What psychological and philosophical significance should we attach to recent efforts at computer simulations of human cognitive capacities? In answering this question, I find it useful to distinguish what I will call "strong" AI from "weak" or "cautious" AI. According to weak AI, the principal value of the computer in the study of the mind is that it gives us a very powerful tool. For example, it enables us to formulate and test hypotheses in a more rigorous and precise fashion. (...) But according to strong AI, the computer is not merely a tool in the study of the mind; rather, the appropriately programmed computer really is a mind, in the sense that computers given the right programs can be literally said to. (shrink)

I propose to consider the question, "Can machines think?" This should begin with definitions of the meaning of the terms "machine" and "think." The definitions might be framed so as to reflect so far as possible the normal use of the words, but this attitude is dangerous, If the meaning of the words "machine" and "think" are to be found by examining how they are commonly used it is difficult to escape the conclusion that the meaning and the answer to (...) the question, "Can machines think?" is to be sought in a statistical survey such as a Gallup poll. But this is absurd. Instead of attempting such a definition I shall replace the question by another, which is closely related to it and is expressed in relatively unambiguous words. The new form of the problem can be described in terms of a game which we call the 'imitation game." It is played with three people, a man (A), a woman (B), and an interrogator (C) who may be of either sex. The interrogator stays in a room apart front the other two. The object of the game for the interrogator is to determine which of the other two is the man and which is the woman. He knows them by labels X and Y, and at the end of the game he says either "X is A and Y is B" or "X is B and Y is A." The interrogator is allowed to put questions to A and B. We now ask the question, "What will happen when a machine takes the part of A in this game?" Will the interrogator decide wrongly as often when the game is played like this as he does when the game is played between a man and a woman? These questions replace our original, "Can machines think?". (shrink)

The ArgumentIn its reconstruction of scientific practice, philosophy of science has traditionally placed scientific theories in a central role, and has reduced the problem of mediating between theories and the world to formal considerations. Many applications of scientific theories, however, involve complex mathematical models whose constitutive equations are analytically unsolvable. The study of these applications often consists in developing representations of the underlying physics on a computer, and using the techniques of computer simulation in order to learn about the behavior (...) of these systems. In many instances, these computer simulations are not simple number-crunching techniques. They involve a complex chain of inferences that serve to transform theoretical structures into specific concrete knowledge of physical systems. In this paper I argue that this process of transformation has its own epistemology. I also argue that this kind of epistemology is unfamiliar to most philosophy of science, which has traditionally concerned itself with the justification of theories, not with their application. Finally, I urge that the nature of this epistemology suggests that the end results of some simulations do not bear a simple, straightforward relation to the theories from which they stem. (shrink)

Synthetic biology makes use of genetic and other materials derived from modern biological life forms to design and construct novel synthetic organisms. Artificial organisms are not constructed from parts of existing biological organisms, but from non-biological materials. Artificial and synthetic organisms are artefactual organisms. Here we are concerned with the non-instrumental value of such organisms. More specifically, we are concerned with the extent to which artefactual organisms have natural value, inherent worth and intrinsic value. Our conclusions are largely supportive of (...) the value of artefactual organisms. However, they do not constitute a comprehensive ethical evaluation of them. (shrink)

This paper investigates whether moral status talk gets us anywhere in our search for answers to questions in the ethics of marginal cases. I consider the usefulness of moral status talk first on the assumption that an individual's possession of moral status is not a further fact about that individual, and then on the assumption that it is. Finally, I offer an expressivistic interpretation of moral status talk. In each case, I argue that such talk conveys nothing that cannot be (...) conveyed more clearly in other words. My conclusion is that we should stop using moral status and its cognates. (shrink)

