For an artificial agent to be morally praiseworthy, its rules for behaviour and the mechanisms for supplying those rules must not be supplied entirely by external humans. Such systems are a substantial departure from current technologies and theory, and are a low prospect. With foreseeable technologies, an artificial agent will carry zero responsibility for its behavior and humans will retain full responsibility.

Steven Pinker's How the mind works (HTMW) marks in my opinion an historic point in the history of humankind's attempt to understand itself. Socrates delivered his "know thyself" imperative rather long ago, and now, finally, in this behemoth of a book, published at the dawn of a new millennium, Pinker steps up to have psychology tell us what we are: computers crafted by evolution - end of story; mystery solved; and the poor philosophers, having never managed to obey Socrates' command, (...) are left alone to wander in the labyrinth of their benighted speculation forever. Unfortunately, though HTMW is to this point the crowning attempt of psychology to make systematic sense of persons by integrating everything relevant science knows, the book fails - and it fails so fundamentally and irremediably that we would do well to wonder anew whether we should supplant the basic view it promotes with what I call the super-mind hypothesis: the view that though mere animals are evolved computers, persons are more. (shrink)

This paper provides a survey of philosophical discussion of the "the Turing Test". In particular, it provides a very careful and thorough discussion of the famous 1950 paper that was published in Mind.

Many women wrote philosophy in nineteenth-century Britain, and they wrote across the full range of philosophical topics. Yet these important women thinkers have been left out of the philosophical canon and many of them are barely known today. The aim of this book is to put them back on the map. It introduces twelve women philosophers - Mary Shepherd, Harriet Martineau, Ada Lovelace, George Eliot, Frances Power Cobbe, Helena Blavatsky, Julia Wedgwood, Victoria Welby, Arabella Buckley, Annie Besant, Vernon Lee, and (...) Constance Naden. Alison Stone looks at their views on naturalism, philosophy of mind, evolution, morality and religion, and progress in history. She shows how these women interacted and developed their philosophical views in conversation with one another, not only with their male contemporaries. The rich print and periodical culture of the period enabled these women to publish philosophy in forms accessible to a general readership, despite the restrictions women faced, such as having limited or no access to university education. Stone explains how these women became excluded from the history of philosophy because there was a cultural shift at the end of the nineteenth century towards specialised forms of philosophical writing, which depended on academic credentials that were still largely unavailable to women. (shrink)

The Turing test has been studied and run as a controlled experiment and found to be underspecified and poorly designed. On the other hand, it has been defended and still attracts interest as a test for true artificial intelligence (AI). Scientists and philosophers regret the test’s current status, acknowledging that the situation is at odds with the intellectual standards of Turing’s works. This article refers to this as the Turing Test Dilemma, following the observation that the test has been under (...) discussion for over seventy years and still is widely seen as either too bad or too good to be a valuable experiment for AI. An argument that solves the dilemma is presented, which relies on reconstructing the Turing test as a thought experiment in the modern scientific tradition. It is argued that Turing’s exposition of the imitation game satisfies Mach’s characterization of the basic method of thought experiments and that Turing’s uses of his test satisfy Popper’s conception of the critical and heuristic uses of thought experiments and Kuhn’s association of thought experiments to conceptual change. It is emphasized how Turing methodically varied the imitation game design to address specific challenges posed to him by other thinkers and how his test illustrates a property of the phenomenon of intelligence and suggests a hypothesis on machine learning. This reconstruction of the Turing test provides a rapprochement to the conflicting views on its value in the literature. (shrink)

Alan Turing’s 1950 imitation game has been widely understood as a means for testing if an entity is intelligent. Following a series of papers by Diane Proudfoot, I offer a socio-technological interpretation of Turing’s paper and present an alternative way of understanding both the imitation game and Turing’s concept of intelligence. Turing, I claim, saw intelligence as a social concept, meaning that possession of intelligence is a property determined by society’s attitude toward the entity. He realized that as long as (...) human society held a prejudiced attitude toward machinery—seeing machines a priori as mindless objects—machines could not be said to be intelligent, by definition. He also realized, though, that if humans’ a priori, chauvinistic attitude toward machinery changed, the existence of intelligent machines would become logically possible. Turing thought that such a change would eventually occur: He believed that when scientists overcome the technological challenge of constructing sophisticated machines that could imitate human verbal behavior—i.e., do well in the imitation game—humans’ prejudiced attitude toward machinery will have altered in such a way that machines could be said to be intelligent. The imitation game, for Turing, was not an intelligence test, but a technological aspiration whose realization would likely involve a change in society’s attitude toward machines. (shrink)

Since the 1980s, an immense wave of scholarship has recovered the voices of the many women who contributed to early modern philosophy, transforming our picture of the period. It is now typical for...

