Vincent C. Müller

The central concept of this edited volume is "blended cognition", the natural skill of human beings for combining constantly different heuristics during their several task-solving activities. Something that was sometimes observed like a problem as “bad reasoning”, is now the central key for the understanding of the richness, adaptability and creativity of human cognition. The topic of this book connects in a significant way with the disciplines of psychology, neurology, anthropology, philosophy, logics, engineering, logics, and AI. In a nutshell: understanding better humans for designing better machines. It contains a Preface by the editors and 12 chapters.

Artificial intelligence (AI) and robotics are digital technologies that will have significant impact on the development of humanity in the near future. They have raised fundamental questions about what we should do with these systems, what the systems themselves should do, what risks they involve, and how we can control these. - After the Introduction to the field (§1), the main themes (§2) of this article are: Ethical issues that arise with AI systems as objects, i.e., tools made and used by humans. This includes issues of privacy (§2.1) and manipulation (§2.2), opacity (§2.3) and bias (§2.4), human-robot interaction (§2.5), employment (§2.6), and the effects of autonomy (§2.7). Then AI systems as subjects, i.e., ethics for the AI systems themselves in machine ethics (§2.8) and artificial moral agency (§2.9). Finally, the problem of a possible future AI superintelligence leading to a “singularity” (§2.10). We close with a remark on the vision of AI (§3). - For each section within these themes, we provide a general explanation of the ethical issues, outline existing positions and arguments, then analyse how these play out with current technologies and finally, what policy consequences may be drawn.

Die Entwicklungen in der Künstlichen Intelligenz (KI) sind spannend. Aber wohin geht die Reise? Ich stelle eine Analyse vor, der zufolge exponentielles Wachstum von Rechengeschwindigkeit und Daten die entscheidenden Faktoren im bisherigen Fortschritt waren. Im Folgenden erläutere ich, unter welchen Annahmen dieses Wachstum auch weiterhin Fortschritt ermöglichen wird: 1) Intelligenz ist eindimensional und messbar, 2) Kognitionswissenschaft wird für KI nicht benötigt, 3) Berechnung (computation) ist hinreichend für Kognition, 4) Gegenwärtige Techniken und Architektur sind ausreichend skalierbar, 5) Technological Readiness Levels (TRL) erweisen sich als machbar. Diese Annahmen werden sich als dubios erweisen.

This book reports on the results of the third edition of the premier conference in the field of philosophy of artificial intelligence, PT-AI 2017, held on November 4 - 5, 2017 at the University of Leeds, UK. It covers: advanced knowledge on key AI concepts, including complexity, computation, creativity, embodiment, representation and superintelligence; cutting-edge ethical issues, such as the AI impact on human dignity and society, responsibilities and rights of machines, as well as AI threats to humanity and AI safety; and cutting-edge developments in techniques to achieve AI, including machine learning, neural networks, dynamical systems. The book also discusses important applications of AI, including big data analytics, expert systems, cognitive architectures, and robotics. It offers a timely, yet very comprehensive snapshot of what is going on in the field of AI, especially at the interfaces between philosophy, cognitive science, ethics and computing.

While it is often said that robotics should aspire to reproducible and measurable results that allow benchmarking, I argue that a focus on benchmarking can be a hindrance for progress in robotics. The reason is what I call the ‘measure-target confusion’, the confusion between a measure of progress and the target of progress. Progress on a benchmark (the measure) is not identical to scientific or technological progress (the target). In the past, several academic disciplines have been led into pursuing only reproducible and measurable ‘scientific’ results – robotics should be careful to follow that line because results that can be benchmarked must be specific and context-dependent, but robotics targets whole complex systems for a broad variety of contexts. While it is extremely valuable to improve benchmarks to reduce the distance be- tween measure and target, the general problem to measure progress towards more intelligent machines (the target) will not be solved by benchmarks alone; we need a balanced approach with sophisticated benchmarks, plus real-life testing, plus qualitative judgment.

The contribution of the body to cognition and control in natural and artificial agents is increasingly described as “off-loading computation from the brain to the body”, where the body is said to perform “morphological computation”. Our investigation of four characteristic cases of morphological computation in animals and robots shows that the ‘off-loading’ perspective is misleading. Actually, the contribution of body morphology to cognition and control is rarely computational, in any useful sense of the word. We thus distinguish (1) morphology that facilitates control, (2) morphology that facilitates perception and the rare cases of (3) morphological computation proper, such as ‘reservoir computing.’ where the body is actually used for computation. This result contributes to the understanding of the relation between embodiment and computation: The question for robot design and cognitive science is not whether computation is offloaded to the body, but to what extent the body facilitates cognition and control – how it contributes to the overall ‘orchestration’ of intelligent behaviour.

The European Association for Cognitive Systems is the association resulting from the EUCog network, which has been active since 2006. It has ca. 1000 members and is currently chaired by Vincent C. Müller. We ran our annual conference on December 08-09 2016, kindly hosted by the Technical University of Vienna with Markus Vincze as local chair. The invited speakers were David Vernon and Paul F.M.J. Verschure. Out of the 49 submissions for the meeting, we accepted 18 a papers and 25 as posters (after double-blind reviewing). Papers are published here as “full papers” or “short papers” while posters are published here as “short papers” or “abstracts”. Some of the papers presented at the conference will be published in a separate special volume on ‘Cognitive Robot Architectures’ with the journal Cognitive Systems Research. - RC, VCM, YS, MV.