To hold an environmental ethic is to hold that non-human beings and states of affairs in the natural world have intrinsic value. This seemingly straightforward claim has been the focus of much recent philosophical discussion of environmental issues. Its clarity is, however, illusory. The term ‘intrinsic value’ has a variety of senses and many arguments on environmental ethics suffer from a conflation of these different senses: specimen hunters for the fallacy of equivocation will find rich pickings in the area. This (...) paper is largely the work of the underlabourer. I distinguish different senses of the concept of intrinsic value, and, relatedly, of the claim that non-human beings in the natural world have intrinsic value; I exhibit the logical relations between these claims and examine the distinct motivations for holding them. The paper is not however merely an exercise in conceptual underlabouring. It also defends one substantive thesis: that while it is the case that natural entities have intrinsic value in the strongest sense of the term, i.e., in the sense of value that exists independently of human valuations, such value does not as such entail any obligations on the part of human beings. The defender of nature’s intrinsic value still needs to show that such value contributes to the well-being of human agents. (shrink)

A formal theory of truth, alternative to tarski's 'orthodox' theory, based on truth-value gaps, is presented. the theory is proposed as a fairly plausible model for natural language and as one which allows rigorous definitions to be given for various intuitive concepts, such as those of 'grounded' and 'paradoxical' sentences.

The notion of scope as it relates to a model of logical form is discussed. The inability of the accepted definition of scope to account for the contrast between priority scope - the logical priority of different quantifiers & other logical notions via rule ordering - & binding scope - the identification of the connection between variables of quantification & a particular quantifier - is demonstrated. The semantic ambiguity of this dichotomy of scope is explored via examination of donkey sentences. (...) A formal representation of this dichotomy is suggested. The government-binding approach & principle of compositionality that handle scope relations via the logical form is rejected due to the complexity of the mechanism by which syntactic form results in logical forms. A discourse representational approach is also rejected. It is concluded that the interaction of syntax & semantics is instead better represented by a game-theoretical treatment of scope & anaphora. 26 References. T. Rosenberg. (shrink)

If one wishes to accept that some painful animal experimentation can be justified on grounds that benefit is conferred, one is faced with a difficult moral dilemma argues the first author, a philosopher. Either one needs to be able to say why human lives of any quality however low should be inviolable from painful experimentation when animal lives are not; or one should accept that sufficient benefit can justify certain painful experiments on human beings of sufficiently low quality of life. (...) Alternatively, one can reject the original premise and accept antivivisectionism. Replies to his paper follow from an antivivisectionist philosopher and an eminent pharmacologist long involved in animal experimentation. Dr Frey responds to both replies. (shrink)

Whereas computer simulations involve no direct physical interaction between the machine they are run on and the physical systems they are used to investigate, they are often used as experiments and yield data about these systems. It is commonly argued that they do so because they are implemented on physical machines. We claim that physicality is not necessary for their representational and predictive capacities and that the explanation of why computer simulations generate desired information about their target system is only (...) to be found in the detailed analysis of their semantic levels. We provide such an analysis and we determine the actual consequences of physical implementation for simulations. (shrink)

Christine M. Korsgaard is Arthur Kingsley Porter Professor of Philosophy at Harvard University. She was educated at the University of Illinois and received a Ph.D. from Harvard. She has held positions at Yale, the University of California at Santa Barbara, and the University of Chicago, and visiting positions at Berkeley and UCLA. She is a member of the American Philosophical Association and a fellow of the American Academy of Arts and Sciences. She has published extensively on Kant, and about moral (...) philosophy and its history, the theory of practical reason, the philosophy of action, and personal identity. Her two published books are The Sources of Normativity (1992) and Creating the King- dom of Ends (1996). (shrink)

Environmental Ethics: An Anthology brings together seminal writings on the central questions in environmental ethics. The book comprises both classic and cutting-edge essays that have formed contemporary environmental ethics, ranging from the welfare of animals versus ecosystems to theories of the intrinsic value of nature. The volume also discusses alternatives to traditional environmental ethics, including deep ecology, ecofeminism, and environmental pragmatism; and presents important works on particular environmental issues, such as wilderness preservation and global climate change. Additional editorial material provides (...) a helpful overview of the field and points to new directions and controversies shaping the relationship between humans and nature into the future. Specifically designed for course use, Environmental Ethics: An Anthology provides an excellent introduction, at once accessible and thorough, to this increasingly important and urgent area of study. (shrink)

