Alan Turing anticipated many areas of current research incomputer and cognitive science. This article outlines his contributionsto Artificial Intelligence, connectionism, hypercomputation, andArtificial Life, and also describes Turing's pioneering role in thedevelopment of electronic stored-program digital computers. It locatesthe origins of Artificial Intelligence in postwar Britain. It examinesthe intellectual connections between the work of Turing and ofWittgenstein in respect of their views on cognition, on machineintelligence, and on the relation between provability and truth. Wecriticise widespread and influential misunderstandings of theChurch–Turing thesis (...) and of the halting theorem. We also explore theidea of hypercomputation, outlining a number of notional machines thatcompute the uncomputable. (shrink)

We describe an emerging field, that of nonclassical computability and nonclassical computing machinery. According to the nonclassicist, the set of well-defined computations is not exhausted by the computations that can be carried out by a Turing machine. We provide an overview of the field and a philosophical defence of its foundations.

A myth has arisen concerning Turing's paper of 1936, namely that Turing set forth a fundamental principle concerning the limits of what can be computed by machine - a myth that has passed into cognitive science and the philosophy of mind, to wide and pernicious effect. This supposed principle, sometimes incorrectly termed the 'Church-Turing thesis', is the claim that the class of functions that can be computed by machines is identical to the class of functions that can be computed by (...) Turing machines. In point of fact Turing himself nowhere endorses, nor even states, this claim (nor does Church). I describe a number of notional machines, both analogue and digital, that can compute more than a universal Turing machine. These machines are exemplars of the class of _nonclassical_ computing machines. Nothing known at present rules out the possibility that machines in this class will one day be built, nor that the brain itself is such a machine. These theoretical considerations undercut a number of foundational arguments that are commonly rehearsed in cognitive science, and gesture towards a new class of cognitive models. (shrink)

To compute is to execute an algorithm. More precisely, to say that a device or organ computes is to say that there exists a modelling relationship of a certain kind between it and a formal specification of an algorithm and supporting architecture. The key issue is to delimit the phrase of a certain kind. I call this the problem of distinguishing between standard and nonstandard models of computation. The successful drawing of this distinction guards Turing's 1936 analysis of computation against (...) a difficulty that has persistently been raised against it, and undercuts various objections that have been made to the computational theory of mind. (shrink)

John Searle distinguished between weak and strong artificial intelligence (AI). This essay discusses a third alternative, mild AI, according to which a machine may be capable of possessing a species of mentality. Using James Fetzer's conception of minds as semiotic systems, the possibility of what might be called ``mild AI'' receives consideration. Fetzer argues against strong AI by contending that digital machines lack the ground relationship required of semiotic systems. In this essay, the implementational nature of semiotic processes posited by (...) Charles S. Peirce's triadic sign relation is re-examined in terms of the underlying dispositional processes and the ontological levels they would span in an inanimate machine. This suggests that, if non-human mentality can be replicated rather than merely simulated in a digital machine, the direction to pursue appears to be that of mild AI. (shrink)

This article is an accompaniment to Anthony Freeman’s review of Views into the Chinese Room, reflecting on some pertinent outstanding questions about the Chinese room argument. Although there is general agreement in the artificial intelligence community that the CRA is somehow wrong, debate continues on exactly why and how it is wrong. Is there a killer counter-argument and, if so, what is it? One remarkable fact is that the CRA is prototypically a thought experiment, yet it has been very little (...) discussed from the perspective of thought experiments in general. Here, I argue that the CRA fails as a thought experiment because it commits the fallacy of undersupposing, i.e., it leaves too many details to be filled in by the audience. Since different commentators will often fill in details differently, leading to different opinions of what constitutes a decisive counter, the result is 21-plus years of inconclusive debate. (shrink)

John Searle’s Chinese room argument is a celebrated thought experiment designed to refute the hypothesis, popular among artificial intelligence scientists and philosophers of mind, that “the appropriately programmed computer really is a mind”. Since its publication in 1980, the CRA has evoked an enormous amount of debate about its implications for machine intelligence, the functionalist philosophy of mind, theories of consciousness, etc. Although the general consensus among commentators is that the CRA is flawed, and not withstanding the popularity of the (...) systems reply in some quarters, there is remarkably little agreement on exactly how and why it is flawed. A newcomer to the controversy could be forgiven for thinking that the bewildering collection of diverse replies to Searle betrays a tendency to unprincipled, ad hoc argumentation and, thereby, a weakness in the opposition’s case. In this paper, treating the CRA as a prototypical example of a ‘destructive’ thought experiment, I attempt to set it in a logical framework, which allows us to systematise and classify the various objections. Since thought experiments are always posed in narrative form, formal logic by itself cannot fully capture the controversy. On the contrary, much also hinges on how one translates between the informal everyday language in which the CRA was initially framed and formal logic and, in particular, on the specific conception of possibility that one reads into the logical formalism. (shrink)

Turing''s test has been much misunderstood. Recently unpublished material by Turing casts fresh light on his thinking and dispels a number of philosophical myths concerning the Turing test. Properly understood, the Turing test withstands objections that are popularly believed to be fatal.