The background to this paper is that in our world of massively increasing personal digital data any control over the data about me seems illusionary – informational privacy seems a lost cause. On the other hand, the production of this digital data seems a necessary component of our present life in the industrialized world. A framework for a resolution of this apparent dilemma is provided if by the distinction between (meaningless) data and (meaningful) information. I argue that computational data processing is necessary for many present-day processes and not a breach of privacy, while collection and processing of private information is often not necessary and a breach of privacy. The problem and the sketch of its solution are illustrated in a case-study: supermarket customer cards.

Lethal Autonomous Weapon Systems are here. Technological development will see them become widespread in the near future. This is in a matter of years rather than decades. When the UN Convention on Certain Conventional Weapons meets on 10-14th November 2014, well-considered guidance for a decision on the general policy direction for LAWS is clearly needed. While there is widespread opposition to LAWS—or ‘killer robots’, as they are popularly called—and a growing campaign advocates banning them outright, we argue the opposite. LAWS may very well reduce suffering and death in war. Rather than banning them, they should be regulated, to ensure both compliance with international humanitarian law, and that this positive outcome occurs. This policy memo sets out the basic structure and content of the regulation required

Proceedings of the papers presented at the Symposium on "Revisiting Turing and his Test: Comprehensiveness, Qualia, and the Real World" at the 2012 AISB and IACAP Symposium that was held in the Turing year 2012, 2–6 July at the University of Birmingham, UK. Ten papers. - http://www.pt-ai.org/turing-test --- Daniel Devatman Hromada: From Taxonomy of Turing Test-Consistent Scenarios Towards Attribution of Legal Status to Meta-modular Artificial Autonomous Agents - Michael Zillich: My Robot is Smarter than Your Robot: On the Need for a Total Turing Test for Robots - Adam Linson, Chris Dobbyn and Robin Laney: Interactive Intelligence: Behaviour-based AI, Musical HCI and the Turing Test - Javier Insa, Jose Hernandez-Orallo, Sergio España - David Dowe and M.Victoria Hernandez-Lloreda: The anYnt Project Intelligence Test (Demo) - Jose Hernandez-Orallo, Javier Insa, David Dowe and Bill Hibbard: Turing Machines and Recursive Turing Tests — Francesco Bianchini and Domenica Bruni: What Language for Turing Test in the Age of Qualia? - Paul Schweizer: Could there be a Turing Test for Qualia? - Antonio Chella and Riccardo Manzotti: Jazz and Machine Consciousness: Towards a New Turing Test - William York and Jerry Swan: Taking Turing Seriously (But Not Literally) - Hajo Greif: Laws of Form and the Force of Function: Variations on the Turing Test.

Hilary Putnams Biographie und philosophische Entwicklung spiegeln die Geschichte der angelsächsischen Philosophie in den letzten 40 Jahren. Beinahe ebenso lange hat Putnam diese Geschichte wesentlich beeinflußt und so kann John Passmore über Putnam schreiben: «Er ist die Geschichte der gegenwärtigen Philosophie im Umriß»1. In der vorliegenden Einleitung soll vor allem der Kontext dargestellt werden, in dem Putnam steht und aus dem heraus verständlich wird, was er philosophisch zu sagen hat. Dieser Kontext ist sicherlich ein Grund dafür, daß Putnam hierzulande noch relativ wenig bekannt ist, während er in den USA häufig für den bedeutendsten aktiven Philosophen gehalten wird. Im Rahmen einer Skizze von Putnams philosophischer Entwicklung soll zudem eine vorläufige philosophiehistorische Einordnung versucht werden, auch wenn hier nicht der Ort für eine umfassende Kritik oder Darstellung sein kann: Die Einleitung muß auf recht elementarem Niveau bleiben und kann eine Lektüre der Texte natürlich nicht ersetzen. Da Putnams Werk sicherlich Teil einer Annäherung von ‹analytischer› und ‹kontinentaler› Philosophie ist, soll bei der Einführung in die hier übersetzten Texte schließlich deutlich werden, was Putnam nicht analytisch orientierten Lesern zu bieten hat.

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 -.

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;.

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.

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).

The declared goal of this paper is to fill this gap: “... cognitive systems research needs questions or challenges that define progress. The challenges are not (yet more) predictions of the future, but a guideline to what are the aims and what would constitute progress.” – the quotation being from the project description of EUCogII, the project for the European Network for Cognitive Systems within which this formulation of the ‘challenges’ was originally developed (http://www.eucognition.org). So, we stick out our neck and formulate the challenges for artificial cognitive systems. These challenges are articulated in terms of a definition of what a cognitive system is: a system that learns from experience and uses its acquired knowledge (both declarative and practical) in a flexible manner to achieve its own goals.

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

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.

This is the editorial for a special volume of JETAI, featuring papers by Omohundro, Armstrong/Sotala/O’Heigeartaigh, T Goertzel, Brundage, Yampolskiy, B. Goertzel, Potapov/Rodinov, Kornai and Sandberg. - If the general intelligence of artificial systems were to surpass that of humans significantly, this would constitute a significant risk for humanity – so even if we estimate the probability of this event to be fairly low, it is necessary to think about it now. We need to estimate what progress we can expect, what the impact of superintelligent machines might be, how we might design safe and controllable systems, and whether there are directions of research that should best be avoided or strengthened.

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