Are ecosystems morally considerable-that is, do we owe it to them to protect their “interests”? Many environmental ethicists, impressed by the way that individual nonsentient organisms such as plants tenaciously pursue their own biological goals, have concluded that we should extend moral considerability far enough to include such organisms. There is a pitfall in the ecosystem-to-organism analogy, however. We must distinguish a system’s genuine goals from the incidental effects, or byproducts, of the behavior of that system’s parts. Goals seem capable (...) of giving rise to interests; byproducts do not. It is hard to see how whole ecosystems can be genuinely goal-directed unless group selection occurs at the community level. Currently, mainstream ecological and evolutionary theory is individualistic. From such a theory it follows that the apparent goals of ecosystems are mere byproducts and, as such, cannot ground moral considerability. (shrink)

We propose here to clarify some of the relations existing between information and meaning by showing how meaningful information can be generated by a system submitted to a constraint. We build up definitions and properties for meaningful information, a meaning generator system and the domain of efficiency of a meaning (to cover cases of meaningful information transmission). Basic notions of information processing are used.

Simulation techniques, especially those implemented on a computer, are frequently employed in natural as well as in social sciences with considerable success. There is mounting evidence that the "model-building era" (J. Niehans) that dominated the theoretical activities of the sciences for a long time is about to be succeeded or at least lastingly supplemented by the "simulation era". But what exactly are models? What is a simulation and what is the difference and the relation between a model and a simulation? (...) These are some of the questions addressed in this article. I maintain that the most significant feature of a simulation is that it allows scientists to imitate one process by another process. "Process" here refers solely to a temporal sequence of states of a system. Given the observation that processes are dealt with by all sorts of scientists, it is apparent that simulations prove to be a powerful interdisciplinarily acknowledged tool. Accordingly, simulations are best suited to investigate the various research strategies in different sciences more carefully. To this end, I focus on the function of simulations in the research process. Finally, a somewhat detailed case-study from nuclear physics is presented which, in my view, illustrates elements of a typical simulation in physics. (shrink)

What happens when machines become more intelligent than humans? One view is that this event will be followed by an explosion to ever-greater levels of intelligence, as each generation of machines creates more intelligent machines in turn. This intelligence explosion is now often known as the “singularity”. The basic argument here was set out by the statistician I.J. Good in his 1965 article “Speculations Concerning the First Ultraintelligent Machine”: Let an ultraintelligent machine be defined as a machine that can far (...) surpass all the intellectual activities of any man however clever. Since the design of machines is one of these intellectual activities, an ultraintelligent machine could design even better machines; there would then unquestionably be an “intelligence explosion”, and the intelligence of man would be left far behind. Thus the first ultraintelligent machine is the last invention that man need ever make. The key idea is that a machine that is more intelligent than humans will be better than humans at designing machines. So it will be capable of designing a machine more intelligent than the most intelligent machine that humans can design. So if it is itself designed by humans, it will be capable of designing a machine more intelligent than itself. By similar reasoning, this next machine will also be capable of designing a machine more intelligent than itself. If every machine in turn does what it is capable of, we should expect a sequence of ever more intelligent machines. This intelligence explosion is sometimes combined with another idea, which we might call the “speed explosion”. The argument for a speed explosion starts from the familiar observation that computer processing speed doubles at regular intervals. Suppose that speed doubles every two years and will do so indefinitely. Now suppose that we have human-level artificial intelligence 1 designing new processors. Then faster processing will lead to faster designers and an ever-faster design cycle, leading to a limit point soon afterwards. The argument for a speed explosion was set out by the artificial intelligence researcher Ray Solomonoff in his 1985 article “The Time Scale of Artificial Intelligence”.1 Eliezer Yudkowsky gives a succinct version of the argument in his 1996 article “Staring at the Singularity”: “Computing speed doubles every two subjective years of work.. (shrink)

