The computational paradigm, which has dominated psychology and artificial intelligence since the cognitive revolution, has been a source of intense debate. Recently, several cognitive scientists have argued against this paradigm, not by objecting to computation, but rather by objecting to the notion of representation. Our analysis of these objections reveals that it is not the notion of representation per se that is causing the problem, but rather specific properties of representations as they are used in various psychological theories. Our analysis (...) suggests that all theorists accept the idea that cognitive processing involves internal information-carrying states that mediate cognitive processing. These mediating states are a superordinate category of representations. We discuss five properties that can be added to mediating states and examine their importance in various cognitive models. Finally, three methodological lessons are drawn from our analysis and discussion. (shrink)

Advocates of dynamic systems have suggested that higher mental processes are based on continuous representations. In order to evaluate this claim, we first define the concept of representation, and rigorously distinguish between discrete representations and continuous representations. We also explore two important bases of representational content. Then, we present seven arguments that discrete representations are necessary for any system that must discriminate between two or more states. It follows that higher mental processes require discrete representations. We also argue that discrete (...) representations are more influenced by conceptual role than continuous representations. We end by arguing that the presence of discrete representations in cognitive systems entails that computationalism (i.e., the view that the mind is a computational device) is true, and that cognitive science should embrace representational pluralism. (shrink)

Representation is a central part of models in cognitive science, but recently this idea has come under attack. Researchers advocating perceptual symbol systems, situated action, embodied cognition, and dynamical systems have argued against central assumptions of the classical representational approach to mind. We review the core assumptions of the dominant view of representation and the four suggested alternatives. We argue that representation should remain a core part of cognitive science, but that the insights from these alternative approaches must be incorporated (...) into models of cognitive processing. (shrink)

We argue that the dynamical and computational hypotheses are compatible and in fact need each other: they are about different aspects of cognition. However, only computationalism is about the information-processing aspect. We then argue that any form of information processing relying on matching and comparing, as cognition does, must use discrete representations and computations defined over them.

Analogical reminding in humans and machines is a great source for chance discoveries because analogical reminding can produce representational change and thereby produce insights. Here, we present a new kind of representational change associated with analogical reminding called packing. We derived the algorithm in part from human data we have on packing. Here, we explain packing and its role in analogy making, and then present a computer model of packing in a micro-domain. We conclude that packing is likely used in (...) human chance discoveries, and is needed if our machines are to make their own chance discoveries. (shrink)

The perceptual symbol system view assumes that perceptual representations have a role-argument structure. A role-argument structure is often incorporated into amodal symbol systems in order to explain conceptual functions like abstraction and rule use. The power of perceptual symbol systems to support conceptual functions is likewise rooted in its use of structure. On Barsalou's account, this capacity to use structure (in the form of frames) must be innate.

It is possible to survey humankind and be proud, even to smile, for we accomplish great things. Art and science are two notable worthy human accomplishments. Consonant with art and science are some of the ways we treat each other. Sacrifice and heroism are two admirable human qualities that pervade human interaction. But, as everyone knows, all this goodness is more than balanced by human depravity. Moral corruption infests our being. Why?

This chapter contains sections titled: The Allure of Monsters Explaining the Allure: First Look Stalking the Deeper Reasons Closing in for the Kill Removing Empathy The Prison of Rules Conclusion.

Chalmers' anti-materialist arguments are an interesting twist on a well-known argument form, and his naturalistic dualism is exciting to contemplate. Nevertheless, we think we can save materialism from the Chalmerian attack. This is what we do in the present paper.

Tests of economic theory often focus on choice outcomes and find significant individual differences in these outcomes. This variability may mask universal psychological processes that lead to different choices because of differences across cultures in the information people have available when making decisions. On this view, decision making research within and across cultures must focus on the processes underlying choice.

Pothos suggests dispensing with the distinction between rules and similarity, without defining what is meant by either term. We agree that there are problems with the distinction between rules and similarity, but believe these will be solved only by exploring the representations and processes underlying cases purported to involve rules and similarity.