The concept of narrow content is still under discussion in the debate over mental representation. In the paper, one-factor dimensional accounts of representation are analyzed, particularly the case of Fodor's methodological solipsism. In methodological solipsism, semantic properties of content are arguably eliminated in favor of syntactic ones. If “narrow content” means content properties independent of external factors to a system (as in Segal's view), the concept of content becomes elusive. Moreover, important conceptual problems with one-factor dimensional account are pointed out (...) as a result of analysis arguments presented by J. Searle, S. Harnad and T. Burge. Furthermore, these problems are illustrated with psychological and ethological examples. Although understanding content as partially independent from contextual factors allows theorists to preserve content properties, it seems that understanding content in total abstraction from external factors of these properties is implausible. As a result, internalism is rejected in favor of externalism. (shrink)

If Australasian philosophers constitute the kind of group to which a collective identity or broadly shared self-image can plausibly be ascribed, the celebrated history of Australian materialism rightly lies close to its heart. Jack Smart’s chapter in this volume, along with an outstanding series of briefer essays in A Companion to Philosophy in Australia and New Zealand (Forrest 2010; Gold 2010; Koksvik 2010; Lycan 2010; Matthews 2010; Nagasawa 2010; Opie 2010; Stoljar 2010a), effectively describe the naturalistic realism of Australian philosophy (...) of mind. In occasional semi-serious psychogeographic speculation, this long-standing and strongly-felt intellectual attitude has been traced back to the influences of our light, land, or lifestyle (Devitt 1996, x; compare comments by Chalmers and O’Brien in Mitchell, 2006). Australasian work in philosophy of mind and cognition has become more diverse in the last 40 years, but is almost all still marked, in one way or another, by the history of these debates on materialism. (shrink)

Este artículo analiza el Test de Turing, uno de los métodos más famosos y controvertidos para evaluar la existencia de vida mental en la Filosofía de la Mente, revelando dos mitos filosóficos comúnmente aceptados y criticando su dogma. En primer lugar, se muestra por qué Turing nunca propuso una definición de inteligencia. En segundo lugar, se refuta que el Test de Turing involucre condiciones necesarias o suficientes para la inteligencia. En tercer lugar, teniendo presente el objetivo y el tipo de (...) evidencia que recopila, se considera si el Test de Turing cuenta como un experimento científico a la luz de la concepción de Fodor. Finalmente, se argumenta que Turing simpatiza con una forma de Conductismo, confundiendo la simulación -un proceso epistémico que, gobernado por la verosimilitud, es eficaz cuando alguien es causado a creer que el computador es inteligente- con la duplicación de la inteligencia en cuanto propiedad, lo que ocurre a nivel ontológico. Tal confusión implica un dogma y explica por qué, a pesar de haber sido propuesto como una solución final a la problemática de si las máquinas programadas piensan, el Test de Turing ha tenido precisamente el efecto contrario en más de cinco décadas, estimulando el debate filosófico en torno a la naturaleza de lo mental. (shrink)

Searle has recently used two adaptations of his Chinese room argument in an attack on connectionism. I show that these new forms of the argument are fallacious. First I give an exposition of and rebuttal to the original Chinese room argument, and then a brief introduction to the essentials of connectionism.