There has been much discussion recently about the scope and limits of purely symbolic models of the mind and about the proper role of connectionism in cognitive modeling. This paper describes the symbol grounding problem : How can the semantic interpretation of a formal symbol system be made intrinsic to the system, rather than just parasitic on the meanings in our heads? How can the meanings of the meaningless symbol tokens, manipulated solely on the basis of their shapes, be grounded (...) in anything but other meaningless symbols? The problem is analogous to trying to learn Chinese from a Chinese/Chinese dictionary alone. A candidate solution is sketched: Symbolic representations must be grounded bottom-up in nonsymbolic representations of two kinds: iconic representations, which are analogs of the proximal sensory projections of distal objects and events, and categorical representations, which are learned and innate feature-detectors that pick out the invariant features of object and event categories from their sensory projections. Elementary symbols are the names of these object and event categories, assigned on the basis of their categorical representations. Higher-order symbolic representations, grounded in these elementary symbols, consist of symbol strings describing category membership relations. Connectionism is one natural candidate for the mechanism that learns the invariant features underlying categorical representations, thereby connecting names to the proximal projections of the distal objects they stand for. In this way connectionism can be seen as a complementary component in a hybrid nonsymbolic/symbolic model of the mind, rather than a rival to purely symbolic modeling. Such a hybrid model would not have an autonomous symbolic module, however; the symbolic functions would emerge as an intrinsically dedicated symbol system as a consequence of the bottom-up grounding of categories ' names in their sensory representations. Symbol manipulation would be governed not just by the arbitrary shapes of the symbol tokens, but by the nonarbitrary shapes of the icons and category invariants in which they are grounded. (shrink)

There is no consensus yet on the definition of semantic information. This paper contributes to the current debate by criticising and revising the Standard Definition of semantic Information as meaningful data, in favour of the Dretske-Grice approach: meaningful and well-formed data constitute semantic information only if they also qualify as contingently truthful. After a brief introduction, SDI is criticised for providing necessary but insufficient conditions for the definition of semantic information. SDI is incorrect because truth-values do not supervene on semantic (...) information, and misinformation is not a tyoe of semantic information, but pseudo-information, that is not semantic information at all. This is shown by arguing that none of the reasons for interpreting misinformation as a type of semantic information is convincing, whilst there are compelling reasons to treat it as pseudo-information. As a consequence, SDI is revised to include a necessary truth-condition. The last section summarises the main results of the paper and indicates the important implications of the revised definition for the analysis of the deflationary theories of truth, the standard definition of knowledge and the classic, quantitative theory of semantic information. (shrink)

This article provides a survey of some of the reasons why computational approaches have become a permanent addition to the set of scientific methods. The reasons for this require us to represent the relation between theories and their applications in a different way than do the traditional logical accounts extant in the philosophical literature. A working definition of computer simulations is provided and some properties of simulations are explored by considering an example from quantum chemistry.

This article reviews eight proposed strategies for solving the Symbol Grounding Problem (SGP), which was given its classic formulation in Harnad (1990). After a concise introduction, we provide an analysis of the requirement that must be satisfied by any hypothesis seeking to solve the SGP, the zero semantical commitment condition. We then use it to assess the eight strategies, which are organised into three main approaches: representationalism, semi-representationalism and non-representationalism. The conclusion is that all the strategies are semantically committed and (...) hence that none of them provides a valid solution to the SGP, which remains an open problem. (shrink)