Except for a patina of twenty-first century modernity, in the form of logic and language, philosophy is exactly the same now as it ever was; it has made no progress whatsoever. We philosophers wrestle with the exact same problems the Pre-Socratics wrestled with. Even more outrageous than this claim, though, is the blatant denial of its obvious truth by many practicing philosophers. The No-Progress view is explored and argued for here. Its denial is diagnosed as a form of anosognosia, a (...) mental condition where the affected person denies there is any problem. The theories of two eminent philosophers supporting the No-Progress view are also examined. The final section offers an explanation for philosophy 's inability to solve any philosophical problem, ever. The paper closes with some reflections on philosophy 's future. (shrink)

In Sisyphus's Boulder, Eric Dietrich and Valerie Hardcastle argue that we will never get such a theory because consciousness has an essential property that..

This paper offers an explanation for why some parts of philosophy have made no progress. Philosophy has made no progress because it cannot make progress. And it cannot because of the nature of the phenomena philosophy is tasked with explaining—all of it involves consciousness. Here, it will not be argued directly that consciousness is intractable. Rather, it will be shown that a specific version of the problem of consciousness is unsolvable. This version is the Problem of the Subjective and Objective. (...) Then it is argued that the unsolvability of this latter problem is why there are other unsolvable philosophy problems. (shrink)

This paper examines three cases of the clash between science and philosophy: Zeno’s paradoxes, the Frame Problem, and a recent attempt to experimentally refute skepticism. In all three cases, the relevant science claims to have resolved the purported problem. The sciences, construing the term broadly, are mathematics, artificial intelligence, and psychology. The goal of this paper is to show that none of the three scientific solutions work. The three philosophical problems remain as vibrant as ever in the face of robust (...) scientific attempts to dispel them. The paper concludes by examining some consequences of this persistence. (shrink)

Replicating or exceeding human intelligence, not just in particular domains but in general, has always been a major goal of Artificial Intelligence (AI). We argue here that “human intelligence” is not only ill-defined, but often conflated with broader aspects of human psychology. Standard arguments for replicating it are morally unacceptable. We then suggest a reframing: that the proper goal of AI is not to replicate humans, but to complement them by creating diverse intelligences capable of collaborating with humans. This goal (...) renders issues of theory of mind, empathy, and caring, or community engagement, central to AI. It also challenges AI to better understand the circumstances in which human intelligence, including human moral intelligence, fails. (shrink)

Flipping convention on its head, Eric Dietrich argues that science uncovers awe-inspiring, enduring mysteries, while religion, regarded as the source for such mysteries, is a biological phenomenon. Just like spoken language, Dietrich shows that religion is an evolutionary adaptation. Science is the source of perplexing yet beautiful mysteries, however natural the search for answers may be to human existence. _Excellent Beauty_ undoes our misconception of scientific inquiry as an executioner of beauty, making the case that science has (...) won the battle with religion so thoroughly it can now explain why religion persists. The book also draws deep lessons for human flourishing from the very existence of scientific mysteries. It is these latter wonderful, completely _public_ truths that constitute some strangeness in the proportion, revealing a universe worthy of awe and wonder. (shrink)

Can computers think? This book is intended to demonstrate that thinking, understanding, and intelligence are more than simply the execution of algorithms--that is, that machines cannot think. Written and edited by leaders in the fields of artificial intelligence and the philosophy of computing.

Recently, on the History Channel, artificial intelligence (AI) was singled out, with much wringing of hands, as one of the seven possible causes of the end of human life on Earth. I argue that the wringing of hands is quite inappropriate: the best thing that could happen to humans, and the rest of life of on planet Earth, would be for us to develop intelligent machines and then usher in our own extinction.

This paper argues for a noncognitiveist computationalism in the philosophy of mind. It further argues that both humans and computers have intentionality, that is, their mental states are semantical -- they are about things in their worlds.

