Alan Turing

Was ist es, was eine Maschine, einen Computer oder einen
Menschen überhaupt intelligent macht? Diese Frage ist weitaus schwerer zu beantworten, als man zunächst erwarten würde. Man kann hier etwa auf die Fähigkeit des Denkens oder auf eine bestimmte Art des Handelns abstellen. Der Ansatz, dass sich Künstliche Intelligenz daran festmachen ließe, ob eine Maschine den gleichen Output wie ein Mensch nachahmen kann, ist seit den Anfangstagen der Fachdisziplin der Künstlichen Intelligenz bis heute stark verbreitet. Doch ebenso lange wird auch darüber diskutiert, ob damit der Wesensbereich menschlicher Intelligenz
überhaupt erfasst wird. Seit den 50er Jahren wird darüber
debattiert, ob die Simulation eines intelligenten Outputs ausreichend
sein kann für die Frage, ob ein System intelligent ist oder nicht
und ob zur menschlichen Intelligenz nicht gerade etwas hinzuzuzählen
ist, das über einen entsprechenden Abgleich von Outputs gar nicht zu
erfassen ist. Mit dieser Kritik an der Verifikationsmethode ist eine Kritik
an der Idee, dass Maschinen prinzipiell das Niveau menschlicher Intelligenz überhaupt erreichen könnten, eng verbunden. Die Idee, dass
dies prinzipiell erreichbar ist, wird einem Vorschlag von John Searle
folgend auch als starke KI-These bezeichnet, während die Kritiker nur
einer schwachen KI-These zustimmen können, wonach artifizielle Systeme lediglich Teilaspekte menschlicher Intelligenz erfolgreich simulieren können, aber eben nie im vollen Umfang als intelligent zu bezeichnen wären.
Zwei Kritikpunkte an der Vorstellung einer starken KI sind bis heute extrem wirkmächtig:
1.: Künstliche Intelligenz könne niemals ‚wirklich‘ intelligent sein,
weil das selbstbewusste ‚Ich‘ fehle, an dem nicht nur das Denken i.e.S.,
sondern wahlweise auch Intentionalität, Emotionen, phänomenale Bewusstseinszustände, freier Wille, Intuition und Ähnliches mehr hingen.
2.: Künstlicher Intelligenz fehle es an einer Verkörperung und
menschlichen Sozialisation, sie sei nicht eingebettet in eine Welt, in der
sie lernen und mit der sie reziprok und kontinuierlich in Verbindung
steht, was aber konstitutiv für die menschliche Art von Intelligenz sei.
Diese Art der Kritik und der Gegenentwurf von Befürwortern der
starken KI-These zeigen, dass die philosophische Debatte
um Künstliche Intelligenz untrennbar mit den ganz zentralen Fragen
der Philosophie des Geistes der letzten Jahrhunderte verbunden ist. Die
KI-Debatte wirft Fragen auf, deren Antworten von den Grundpositionen
abhängen, die in ihr eingenommen werden. Drei große kartographieren das Feld: Die erste Frage lautet, was das Selbst eigentlich ist, das sich in unserem Geist seiner selbst bewusst wird: Ist es eine Seele, also eine vom Körper zu trennende Substanz, oder handelt es sich um ein stark emergentes Phänomen, das jenseits physikalischer Gesetzmäßigkeiten aus dem Zusammenspiel unseres Gehirns entsteht oder aber ist es schlicht ein besonders kluger Trick der Evolution, der im Rahmen darwinistischer Prozesse entstanden und in keiner Weise mysteriös ist, sondern auch physikalisch erklärt werden kann. Die zweite ist die metaphysische Frage nach unserer Realität, ob das Sein also monistisch oder dualistisch zu verstehen ist, ob es letztlich aus den physikalischen Elementarteilchen und den zwischen ihnen wirkenden Kräften besteht, ober ob im Falle des menschlichen Geistes etwas Spirituelles hinzukommt. Und die dritte schließlich ist die anthropologische Frage nach dem, was der Mensch ist: Ist er etwas Herausgestelltes und Besonderes, das etwa kraft seiner Vernunft allem anderen Leben enthoben ist, oder ist er ein evolutionär besonders weit entwickeltes Tier oder aber ist er letztlich auch nur eine Maschine? Je nach Position zu diesen drei Fragen ergibt sich ein anderer Raum von Optionen, wie die starke KI-These zu beurteilen ist.