Disertační práce se zabývá problematikou připisování myšlení jiným entitám, a to pomocí imitační hry navržené v roce 1950 britským filosofem Alanem Turingem. Jeho kritérium, známé v dějinách filosofie jako Turingův test, je podrobeno detailní analýze. Práce popisuje nejen původní námitky samotného Turinga, ale především pozdější diskuse v druhé polovině 20. století. Největší pozornost je věnována těmto kritikám: Lucasova matematická námitka využívající Gödelovu větu o neúplnosti, Searlův argument čínského pokoje konstatující nedostatečnost syntaxe pro sémantiku, Blockův návrh na použití brutální síly pro (...) řešení imitační hry, Frenchova teorie subkognitivních informací a Michieho skepticismus ohledně možnosti umělého vědomí. Závěr práce zachycuje současný stav recepce Turingova testu a představuje pokusy o jeho praktickou realizaci, například v každoroční soutěži o Loebnerovu cenu. Autor práce zastává názor, že ani po více než šedesáti letech od uveřejnění Turingova paradigmatického eseje stále neexistují žádné vážné důvody pro zamítnutí jeho tvrzení. Tradiční komputační funkcionalismus možná není ideální teorií vysvětlující činnost myslí a jako slibnější se může jevit vývoj v neurálních vědách, ale Turingův test je přesto užitečným a snad i jediným nástrojem pro detekci inteligence u lidmi vytvořených strojů. (shrink)

Since Turing proposed the first test of intelligence, several modifications have been proposed with the aim of making Turing’s proposal more realistic and applicable in the search for artificial intelligence. In the modern context, it turns out that some of these definitions of intelligence and the corresponding tests merely measure computational power. Furthermore, in the framework of the original Turing test, for a system to prove itself to be intelligent, a certain amount of deceit is implicitly required which can have (...) serious security implications for future human societies. In this article, we propose a unified framework for developing intelligence tests which takes care of important ethical and practical issues. Our proposed framework has several important consequences. Firstly, it results in the suggestion that it is not possible to construct a single, context independent, intelligence test. Secondly, any measure of intelligence must have access to the process by which a problem is solved by the system under consideration and not merely the final solution. Finally, it requires an intelligent agent to be evolutionary in nature with the flexibility to explore new algorithms on its own. (shrink)

We argue that a command and control system can undermine a commander’s moral agency if it causes him/her to process information in a purely syntactic manner, or if it precludes him/her from ascertaining the truth of that information. Our case is based on the resemblance between a commander’s circumstances and the protagonist in Searle’s Chinese Room, together with a careful reading of Aristotle’s notions of ‘compulsory’ and ‘ignorance’. We further substantiate our case by considering the Vincennes Incident, when the crew (...) of a warship mistakenly shot down a civilian airliner. To support a combat commander’s moral agency, designers should strive for systems that help commanders and command teams to think and manipulate information at the level of meaning. ‘Down conversions’ of information from meaning to symbols must be adequately recovered by ‘up conversions’, and commanders must be able to check that their sensors are working and are being used correctly. Meanwhile ethicists should establish a mechanism that tracks the potential moral implications of choices in a system’s design and intended operation. Finally we highlight a gap in normative ethics, in that we have ways to deny moral agency, but not to affirm it. (shrink)

Both a traditional notion of free will, present in human beings, and artificial intelligence are often argued to be inherently incompatible with determinism. Contrary to these criticisms, this paper defends that an account of free will compatible with determinism, the responsibility strategy (coined here) specifically, is a variety of free will worth wanting as well as a variety that is possible to (in principle) artificially construct. First, freedom will be defined and related to ethics. With that in mind, the two (...) theses of free will are addressed (namely could have done otherwise and source origination) for both human beings and artificial agents. (shrink)

When Ken Malone investigates a case of something causing mental static across the United States, he is teleported to a world that doesn't exist.

The ethical concerns regarding the successful development of an Artificial Intelligence have received a lot of attention lately. The idea is that even if we have good reason to believe that it is very unlikely, the mere possibility of an AI causing extreme human suffering is important enough to warrant serious consideration. Others look at this problem from the opposite perspective, namely that of the AI itself. Here the idea is that even if we have good reason to believe that (...) it is very unlikely, the mere possibility of humanity causing extreme suffering to an AI is important enough to warrant serious consideration. This paper starts from the observation that both concerns rely on problematic philosophical assumptions. Rather than tackling these assumptions directly, it proceeds to present an argument that if one takes these assumptions seriously, then one has a moral obligation to advocate for a ban on the development of a conscious AI. (shrink)

Accelerating Turing machines are Turing machines of a sort able to perform tasks that are commonly regarded as impossible for Turing machines. For example, they can determine whether or not the decimal representation of contains n consecutive 7s, for any n; solve the Turing-machine halting problem; and decide the predicate calculus. Are accelerating Turing machines, then, logically impossible devices? I argue that they are not. There are implications concerning the nature of effective procedures and the theoretical limits of computability. Contrary (...) to a recent paper by Bringsjord, Bello and Ferrucci, however, the concept of an accelerating Turing machine cannot be used to shove up Searle's Chinese room argument. (shrink)

This entry provides a substantive overview of research and debates concerning creativity in philosophy and related fields. Topics covered include definitions of creativity, whether creativity can be learned, whether it can be explained, attempts to explain creativity in cognitive science, and whether computer programs or AI systems can be creative.

