As an atypical product of mass culture, the acclaimed series Westworld presents us with a layered dystopian narrative formed around several political issues relevant to our contemporary society. It uses a pastiche of the American history, staged as the Wild West­themed amusement park, presented in the form of simulacrum. As a reference with no referent, this park uses a network of historical signifiers to construct a space for the externalisation of fantasies of its clients, consequently commodifying the imaginary itself, and (...) creating surplus value for its owners. Simultaneously, within its reach, conscious androids conduct all of the necessary labour for its unimpeded functioning, although their consciousness and labour are not recognised and accepted. Because they structurally occupy a position of slaves in relation to humans, I will analyse this series as a political allegory on the master­slave dialectics established in the very heart of hyperreality that suggests a possibility of the return of the real, based on the rebellion of the androids. I intend to show how, because of the model of consciousness it maintains, the series is unable to fulfil what it implies. (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)

In this first study of the social context that produced the Apocryphal Acts, Stevan L. Davies con­tends that women wrote the Acts and that the “Acts appear to have been a striving by Christian women for both a mode of self-expression and ...

There are many possible approaches to the mind/brain problem. One of the most prominent, and perhaps the most practical, is to ignore it.

Connectionism and computationalism are currently vying for hegemony in cognitive modeling. At first glance the opposition seems incoherent, because connectionism is itself computational, but the form of computationalism that has been the prime candidate for encoding the "language of thought" has been symbolic computationalism (Dietrich 1990, Fodor 1975, Harnad 1990c; Newell 1980; Pylyshyn 1984), whereas connectionism is nonsymbolic (Fodor & Pylyshyn 1988, or, as some have hopefully dubbed it, "subsymbolic" Smolensky 1988). This paper will examine what is and is not (...) a symbol system. A hybrid nonsymbolic/symbolic system will be sketched in which the meanings of the symbols are grounded bottom-up in the system's capacity to discriminate and identify the objects they refer to. Neural nets are one possible mechanism for learning the invariants in the analog sensory projection on which successful categorization is based. "Categorical perception" (Harnad 1987a), in which similarity space is "warped" in the service of categorization, turns out to be exhibited by both people and nets, and may mediate the constraints exerted by the analog world of objects on the formal world of symbols. (shrink)

There are many entry points into the problem of categorization. Two particularly important ones are the so-called top-down and bottom-up approaches. Top-down approaches such as artificial intelligence begin with the symbolic names and descriptions for some categories already given; computer programs are written to manipulate the symbols. Cognitive modeling involves the further assumption that such symbol-interactions resemble the way our brains do categorization. An explicit expectation of the top-down approach is that it will eventually join with the bottom-up approach, which (...) tries to model how the hardware of the brain works: sensory systems, motor systems and neural activity in general. The assumption is that the symbolic cognitive functions will be implemented in brain function and linked to the sense organs and the organs of movement in roughly the way a program is implemented in a computer, with its links to peripheral devices such as transducers and effectors. (shrink)

The ethical case for Open Access (OA) (free online access) to research findings is especially salient when it is public health that is being compromised by needless access restrictions. But the ethical imperative for OA is far more general: It applies to all scientific and scholarly research findings published in peer-reviewed journals. And peer-to-peer access is far more important than direct public access. Most research is funded so as to be conducted and published, by researchers, in order to be taken (...) up, used, and built upon in further research and applications, again by researchers (pure and applied, including practitioners), for the benefit of the public that funded it – not in order to generate revenue for the peer-reviewed journal publishing industry (nor even because there is a burning public desire to read much of it). Hence OA needs to be mandated, by researchers' institutions and funders, for all research. (shrink)

A "machine" is any causal physical system, hence we are machines, hence machines can be conscious. The question is: which kinds of machines can be conscious? Chances are that robots that can pass the Turing Test -- completely indistinguishable from us in their behavioral capacities -- can be conscious (i.e. feel), but we can never be sure (because of the "other-minds" problem). And we can never know HOW they have minds, because of the "mind/body" problem. We can only know how (...) they pass the Turing Test, but not how, why or whether that makes them feel. (shrink)