Evolutionary advantages of consciousness and intersubjectivity are part of current philosophical debates on the nature of consciousness. Both are linked and intersubjectivity is sometimes considered as a form of consciousness [1]. Regarding the evolution of consciousness, studies tend to focus on phenomenal consciousness [2]. We would like here to bring the focus on self-consciousness and continue the build up of a corresponding evolutionary scenario. We also propose to introduce a possible evolutionary link between self-consciousness and phenomenal consciousness. Our starting point (...) is the evolutionary scenario based on the evolution of intersubjectivity that goes thru the identification with conspecifics at pre-human primate time frame [3, 4, 5]. The scenario considers that such identification with conspecifics brought the non self-conscious auto-representation carried by our prehuman primate ancestors to merge with the representations of conspecifics. The latter transferred to the auto-representation the characteristics of an entity existing in the environment, and by this way introduced some first elements of self-consciousness for our pre-human ancestors. In addition, an anxiety increase coming from the identification with suffering or endangered conspecifics produced an evolutionary engine based on anxiety limitation. We want here to complement this evolutionary approach by introducing the improvement of action programs as a contributor to the evolutionary advantages of intersubjectivity and self-consciousness. We look at the possibility for a subject to improve the action programs that conspecifics implement. The performance of identification with conspecifics allows the subject to consider that errors made by conspecifics are potentially her own errors, and consequently allows the subject to correct the errors of conspecifics for her own benefit. We describe the process of non successful action identification from the perspective of an observer and present the synergetic action program improvements with their contribution to the evolution of intersubjectivity and self-consciousness. We add this contribution to the existing evolutionary scenario on self-consciousness and introduce a possible evolutionary link between self-consciousness and phenomenal consciousness. We use for that the relation existing between phenomenal consciousness and pre-reflexive self-consciousness [6] and propose to link the latter to the proposed evolutionary nature of self-consciousness. We finish by summarizing the points addressed and by introducing some possible continuations. (shrink)

Self-consciousness is a product of evolution. Few people today disagree with the evolutionary history of humans. But the nature of self-consciousness is still to be explained, and the story of evolution has rarely been used as a framework for studies on consciousness during the 20th century. This last point may be due to the fact that modern study of consciousness came up at a time where dominant philosophical movements were not in favor of evolutionist theories (Cunningham 1996). Research on consciousness (...) based on Phenomenology or on Analytic Philosophy has been mostly taking the characteristics of humans as starting points. Relatively little has been done with bottom-up approaches, using performances of animals as a simpler starting point to understand the generation of consciousness through evolution. But this status may be changing, thanks to new tools coming from recent discoveries in neurology. The discovery of mirror neurons about ten years ago (Gallese et al. 1996, Rizzolatti et al. 1996) has allowed the built up of new conceptual tools for the understanding of intersubjectivity within humans and non human primates (Gallese 2001, Hurley 2005). Studies in these fields are still in progress, with discussions on the level of applicability of this natural intersubjectivity to non human primates (Decety and Chaminade 2003). We think that these subject/conspecific mental relations made possible by mirror neurons can open new paths for the understanding of the nature of self-consciousness via an evolutionist bottom-up approach. We propose here a scenario for the build up of self-consciousness through evolution by a specific analysis of two steps of evolution: first step from simple living elements to non human primates comparable to chimpanzees, and second step from these non human primates to humans. We identify these two steps as representing the evolution from basic animal awareness to body self-awareness, and from body self-awareness to self-consciousness. (we consider that today non human primates are comparable to what were pre-human primates). We position body self-awareness as corresponding to the performance of mirror self recognition as identified with chimpanzees and orangutans (Gallup). We propose to detail and understand the content of this body self-awareness through a specific evolutionist build up process using the performances of mirror neurons and group life. We address the evolutionary step from body self-awareness to self-consciousness by complementing the recently proposed approach where self-consciousness is presented as a by-product of body self-awareness amplification via a positive feedback loop resulting of anxiety limitation (Menant 2004). The scenario introduced here for the build up of self-consciousness through evolution leaves open the question about the nature of phenomenal-consciousness (Block 2002). We plan to address this question later on with the help of the scenario made available here. (shrink)