Over the last two decades, there was an upsurge of research and innovation in biotechnology and related fields, leading to exciting new discoveries in areas such as the engineering of biological processes, gene editing, stem cell research, CRISPR-Cas9 technology, Synthetic Biology, recombinant DNA, LMOs and GMOs, to mention only a few. At the same time, these advances generated concerns about biosafety, biosecurity and adverse impacts on biodiversity and the environment, leading to the establishment of Research Ethics Committees (RECs) at Higher (...) Education and Research Institutions dedicated to reviewing research with implications for biosafety and the environment. -/- These Biosafety and Environment Research Ethics Committees, referred to as EBRECs, are in the early stages of their establishment and formalisation, and there is much uncertainty about their composition, scope, procedures of decision-making and the principles that should guide their deliberations and assessments. In many respects, EBRECs are venturing into uncharted territory, facing a very wide range of complex research fields, far-reaching research practices and deep concerns new to Review Boards, raising the question to what extent EBRECs can fall back on the fairly well-established principles and procedures of RECs focusing on Human, Health or Animal research, and to what extent they need new or adapted principles and procedures. -/- Against this background, I set out to answer the following three main research questions in this thesis: 1. What is the current state of ethical principles for ethics reviews in the field of environmental and biosafety research ethics? Which principles are currently used in this context, and how? 2. What are the shortcomings of the current principles used by EBRECs and how can they be overcome? 3. What ethical principles must be adopted by environmental and biosafety research ethics committees and guide them in their decision-making? -/- In order to prepare the ground and set the scene for my discussion of these questions, I also formulated four supporting research questions: i. What is environmental research ethics in action? ii. What is biosafety research ethics in action? iii. How are environmental and biosafety ethics related to one another? iv. How should the guidelines and ethical principles related to these two overlapping fields be implemented in the ethics review process? Following my introduction and problem statement in Chapter 1, I devoted Chapters 2 and 3 to an overview of my supporting questions to set the scene for Environmental and Biosafety Research Ethics. In Chapter 4, I turned to my main research question with a discussion of national and international declarations, frameworks and legislation and an investigation of principles in the different research areas to get a picture of applicable principles that can guide EBRECs. -/- The main finding of my thesis is that due to the complexity of EBR, different categories of principles could be the solution for EBRECs. I elaborate on this in Chapter 5, my concluding chapter, in which I also propose a list of core principles that can serve as an accessible and easy-to-use guide for EBRECs in their decision-making. In this proposal, I cluster different kinds of principles in terms of four categories: 1. Principles as a Moral Concept 2. Principles as a Social Concept 3. Principles as a Legal Concept 4. Principles as a Safety Concept . (shrink)

Turing used the expression “emotional” in three distinct ways: to state his philosophical theory of the concept of intelligence, to classify arguments for and against the possibility of machine intelligence, and to describe the education of a “child machine”. The remarks on emotion include several of the most important philosophical claims. This paper analyses these remarks and their significance for current research in Artificial Intelligence.

The presence of intelligence and rationality in Artificial Intelligence and the Internet requires a new context of analysis in which Herbert Simon’s approach to the sciences of the artificial is surpassed in order to grasp the role of information in our contemporary setting. This new framework requires taking into account some relevant aspects. In the historical endeavor of building up AI and the Internet, minds and machines have interacted over the years and in many ways through the interrelation between scientific (...) creativity and technological innovation. Philosophically, minds and machines can have epistemological, methodological and ontological differences, which are based on the distinct configuration of human intelligence and artificial intelligence. Their comparison with rationality and its various forms is particularly relevant. Scientifically, AI and the Internet belong to the sciences of the artificial, because they work on designs that search for specific aims, following selected processes in order to achieve expected results. Technologically, AI and the Internet require the support of information and communication technologies. These have an instrumental role regarding the existence of AI and the Internet. Also ICT shape their diverse forms of configuration over the years.Within this framework, this paper offers a new context of analysis that goes beyond Simon’s and follows four main steps: the interaction between scientific creativity and technological innovation as the philosophico-methodological setting for Artificial Intelligence and the Internet; artificial intelligence and human intelligence as epistemological basis for machines and minds, where the differences between artificial intelligence and human intelligence are made explicit and the analysis of minds and machines is made from the perspective of rationality ; intention and its difference with design of machine learning are considered to distinguish human intelligence from artificial intelligence; and the internal and external aspects of artificial designs in contemporary society are considered through the perspective of rationality, which leads to the transition from intelligence to rationality in the Internet as well as to the historicity of information. (shrink)

L’évolution forme des structures de degrés d’organisation et de pouvoir de plus en plus grands, processus dans lequel les plus forts l’emportent sur les plus faibles et continuent l’évolution. La technologie est une création artificielle qui met souvent en danger la vie et l’évolution entendues comme phénomènes naturels, mais la technologie conserve aussi la vie et agit avec l’évolution. Cependant, certains soutiennent que la technologie fera bien plus que cela, et qu’elle ouvrira une époque tout à fait nouvelle de l’évolution. (...) La technologie remplacera les porteurs biologiques fragiles de l’évolution par une nouvelle espèce de porteurs non biologiques doués d’une intelligence et d’un pouvoir très grands. Cet article examine la plausibilité et la faiblesse de telles projections fascinantes que certains annoncent avec fierté comme la libération finale de l’Esprit, tandis que d’autres les appréhendent comme les signes de l’autodestruction finale de l’Homme. (shrink)