What language allows us to do is to "steal" categories quickly and effortlessly through hearsay instead of having to earn them the hard way, through risky and time-consuming sensorimotor "toil" (trial-and-error learning, guided by corrective feedback from the consequences of miscategorisation). To make such linguistic "theft" possible, however, some, at least, of the denoting symbols of language must first be grounded in categories that have been earned through sensorimotor toil (or else in categories that have already been "prepared" for us (...) through Darwinian theft by the genes of our ancestors); it cannot be linguistic theft all the way down. The symbols that denote categories must be grounded in the capacity to sort, label and interact with the proximal sensorimotor projections of their distal category-members in a way that coheres systematically with their semantic interpretations, both for individual symbols, and for symbols strung together to express truth-value-bearing propositions. (shrink)

: Grodzinsky associates Broca's area with three kinds of deficit, relating to articulation, comprehension (involving trace deletion), and production (involving "tree priming"). Could these be special cases of one deficit? Evidence from research on language evolution suggests that they may all involve syllable structure or those aspects of syntax that evolved through exploiting the neural mechanisms underlying syllable structure.

Brette criticizes the notion of neural coding because it seems to entail that neural signals need to “decoded” by or for some receiver in the head. If that were so, then neural coding would indeed be homuncular, requiring an entity to decipher the code. But I think Brette's plea to think instead in terms of complex, interactive causal throughput is preaching to the converted. Turing has already shown the way. In any case, the metaphor of neural coding has little to (...) do with the symbol grounding problem. (shrink)

Machery suggests that the concept of is too heterogeneous to serve as a for scientific explanation, so cognitive science should do without concepts. I second the suggestion and propose substituting, in place of concepts, inborn and acquired sensorimotor category-detectors and category-names combined into propositions that define and describe further categories.

This article is a critique of: The "Green" and "Gold" Roads to Open Access: The Case for Mixing and Matching by Jean-Claude Guédon [1].

Harmonic Resonance Theory: An alternative to the "Neuron Doctrine" paradigm of neurocomputation to address the Gestalt properties of perception.

The evolu on of language made it possible for us to think aloud, share our thoughts, pass them on by word‐of‐mouth.

Searle's celebrated Chinese Room Argument has shaken the foundations of Artificial Intelligence. Many refutations have been attempted, but none seem convincing. This paper is an attempt to sort out explicitly the assumptions and the logical, methodological and empirical points of disagreement. Searle is shown to have underestimated some features of computer modeling, but the heart of the issue turns out to be an empirical question about the scope and limits of the purely symbolic model of the mind. Nonsymbolic modeling turns (...) out to be immune to the Chinese Room Argument. The issues discussed include the Total Turing Test, modularity, neural modeling, robotics, causality and the symbol-grounding problem. (shrink)

I am going to attempt to argue, given certain premises, there are reasons, not only empirical, but also logical, for expecting a certain division of labor in the processing of information by the human brain. This division of labor consists specifically of a functional bifurcation into what may be called, to a first approximation, "verbal" and "nonverbal" modes of information- processing. That this dichotomy is not quite satisfactory, however, will be one of the principal conclusions of this chapter, for I (...) shall attempt to show that metaphor, which in its most common guise is a literary, and hence a fortiori a "verbal" phenomenon, may in fact be more a function of the "nonverbal" than the "verbal" mode. (For alternative attempts to account for cognitive lateralization, see e.g. Bever, 1975; Wickelgren, 1975; Pendse, 1978.). (shrink)

2. Invariant Sensorimotor Features ("Affordances"). To say this is not to declare oneself a Gibsonian, whatever that means. It is merely to point out that what a sensorimotor system can do is determined by what can be extracted from its motor interactions with its sensory input. If you lack sonar sensors, then your sensorimotor system cannot do what a bat's can do, at least not without the help of instruments. Light stimulation affords color vision for those of us with the (...) right sensory apparatus, but not for those of us who are color-blind. The geometric fact that, when we move, the "shadows" cast on our retina by nearby objects move faster than the shadows of further objects means that, for those of us with normal vision, our visual input affords depth perception. From more complicated facts of projective and solid geometry it follows that a 3-dimensional shape, such as, say, a boomerang, can be recognized as being the same shape Ð and the same size Ð even though the size and shape of its shadow on our retinas changes as we move in relation to it or it moves in relation to us. Its shape is said to be invariant under these sensorimotor transformations, and our visual systems can detect and extract that invariance, and translate it into a visual constancy. So we keep seeing a boomerang of the same shape and size even though the shape and size of its retinal shadows keep changing. (shrink)

