könnten. Im kritischen Abschnitt argumentiere ich dafür, daß es Plantinga nicht gelingt zu zeigen, daß das Kriterium des modernen Fundamentalisten für berechtigte Basalität, dem zufolge solche Aussagen nicht berechtigterweise basal sein können, selbstreferentiell inkohärent oder anderweitig mangelhaft ist. Im erkundenden Abschnitt versuche ich, ein Argument für die Auffassung zu entwickeln, daß solche Aussagen, selbst wenn sie berechtigterweise basal sein könnten, wenn überhaupt, nur selten berechtigterweise basal für intellektuell differenzierte erwachsene Theisten unserer Kultur wären.

In October 2011, the “2nd European Network for Cognitive Systems, Robotics and Interaction”, EUCogII, held its meeting in Groningen on “Autonomous activity in real-world environments”, organized by Tjeerd Andringa and myself. This is a brief personal report on why we thought autonomy in real-world environments is central for cognitive systems research and what I think I learned about it. --- The theses that crystallized are that a) autonomy is a relative property and a matter of degree, b) increasing autonomy of an artificial system from its makers and users is a necessary feature of increasingly intelligent systems that can deal with the real-world and c) more such autonomy means less control but at the same time improved interaction with the system

Wenn Präsident Kennedy nicht erschossen worden wäre, hätte er dann Nordvietnam bombardiert? Das weiß Gott allein. Oder doch nicht? Weiß wenigstens Er, was Kennedy getan hätte? ... Die Jesuiten behaupteten unter anderem, daß viele menschliche Handlungen in dem Sinne frei seien, daß die Ausführenden nicht logisch oder kausal gezwungen seien, sie auszuführen. („Frei“ wird im vorliegenden Aufsatz stets in diesem Sinne verwendet werden.) Wie behält Gott dann die Kontrolle über die menschliche Geschichte? Nicht dadurch, daß Er menschliche Handlungen kausal determiniert, wie die Dominikaner geglaubt zu haben scheinen , sondern indem Er Umstände herbeiführt, von denen Er weiß, daß wir in ihnen freiwillig Seinen Plänen entsprechend handeln werden.

Special Issue “Risks of artificial general intelligence”, Journal of Experimental and Theoretical Artificial Intelligence, 26/3 (2014), ed. Vincent C. Müller. http://www.tandfonline.com/toc/teta20/26/3# - Risks of general artificial intelligence, Vincent C. Müller, pages 297-301 - Autonomous technology and the greater human good - Steve Omohundro - pages 303-315 - - - The errors, insights and lessons of famous AI predictions – and what they mean for the future - Stuart Armstrong, Kaj Sotala & Seán S. Ó hÉigeartaigh - pages 317-342 - - - The path to more general artificial intelligence - Ted Goertzel - pages 343-354 - - - Limitations and risks of machine ethics - Miles Brundage - pages 355-372 - - - Utility function security in artificially intelligent agents - Roman V. Yampolskiy - pages 373-389 - - - GOLEM: towards an AGI meta-architecture enabling both goal preservation and radical self-improvement - Ben Goertzel - pages 391-403 - - - Universal empathy and ethical bias for artificial general intelligence - Alexey Potapov & Sergey Rodionov - pages 405-416 - - - Bounding the impact of AGI - András Kornai - pages 417-438 - - - Ethics of brain emulations - Anders Sandberg - pages 439-457

[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.

Two large lexicological projects for the Center for the Greek Language, Thessaloniki, were to be published in print and on the WWW, which meant that two conversions were needed: a near-database file had to be converted to fully formatted file for printing and a fully formatted file had to be converted to a database for WWW access. As it turned out, both conversions could make use of existing clues that indicated the kinds of information contained in each particular piece of text, thus separating fields from each other and ordering them into a tree-like structure. This indicates that both forms of the dictionaries, print and database, stem from the same cognitive need to categorize information into a kind of information before further understanding – be this for a human reader or for a machine.

This paper investigates the view that digital hypercomputing is a good reason for rejection or re-interpretation of the Church-Turing thesis. After suggestion that such re-interpretation is historically problematic and often involves attack on a straw man (the ‘maximality thesis’), it discusses proposals for digital hypercomputing with Zeno-machines , i.e. computing machines that compute an infinite number of computing steps in finite time, thus performing supertasks. It argues that effective computing with Zeno-machines falls into a dilemma: either they are specified such that they do not have output states, or they are specified such that they do have output states, but involve contradiction. Repairs though non-effective methods or special rules for semi-decidable problems are sought, but not found. The paper concludes that hypercomputing supertasks are impossible in the actual world and thus no reason for rejection of the Church-Turing thesis in its traditional interpretation.