Lady Lovelace’s notes on Babbage’s Analytical Engine never refer to the concept of surprise. Having some pretension to ‘originate’ something—unlike the Analytical Engine—is neither necessary nor sufficient to being able to surprise someone. Turing nevertheless translates Lovelace’s ‘this machine is incapable of originating something’ in terms of a hypothetical ‘computers cannot take us by surprise’ objection to the idea that machines may be deemed capable of thinking. To understand the contemporary significance of what is missed in Turing’s ‘surprise’ translation of (...) Lovelace’s insight, one needs to distinguish between trivial surprises and those events, propositions or encounters that lead us to question our understanding of ourselves or what surrounds us. Only some of these non-trivial surprises are the product of originality endeavours. Not only is it uncommon for surprises to track such endeavours, the type of autonomy that would be required on the part of ‘digital computers’ for originality and surprise to intersect in that way goes far beyond the operational autonomy that can be achieved by ‘learning machines’. This paper argues that a salient translation of Lovelace’s originality insight—for contemporary and future ‘learning machines’—is an upside-down version of Turing’s surprise question: can computers be surprised by us in a non-trivial, ‘co-produced’ way? (shrink)

In this paper I argue that Turing’s responses to the mathematical objection are straightforward, despite recent claims to the contrary. I then go on to show that by understanding the importance of learning machines for Turing as related not to the mathematical objection, but to Lady Lovelace’s objection, we can better understand Turing’s response to Lady Lovelace’s objection. Finally, I argue that by understanding Turing’s responses to these objections more clearly, we discover a hitherto unrecognized, substantive thesis in his philosophical (...) thinking about the nature of mind. (shrink)

Brauchen Roboter moralische Kompetenz? Die Antwort lautet ja. Einerseits benötigen Roboter moralische Kompetenz, um unsere Welt aus Regeln, Vorschriften und Werten zu begreifen, andererseits um von ihrem Umfeld akzeptiert zu werden. Wie aber lässt sich moralische Kompetenz in Roboter implementieren? Welche philosophischen Herausforderungen sind zu erwarten? Und wie können wir uns und unsere Kinder auf Roboter vorbereiten, die irgendwann über moralische Kompetenz verfügen werden? André und Iga Maria Schmiljun skizzieren aus einer humanistisch-philosophischen Perspektive erste Antworten auf diese Fragen und entwickeln (...) einen didaktischen Einstieg in das Thema für die Grundschule. (shrink)

We provide an underlying theory of argument by disanalogy, in order to employ it to show that cyberwarfare is fundamentally new. Once this general case is made, the battle is won: we are well on our way to establishing our main thesis: that Just War Theory itself must be modernized. Augustine and Aquinas had a stunningly long run, but today’s world, based as it is on digital information and increasingly intelligent information-processing, points the way to a beast so big and (...) so radically different, that the core of this duo’s insights needs to be radically extended. (shrink)

The standard interpretation of the imitation game is defended over the rival gender interpretation though it is noted that Turing himself proposed several variations of his imitation game. The Turing test is then justified as an inductive test not as an operational definition as commonly suggested. Turing's famous prediction about his test being passed at the 70% level is disconfirmed by the results of the Loebner 2000 contest and the absence of any serious Turing test competitors from AI on the (...) horizon. But, reports of the death of the Turing test and AI are premature. AI continues to flourish and the test continues to play an important philosophical role in AI. Intelligence attribution, methodological, and visionary arguments are given in defense of a continuing role for the Turing test. With regard to Turing's predictions one is disconfirmed, one is confirmed, but another is still outstanding. (shrink)

Scientific behavior is used as a benchmark to examine the truth status of computationalism (COMP) as a law of nature. A COMP-based artificial scientist is examined from three simple perspectives to see if they shed light on the truth or falsehood of COMP through its ability or otherwise, to deliver authentic original science on the a priori unknown like humans do. The first perspective (A) looks at the handling of ignorance and supports a claim that COMP is "trivially true" or (...) "pragmatically false" in the sense that you can simulate a scientist if you already know everything, which is a state that renders the simulation possible but pointless. The second scenario (B) is more conclusive and unusual in that it reveals that the COMP scientist can never propose/debate that COMP is a law of nature. This marked difference between the human and the artificial scientist in this single, very specific circumstance, means that COMP cannot be true as a general claim. The third scenario (C) examines the artificial scientist's ability to do science on itself/humans to uncover the "law of nature" which results in itself. This scenario reveals that a successful test for scientific behavior by a COMP-based artificial scientist supports a claim that COMP is true. Such a test is quite practical and can be applied to an artificial scientist based on any design principle, not merely COMP. Scenario (C) also reveals a practical example of the COMP scientist's inability to handle informal systems (in the form of liars), which further undermines COMP. Overall, the result is that COMP is false, with certainty in one very specific, critical place. This lends support to the claims (i) that artificial general intelligence will not succeed based on COMP principles, and (ii) computationally enacted abstract models of human cognition will never create a mind. (shrink)