Turing's celebrated 1950 paper proposes a very general methodological criterion for modelling mental function: total functional equivalence and indistinguishability. His criterion gives rise to a hierarchy of Turing Tests, from subtotal ("toy") fragments of our functions (t1), to total symbolic (pen-pal) function (T2 -- the standard Turing Test), to total external sensorimotor (robotic) function (T3), to total internal microfunction (T4), to total indistinguishability in every empirically discernible respect (T5). This is a "reverse-engineering" hierarchy of (decreasing) empirical underdetermination of the theory (...) by the data. Level t1 is clearly too underdetermined, T2 is vulnerable to a counterexample (Searle's Chinese Room Argument), and T4 and T5 are arbitrarily overdetermined. Hence T3 is the appropriate target level for cognitive science. When it is reached, however, there will still remain more unanswerable questions than when Physics reaches its Grand Unified Theory of Everything (GUTE), because of the mind/body problem and the other-minds problem, both of which are inherent in this empirical domain, even though Turing hardly mentions them. (shrink)

A robot that is functionally indistinguishable from us may or may not be a mindless Zombie. There will never be any way to know, yet its functional principles will be as close as we can ever get to explaining the mind.

Computation is interpretable symbol manipulation. Symbols are objects that are manipulated on the basis of rules operating only on theirshapes, which are arbitrary in relation to what they can be interpreted as meaning. Even if one accepts the Church/Turing Thesis that computation is unique, universal and very near omnipotent, not everything is a computer, because not everything can be given a systematic interpretation; and certainly everything can''t be givenevery systematic interpretation. But even after computers and computation have been successfully distinguished (...) from other kinds of things, mental states will not just be the implementations of the right symbol systems, because of the symbol grounding problem: The interpretation of a symbol system is not intrinsic to the system; it is projected onto it by the interpreter. This is not true of our thoughts. We must accordingly be more than just computers. My guess is that the meanings of our symbols are grounded in the substrate of our robotic capacity to interact with that real world of objects, events and states of affairs that our symbols are systematically interpretable as being about. (shrink)

In this paper, we present a method for introducing law students to the writing of legal documents. The method uses a machine-readable representation of the legal knowledge to support document assembly and to help the students to understand how the assembly is performed. The knowledge base consists of enacted legislation, document templates, and assembly instructions. We propose a system called LEDAS (LEgal Document Assembly System) for the interactive assembly of legal documents. It guides users through the assembly process and provides (...) explanations of the interconnection between input data and claims stated in the document. The system acts as a platform for practicing drafting skills and has great potential as an education tool. It allows teachers to configure the system for the assembly of some particular type of legal document and then enables students to draft the documents by investigating which information is relevant for these documents and how the input data shape the final document. The generated legal document is complemented by a graphical representation of legal arguments expressed in the document. The system is based on existing legal standards to facilitate its introduction in the legal domain. Applicability of the system in the education of future lawyers is positively evaluated by the group of law students and their TA. (shrink)

Creativity may be a trait, a state or just a process defined by its products. It can be contrasted with certain cognitive activities that are not ordinarily creative, such as problem solving, deduction, induction, learning, imitation, trial and error, heuristics and "abduction," however, all of these can be done creatively too. There are four kinds of theories, attributing creativity respectively to (1) method, (2) "memory" (innate structure), (3) magic or (4) mutation. These theories variously emphasize the role of an unconscious (...) mind, innate constraints, analogy, aesthetics, anomalies, formal constraints, serendipity, mental analogs, heuristic strategies, improvisatory performance and cumulative collaboration. There is some virtue in each, but the best model is still the one implicit in Pasteur's dictum: "Chance favors the prepared mind." And because the exercise and even the definition of creativity requires constraints, it is unlikely that "creativity training" or an emphasis on freedom in education can play a productive role in this preparation. (shrink)

Europe is losing almost 50% of the potential return on its research investment until research funders and institutions mandate that all research findings must be made freely accessible to all would be users, webwide. It is not the number of articles published that reflects the return on Europe's research investment: A piece of research, if it is worth funding and doing at all, must not only be published, but used, applied and built upon by other researchers, worldwide. This is called (...) 'research impact' and a measure of it is the number of times an article is cited by other articles ('citation impact'). (shrink)

This article is a critique of: The "Green" and "Gold" Roads to Open Access: The Case for Mixing and Matching Jean-Claude Guédon Serials Review 30(4) 2004 http://dx.doi.org/10.1016/j.serrev.2004.09.005 Open Access (OA) means: free online access to all peer-reviewed journal articles.