Understanding computation as “a process of the dynamic change of information” brings to look at the different types of computation and information. Computation of information does not exist alone by itself but is to be considered as part of a system that uses it for some given purpose. Information can be meaningless like a thunderstorm noise, it can be meaningful like an alert signal, or like the representation of a desired food. A thunderstorm noise participates to the generation of meaningful (...) information about coming rain. An alert signal has a meaning as allowing a safety constraint to be satisfied. The representation of a desired food participates to the satisfaction of some metabolic constraints for the organism. Computations on information and representations will be different in nature and in complexity as the systems that link them have different constraints to satisfy. Animals have survival constraints to satisfy. Humans have many specific constraints coming in addition. And computers will compute what the designer and programmer ask for. We propose to analyze the different relations between information, meaning and representation by taking an evolutionary approach on the systems that link them. Such a bottom-up approach allows starting with simple organisms and avoids an implicit focus on humans, which is the most complex and difficult case. To make available a common background usable for the many different cases, we use a systemic tool that defines the generation of meaningful information by and for a system submitted to a constraint [Menant, 2003]. This systemic tool allows to position information, meaning and representations for systems relatively to environmental entities in an evolutionary perspective. We begin by positioning the notions of information, meaning and representation and recall the characteristics of the Meaning Generator System (MGS) that link a system submitted to a constraint to its environment. We then use the MGS for animals and highlight the network nature of the interrelated meanings about an entity of the environment. This brings us to define the representation of an item for an agent as being the network of meanings relative to the item for the agent. Such meaningful representations embed the agents in their environments and are far from the Good Old Fashion Artificial Intelligence type ones. The MGS approach is then used for humans with a limitation resulting of the unknown nature of human consciousness. Application of the MGS to artificial systems brings to look for compatibilities with different levels of Artificial Intelligence (AI) like embodied-situated AI, the Guidance Theory of Representations, and enactive AI. Concerns relative to different types of autonomy and organic or artificial constraints are highlighted. We finish by summarizing the points addressed and by proposing some continuations. (shrink)

Computer simulation is shown to be philosophically interesting because it introduces a qualitatively new methodology for theory construction in science different from the conventional two components of "theory" and "experiment and/or observation". This component is "experimentation with theoretical models." Two examples from the physical sciences are presented for the purpose of demonstration but it is claimed that the biological and social sciences permit similar theoretical model experiments. Furthermore, computer simulation permits theoretical models for the evolution of physical systems which use (...) cellular automata rather than differential equations as their syntax. The great advantages of the former are indicated. (shrink)

This dissertation uses the Liar paradox to motivate an account of the concept of truth that I call the "inconsistency theory of truth." The Liar paradox is the puzzle that arises when we consider such sentences, known as Liar sentences, that say of themselves that they are not true: whatever truth value we attribute to such a sentence, we seem to be immediately driven to the conclusion that it has the opposite truth value. Examining this puzzle reveals that its source (...) is the following principle, which we may call the disquotational principle: for any sentence 'A', 'A' is true if and only if A. While this principle is very natural, it is also inconsistent, as is shown when the sentence 'A' is a Liar sentence. ;After the introductory Chapter 1, Chapter 2 presents some of the technical work on the Liar. Chapter 3 discusses several accounts based on the idea that Liar sentences lack truth values; there I argue that those accounts fail to adequately address a problem known as the strengthened Liar problem. Next, Chapter 4 examines a family of views based on the idea that the formal contradictions derivable by means of the disquotational principle are not really genuine contradictions: according to these views, the appearance of contradiction results from ignoring a contextually determined hidden parameter. I argue that they, too, do not successfully handle the strengthened Liar problem. ;In Chapter 5 I put forth a view based on the idea that the concept of truth itself is inconsistent. Namely, the view I defend is that the linguistic conventions governing the use of the word 'true' commit us to the disquotational schema which, as I said, is inconsistent. I conclude in Chapter 6 by considering some of the implications of believing the inconsistency theory. (shrink)