Among his various productive contributions, Alan Turing has imagined to turn the question “can machines think?” into what he called an Imitation game, with specific rules and play conditions. Reusing the notion of dynamic continuum from ludus to paidia, as introduced by Roger Caillois in his famous study Man, Play and Games, we claim, with most computer scientists, that the Turing Imitation game is strongly ludus-tagged, mostly because it is not attractive and playful enough to be spontaneously played: the contrast is strong, compared to some later paidia-tagged game involving computing machineries, like Interactive information and digital content browsing and retrieval. As far as designing our interactive Artificial Intelligence systems is concerned, why should we have to choose between ludus and paidia or to deny their eternal competition? On the contrary, this paper proposes to dare to establish that irreducible concurrency between ludus and paidia as the heart of our future systems, rediscovering the importance of the Greek notion of kairos.

In recent years, public engagement in museums is increasingly being influenced by the paradigm of "citizen science", that is, active participation in research teams by members of the general public with no formal training in the field of research concerned. This paper provides an overview of citizen science approaches which museums can deploy using online platforms, digital tools and apps. It also aims to highlight challenges and innovations, as well as possible opportunities for cultural organisations to include public participation in research and knowledge creation. Alan Turing. Citizen science. Crowdsourcing. Museums. Public engagement. Public research.

Resumo Frente a cada computador, tablet ou celular vemos nosso reflexo opaco numa tela preta. A tecnologia, a técnica moderna, se faz presente em cada parte do nosso cotidiano. O humano interage com a máquina, mas a pergunta contrária se faz válida-e tenta ser respondida pela ficção. O presente artigo tem como objetivo analisar a relação do ser humano com a inteligência artificial através do episódio " Be Right Back " , da série televisiva de cunho distópicoBlack Mirror, exibida atualmente pelo Netflix. A série tem o objetivo de apresentar e discutir resultados de excessos da tecnologia no cotidiano dos humanos, ainda que apresentado como sendo num futuro, porém possível. O episódio em questão trabalha o relacionamento entre o ser humano e a inteligência artificial num modo de substituir um outro e suprir seus papéis. Serão contrastados os pensamentos de Martin Heidegger sobre o dasein e a natureza humana e estudos derivados com a perspectiva de Alan Turing sobre Inteligência Artificial e humanidade, com o objetivo de discorrer brevemente as perspectivas acerca do pós-humanismo e transhumanismo, bem como suas implicações sociais; adentrar na questão do que é o ser; e discutir a alteridade e sua presença numa inteligência artificial. Assim, pergunta-se, nesse artigo, como é possível entender a alteridade encontrada entre Martha, a protagonista do episódio, e uma Inteligência Artificial que é criada com a função de substituir seu falecido noivo, Ash. Para esse estudo, partiremos de certos pressupostos a respeito do que é o ser e sobre a questão da técnica na concepção heideggeriana de dasein e na visão da técnica como um modo de ser vigente na pós-modernidade.

Al igual que Wittgenstein hace en sus Observaciones de la Rama Dorada de Zattell yo observo la "Maquinaria computacional e Inteligencia De Alan Turing (1950)" y trabajo a partir de este la cuestión del pensar con respecto a las maquinas y la pregunta de Turing sobre si las maquinas piensan

Artificial intelligence (AI) research now strongly focuses on special purpose "narrow AI". Artificial general intelligence (AGI) research has stalled. One suggested reason is that current concepts used to understand general intelligence are inadequate and new ones are needed. But AGI has two subjects: (1) general intelligence, (2) the digital computer. AI including AGI accepts Turing's concept of the electronic device as a practical version of his abstract Turing machine design. I show why this account is inadequate for understanding the intrinsic machine, as AGI must, and conclude that to progress, AGI must abandon Turing. Further, I show that if Searle's Chinese room argument is correct, this means only that Turing's conception of the computer does not allow semantic content. It doesn't mean computers will never think. There are other conceptions. The CRA fails to address whether any of these are both true to the hardware and allow semantic content, and one of them may.

Cellular automata are models that deal with both nature and artefacts: they can indeed simulate living beings as well as be employed in the creation of objects. After the introduction of this concept by Stanislaw Ulam and John Von Neumann in the late 1940s, many different kinds of cellular automata have been created and have become part of what Christopher Langton called " artificial life " in 1986. The most complex examples among them are based on stochastic development, thus they share their structural properties with morphogenetic models like the one suggested by Alan Turing (1952). This is the reason why some cellular automata are capable of simulating the development of living beings , but also of cities and artefacts. They are indeed widely used in computer graphics related to parametric design, in order to create performative objects at various scales that can be produced according to the principle of mass customisation. The purpose of this study is to analyse the properties of these models with the help of computer simulations and, as a consequence, to explore some of their different fields of application. As a result, it can be observed that these processes , based on a stochastic geometry, can lead not only to simple biomimicry (regarded as the artificial replication of biological features) but also, in a wider sense, to bioinspiration (a more general relation between nature and artefacts based on shared structural properties).