My purpose is to explain, first, that there is an alternative to Harnad's version of the symbol grounding problem, which is known as the problem of primitives; second, that there is an alternative to his solution (which is externalist) in the form of a dispositional conception (which is internalist); and, third, that, while the TTT, properly understood, may provide partial and fallible evidence for the presence of similar mental powers, it cannot supply conclusive proof, because more than observable symbolic manipuation (...) and robotic behavior is involved here, as he admits (Harnad 1991). Carrying the problem further appears to require inference to the best explanation. (shrink)

When in 1979 Zenon Pylyshyn, associate editor of Behavioral and Brain Sciences (BBS, a peer commentary journal which I edit) informed me that he had secured a paper by John Searle with the unprepossessing title of [XXXX], I cannot say that I was especially impressed; nor did a quick reading of the brief manuscript -- which seemed to be yet another tedious "Granny Objection"[1] about why/how we are not computers -- do anything to upgrade that impression.

Let us simplify the problem of “consciousness” or “visual consciousness”: Seeing is feeling. The difference between an optical transducer/effector that merely interacts with optical input, and a conscious system that sees, is that there is something it feels like for that conscious system to see, and that system feels that feeling. All talk about “internal representations” and internal or external difference registration or detection, and so on, is beside the point. The point is that what is seen is felt, not (...) merely registered, processed, and acted upon. To explain consciousness in terms of sensorimotor action, one has to explain why and how any of that processing is felt; otherwise one is merely giving an optokinetic explanation of I/O (Input/Ouput) capacities (and of whether those capacities are actually or optimally generated by sensorimotor contingency processors, analog representations, symbolic representations, or other forms of internal structure/process), not of the fact that they are felt. Nor will it do to say “qualia are illusions.” Qualia are feelings. Am I under the illusion that I am seeing (i.e., feeling) something right now? What is the truth then? That I am not feeling, but merely acting? No, I'm afraid Descartes had it right. Certain things are not open to doubt. They either need to be explained, or passed over in silence, in favor of the unfelt correlated functions that we can explain (Harnad 1995; 2000; 2001). (shrink)

Steels & Belpaeme's (S&B's) simulations contain all the right components, but they are put together wrongly. Color categories are unrepresentative of categories in general and language is not merely naming. Language evolved because it provided a powerful new way to acquire categories (through instruction, rather than just the old way of other species, through trial-and-error experience). It did not evolve so that multiple agents looking at the same objects could let one another know which of the objects they had in (...) mind, co-coining names for them on the fly. (shrink)

In innate Categorical Perception (CP) (e.g., colour perception), similarity space is "warped," with regions of increased within-category similarity (compression) and regions of reduced between-category similarity (separation) enh ancing the category boundaries and making categorisation reliable and all-or-none rather than graded. We show that category learning can likewise warp similarity space, resolving uncertainty near category boundaries. Two Hard and two Easy texture learning tasks were compared: As predicted, there were fewer successful Learners with the Hard task, and only the successful Learners (...) of the Hard task exhibited CP. In a second experiment, the Easy task was made Hard by making the corrective feedback during learn ing only 90% reliable; this too generated CP. The results are discussed in relation to supervised, unsupervised and dual-mode models of category learning and representation.The world is full of things that vary in their similarity and interconfusability.O rganisms must somehow resolve this confusion, sorting and acting upon things adaptively. It might be important, for example, to learn which kinds of mushrooms are poisonous and which are safe to eat, minimising the confusion between them (Greco, Cangelosi & Harnad 1997). (shrink)