Masterthesis. An universal Turing-Maschine has several interesting properties: It is (a) deterministic, (b) programmable, (c) self-changing, (d) very extensible and (e) it can be build as a mechanical aparatus. Is that enough to develop intelligent behavior? To properly understand this question, this masterthesis (1) reconstructs the developement of the concept of the Turing-Machine against the background of the history of mathematics and its philosophical implications and (2) follows Alan M. Turings thoughts about the de-limitation of  actual versions of Turing-Machines. It is explored which limits of his machines Turing did see and if any of these limits are supposed to be neccesary (in the sense of: not historically contingent).  As a result the starting question can be rephrased: "Is there something that we should attribute to a human beeing, but that we cannot attribute to a Turing-Machine?".
An introduction sums up the discourse about the relevance of the Turing-Test for the history of philosophy, especially in Germany. Chapter 5 collects some open questions about (a) the possible range of variation of embodiment of a Turing-Machine, (b) the relevance of Turings biography for Turings work and (c) the relevance of poetic narratives (like science fiction) for the developement of state-of-the-art technology.
In Chapters 6 an annotated history of Turing-Editions (and german translations) and scientific anthologies about the Turing-Test is given. Chaper 7 contains a useful bibliography.

‘Virtual Ethics’, was written at the behest of Jenny Chapman at the BBC, who wanted an introduction to an ethics for immersive technology. Since there is little of such yet, I have started much from scratch. The essay is general, and is written for those who need of tools for ethical deliberation regarding new technology.
Yet, the essay, among other things, also attempts a liberal expansion of the set of objects for moral concern.

I thank Chris Bobonich for reading.

How does our brain give rise to the rich world of our conscious experience?  Each lecture in this course approaches this fundamental philosophical question by focusing on a specific issue regarding thinking, minds, and brains.  Topics include little-known facts about consciousness, what it is like to be a bat, the 'inner theater' view of consciousness, Charles Babbage's steam-driven computing engines, and how optical illusions work.  Philosophical theories of mind are at the core of the course, from Plato and Aristotle through Descartes and Locke to contemporary work by Daniel Dennett, David Chalmers, and Paul and Patricia Smith Churchland.  In addition, the course draws from psychology, neurophysiology, linguistics, and the amazing history of attempts at building thinking machines.

Alan Turing has a rightful claim to the title of father of modern computing. He laid the theoretical groundwork for a universal machine that models a computer in its most general form before World War II. During the war, Turing was instrumental in developing and influencing actual computing devices that have been said to have shortened the war by up to two years by decoding encrypted enemy messages that were believed by others to be unbreakable. Unlike some theoreticians, he was willing to be involved with practical aspects, and was as happy to wield a soldering iron as he was to wrestle with a mathematical problem, normally from a unique angle compared to others.

La Filosofia e l'Intelligenza Artificiale sono due discipline che, nel corso del tempo, hanno interagito e si sono impegnate in un dialogo fruttuoso: è innegabile, ad esempio, che l'IA abbia plasmato il modo in cui i filosofi concepiscono la mente umana e, viceversa, le diverse concezioni della mente hanno avuto un impatto in merito alla ricerca nel campo dell'IA. Siffatte interazioni hanno avuto luogo in quanto gli obiettivi che l'IA si pone l'hanno resa una disciplina di notevole interesse per molti filosofi.

A tal proposito, in quest'elaborato verranno analizzati due esperimenti mentali molto famosi, cioè il "Turing Test" ed il "Chinese Room Argument", formulati rispettivamente da Alan Turing e John R. Searle. Entrambe queste prove mirano a rispondere, in maniera più o meno diretta, all'interrogativo "Le macchine possono pensare?": Turing afferma di essere molto fiducioso, mentre Searle si dichiara assai scettico a riguardo.

Tale domanda non è ovviamente stata dibattuta solo da Turing e Searle, poiché ha dato vita ad una smisurata molteplicità di rivoli interpretativi: esistono infatti approcci anche radicalmente differenti alla disciplina dell'IA. Tramite questo paper non si ambisce ad una trattazione approfondita e rigorosa della domanda poc'anzi citata e neppure di tutti gli interrogativi suscitati dai testi presi in esame. Purtuttavia, l'elaborato mira a fornire alcuni spunti di riflessione limitatamente ad alcuni aspetti relativi all'intelligenza artificiale e alle implicazioni più immediate dei due esperimenti mentali che son stati esaminati.

First Paragraph: I live just off of Bell Road outside of Newburgh, Indiana, a small town of 3,000 people. A mile down the street Bell Road intersects with Telephone Road not as a modern reminder of a technology belonging to bygone days, but as testimony that this technology, now more than a century and a quarter old, is still with us. In an age that prides itself on its digital devices and in which the computer now equals the telephone as a medium of communication, it is easy to forget the debt we owe to an era that industrialized the flow of information, that the light bulb, to pick a singular example, which is useful for upgrading visual information we might otherwise overlook, nonetheless remains the most prevalent of all modern day information technologies. Edison’s light bulb, of course, belongs to a different order of informational devices than the computer, but not so the telephone, not entirely anyway.

In this short paper I tried to develop the importance of Alan Mathison Turing (1912--1954) as one of a few mathematicians in the process of breaking the Enigma cipher at Bletchley Park (the British WWII sigint centre, known within SIS as Station X), popularly known as 'Top Secret Ultra', of which it is said that it has shortened the war in Europe by some two years. For this purpose I sifted through different articles and books. At first I trace the prehistory of the activities at Bletchley Park. But I'm not going to try to explain the Enigma system (its technical specification), including its use in detail, for this has been done already sufficiently. Then Turings history at Bletchley Park is briefly shown.

Alan Mathison Turing (1912-1954) può essere definito un transumanista ante litteram. Solitamente si fa riferimento alla sua opera per focalizzare lo stadio iniziale del paradigma della mente artificiale, ma non sempre vengono sottolineati tre ulteriori punti che caratterizzano il suo pensiero: 1) la sua etica fortemente "transumanista" 2) la sua propensione nell'effettuare scommesse futurologiche-un connotato anch'esso transumanista 3) il fatto di avere tentato egli stesso di "violare" i vincoli computazionali della Turing machine al fine di raggiungere una "computazione" simile a quella "messa in atto" dalle specie viventi.

Dissertazione di laurea triennale che ha come obiettivo di presentare la genesi del pensiero sull'intelligenza artificiale a partire dalle intuizioni di Leibniz fino alle applicazioni contemporanee nella robotica.
Ci si è soffermati su i due punti di vista fondamentali di questo ambito di ricerca, ovvero il Test di Turing e la sua critica portata avanti da Searle. Infine si è proposta una "terza via", a partire dalle riflessioni di Giuseppe O. Longo, in cui si rilegge in chiave monista la teoria dell'intelligenza artificiale e confronta con le nuove intelligenze robotiche.

Bu makalede karar verme problemini ortaya çıkaran süreç tarihsel olarak incelenmiştir. Matematiği mantık çerçevesinde sağlam temellere oturtma çabaları sistemin kendine referans (self referans) olarak verilmesi durumunda çıkmaza girmiştir. Tarihsel olarak bakıldığında benzer çıkmazların mevcut olduğu görülecektir. Eublides’in önermesi, Russell’ın paradoksu, Gödel’in eksiklik teorimi ve Turing’in durma probleminin ortaya serdiği çıkmazların kök nedeninde sistemin kendine referans vermesi yatmaktadır. Hatta Wittgenstein’in iki döneminin bulunmasının sebebi de benzerdir. İlk dönemde ortaya koyduklarını kendi teorisi içinden çıkaramaması nedeniyle terk etmek zorunda kalmıştır. Bu çıkmazla karşılaşanlar, çözüm olarak ya sistemin bu istisna dışında çalışıyor olmasını yeterli görerek sistemi kullanamaya devam etmişler ya da kurallar konulurken tipler kuramı gibi ek aksiyomlar eklenerek sistemin kendine referans vermesi baştan engellenmeye çalışmışlardır. Yine de kendine referans durumu, sistemleri içinde hiçbir boşluk bırakmak istemeyenler için dev bir engel olarak durmaktadır.