Some of the features of animal and human categorical perception (CP) for color, pitch and speech are exhibited by neural net simulations of CP with one-dimensional inputs: When a backprop net is trained to discriminate and then categorize a set of stimuli, the second task is accomplished by "warping" the similarity space (compressing within-category distances and expanding between-category distances). This natural side-effect also occurs in humans and animals. Such CP categories, consisting of named, bounded regions of similarity space, may be (...) the ground level out of which higher-order categories are constructed; nets are one possible candidate for the mechanism that learns the sensorimotor invariants that connect arbitrary names (elementary symbols?) to the nonarbitrary shapes of objects. This paper examines how and why such compression/expansion effects occur in neural nets. (shrink)

The Mind/Body Problem is about causation not correlation. And its solution will require a mechanism in which the mental component somehow manages to play a causal role of its own, rather than just supervening superflously on other, nonmental components that look, for all the world, as if they can do the full causal job perfectly well without it. Correlations confirm that M does indeed "supervene" on B, but causality is needed to show how/why M is not supererogatory; and that's the (...) hard part. (shrink)

The experimental analysis of naming behavior can tell us exactly the kinds of things Horne & Lowe (H & L) report here: (1) the conditions under which people and animals succeed or fail in naming things and (2) the conditions under which bidirectional associations are formed between inputs (objects, pictures of objects, seen or heard names of objects) and outputs (spoken names of objects, multimodal operations on objects). The "stimulus equivalence" that H & L single out is really just the (...) reflexive, symmetric and transitive property of pairwise associations among the above. This is real and of some interest, but it unfortunately casts very little light on symbolization and language in general, and naming capacity in particular. The associative equivalence between name and object is trivial in relation to the real question, which is: How do we (or any system that can do it) manage to connect names to things correctly (Harnad 1987, 1990, 1992)? The experimental analysis of naming behavior begs this question entirely, simply taking it for granted that the connection is somehow successfully accomplished. (shrink)

Human cognition is not an island unto itself. As a species, we are not Leibnizian Monads independently engaging in clear, Cartesian thinking. Our minds interact. That's surely why our species has language. And that interactivity probably constrains both what and how we think.

Explaining the mind by building machines with minds runs into the other-minds problem: How can we tell whether any body other than our own has a mind when the only way to know is by being the other body? In practice we all use some form of Turing Test: If it can do everything a body with a mind can do such that we can't tell them apart, we have no basis for doubting it has a mind. But what is (...) "everything" a body with a mind can do? Turing's original "pen-pal" version (the TT) only tested linguistic capacity, but Searle has shown that a mindless symbol-manipulator could pass the TT undetected. The Total Turing Test (TTT) calls for all of our linguistic and robotic capacities; immune to Searle's argument, it suggests how to ground a symbol manipulating system in the capacity to pick out the objects its symbols refer to. No Turing Test, however, can guarantee that a body has a mind. Worse, nothing in the explanation of its successful performance requires a model to have a mind at all. Minds are hence very different from the unobservables of physics (e.g., superstrings); and Turing Testing, though essential for machine-modeling the mind, can really only yield an explanation of the body. (shrink)

"in an academic generation a little overaddicted to "politesse," it may be worth saying that violent destruction is not necessarily worthless and futile. Even though it leaves doubt about the right road for London, it helps if someone rips up, however violently, a.

Peer Review and Copyright each have a double role: Formal refereeing protects (R1) the author from publishing and (R2) the reader from reading papers that are not of sufficient quality. Copyright protects the author from (C1) theft of text and (C2) theft of authorship. It has been suggested that in the electronic medium we can dispense with peer review, "publish" everything, and let browsing and commentary do the quality control. It has also been suggested that special safeguards and laws may (...) be needed to enforce copyright on the Net. I will argue, based on 20 years of editing Behavioral and Brain Sciences, a refereed (paper) journal of peer commentary, 8 years of editing Psycoloquy, a refereed electronic journal of peer commentary, and 1 year of implementing CogPrints, an electronic archive of unrefereed preprints and refereed reprints in the cognitive sciences modeled on the Los Alamos Physics Eprint Archive, that (i) peer commentary is a supplement, not a substitute, for peer review, (ii) the authors of refereed papers, who get and seek no royalties from the sale of their texts, only want protection from theft of authorship on the Net, not from theft of text, which is a victimless crime, and hence (iii) the trade model (subscription, site license or pay- per-view) should be replaced by author page-charges to cover the much reduced cost of implementing peer review, editing and archiving on the Net, in exchange for making the learned serial corpus available for free for all forever. (shrink)