"One should resist the temptation to proclaim the prospect of a wired brain an illusion, something that we are still far from and that cannot really be actualized: such a view is itself an escape from the threat, from the fact that something new and unheard-of is effectively emerging. Even if it will be realized in a much more modest way than today's grandiose visions of Singularity, everything will change with it. But how will things change? It is here that Jan De Vos points to the role of the mainstream psy-sciences and their simple, cardboard psychological models informing the design of our avatars and 'smart environments'. Are we doomed or is there a prospect for a more emancipatory digital technology? Jan de Vos approaches this question, carefully avoiding the fascination by New

Avvisiamo il lettore che questo articolo è un'apologia della macchina, o meglio, del sistema di macchine. Nella società futura sarà certo possibile per chi lo vorrà, ritornare a vivere come un neandertaliano al tempo del comunismo primitivo, ma i caratteri sociali prevalenti saranno quelli ad alta densità tecnologica. La disumana tecnologia visibile di oggi sarà sostituita da un metabolismo umano regolato da sensori e attuatori invisibili. Il ricorso ad un minimo di apparecchiature sarà il risultato di un massimo livello delle loro qualità intrinseche. Eppure c'è ancora qualcuno che scambia l'aumento della forza produttiva sociale con l'aumento della produzione. La società futura dimenticherà felicemente l'epoca del quantitativismo produttivo e tenderà a mettere in armonia l'energia dissipata con quella che ci regala il Sole.

In 1950, Turing proposed to answer the question “can machines think” by staging an “imitation game” where a hidden computer attempts to mislead a human interrogator into believing it is human. While the cybercrime of bots defrauding people by posing as Nigerian princes and lascivious e-girls indicates humans have been losing the Turing test for some time, this paper focuses on “deepfakes,” artificial neural nets generating realistic audio-visual simulations of public figures, as a variation on the imitation game. Deepfakes blur the lines between fact and fiction, making it possible for the mere fiction of a nuclear apocalypse to make itself real. Seeing oneself becoming another, doing and saying strange things as if demonically possessed, triggers a disillusionment of our sense of self as human cloning and sinister doppelgängers become a reality that’s open-source and free. Along with electronic club music, illicit drugs, movies like Ex Machina and the coming sex robots, the primari...

This paper makes no apology for its reading like a collection of book reports. It draws mainly on the reminiscences of Sara and John Turing, Alan Turing’s mother and elder brother respectively, as well as from Andrew Hodges’ extensive research on the man, his work and his impact gathered for the definitive Alan Turing biography. Alan Turing was a complex, talented man bereft of one stable and loyal companion throughout his life. He was the boy who explained Einstein’s Theory of Relativity aged 15½ for his mother and the tormented outcast who gave us the modern world (Sunday Times, 2011).

Based on Shah's PhD 'Deception-detection and Machine Intelligence in Practical Turing tests' and follow up experiments, the book introduces and explores Turing's Imitation Game (Turing Test,) which gave rise to the science of artificial intelligence. Involving an interrogator conversing with hidden identities, one human and one machine, the test strikes at the heart of any questions about the capacity of machines to behave as humans. The book offers an up-to-date assessment of Turing's Imitation Game, its history, context and implications, all illustrated with practical Turing tests. The contemporary relevance of this topic and the strong emphasis on example transcripts makes this book an ideal companion for undergraduate courses in artificial intelligence, engineering, psychology, linguistics, philosophy and more. Available from Cambridge University Press:

Turing was a philosopher of logic and mathematics, as well as a mathematician. His work throughout his life owed much to the Cambridge milieu in which he was educated and to which he returned throughout his life. A rich and distinctive tradition discussing how the notion of " common sense " relates to the foundations of logic was being developed during Turing's undergraduate days, most intensively by Wittgenstein, whose exchanges with Russell, Ramsey,Sraffa, Hardy, Littlewood and others formed part of the backdrop which shaped Turing’s work. Beginning with a Moral Sciences Club talk in 1933, Turing developed an “anthropological” approach to the foundations of logic, influenced by Wittgenstein, in which “common sense” plays a foundational role. This may be seen not only in “On Computable Numbers” (1936/7) and Turing’s dissertation (written 1938, see (1939)), but in his exchanges with Wittgenstein in 1939 and in two later papers, “The Reform of Mathematical Phraseology and Notation” (1944/5) and “Solvable and Unsolvable Problems” (1954).

THE CHURCH-TURING THESIS (CTT) underlies tantalizing open questions concerning the fundamental place of computing in the physical universe. For example, is every physical system computable? Is the universe essentially computational in nature? What are the implications for computer science of recent speculation about physical uncomputability? Does CTT place a fundamental logical limit on what can be computed, a computational "barrier" that cannot be broken, no matter how far and in what multitude of ways computers develop? Or could new types of hardware, based perhaps on quantum or relativistic phenomena, lead to radically new computing paradigms that do breach the Church-Turing barrier, in which the uncomputable becomes computable , in an upgraded sense of "com-putable"? Before addressing these questions , we first look back to the 1930s to consider how Alonzo Church and Alan Turing formulated, and sought to justify , their versions of CTT. With this necessary history under our belts, we then turn to today's dramatically more powerful versions of CTT.