The open-domain Frame Problem is the problem of determining what features of an open task environment need to be updated following an action. Here we prove that the open-domain Frame Problem is equivalent to the Halting Problem and is therefore undecidable. We discuss two other open-domain problems closely related to the Frame Problem, the system identification problem and the symbol-grounding problem, and show that they are similarly undecidable. We then reformulate the Frame Problem as a quantum decision problem, and show (...) that it is undecidable by any finite quantum computer. (shrink)

Sometimes analogy researchers talk as if the freshness of an experience of analogy resides solely in seeing that something is like something else -- seeing that the atom is like a solar system, that heat is like flowing water, that paint brushes work like pumps, or that electricity is like a teeming crowd. But analogy is more than this. Analogy isn't just seeing that the atom is like a solar system; rather, it is seeing something new about the atom, an (...) observation enabled by 'looking' at atoms from the perspective of one's understanding of solar systems. The question for analogy researchers then is this: Where does this new knowledge about atoms come from? How can an analogy provide new knowledge and new understanding? (shrink)

There is a prevalent notion among cognitive scientists and philosophers of mind that computers are merely formal symbol manipulators, performing the actions they do solely on the basis of the syntactic properties of the symbols they manipulate. This view of computers has allowed some philosophers to divorce semantics from computational explanations. Semantic content, then, becomes something one adds to computational explanations to get psychological explanations. Other philosophers, such as Stephen Stich, have taken a stronger view, advocating doing away with semantics (...) entirely. This paper argues that a correct account of computation requires us to attribute content to computational processes in order to explain which functions are being computed. This entails that computational psychology must countenance mental representations. Since anti-semantic positions are incompatible with computational psychology thus construed, they ought to be rejected. Lastly, I argue that in an important sense, computers are not formal symbol manipulators. (shrink)

It is shown that the Fodor's interpretation of the frame problem is the central indication that his version of the Modularity Thesis is incompatible with computationalism. Since computationalism is far more plausible than this thesis, the latter should be rejected.

A recent issue of Time magazine (March 29, 1999) was devoted to the twenty greatest "thinkers" of the twentieth century -- scientists, inventors, and engineers. There is one interesting omission: there are no cognitive psychologists or cognitive scientists. (Cognitive science is an amalgam of cognitive, neuro, and developmental psychology, artificial intelligence, philosophy, linguistics, biology, and anthropology.) Freud is there, to be sure. But, while he was very influential, it is not even clear that he was a scientist, let alone a (...) cognitive scientist. There are those who regard Freud as somewhere between incompetent and a charlatan (see Glymour, 1988). In any case, though Freud's positive proposal for the mind's architecture -- namely, that it contains the unconscious -- seems correct as far as it goes, it does appear that all the details are wrong. For example: (1) there is a lot more to the mind than the mere unconscious; (2) it is doubtful that there is an id, ego, and superego; (3) most dreams may very likely be meaningless; and (4) human motivation, even unconscious motivation, is about a lot more than sex. In the end, because he was most interested in certain kinds of human mental malfunctioning, Freud is probably best thought of as a physician, a proponent and early explorer of human mental health; he was not an experimental cognitive psychologist. (shrink)

True contradictions are taken increasingly seriously by philosophers and logicians. Yet, the belief that contradictions are always false remains deeply intuitive. This paper confronts this belief head-on by explaining in detail how one specific contradiction is true. The contradiction in question derives from Priest's reworking of Berkeley's argument for idealism. However, technical aspects of the explanation offered here differ considerably from Priest's derivation. The explanation uses novel formal and epistemological tools to guide the reader through a valid argument with, not (...) just true, but eminently acceptable premises, to an admittedly unusual conclusion: a true contradiction. The novel formal and epistemological tools concern points of view and changes in points of view. The result is an understanding of why the contradiction is true. (shrink)

The sciences occasionally generate discoveries that undermine their own assumptions. Two such discoveries are characterized here: the discovery of apophenia by cognitive psychology and the discovery that physical systems cannot be locally bounded within quantum theory. It is shown that such discoveries have a common structure and that this common structure is an instance of Priest’s well-known Inclosure Schema. This demonstrates that science itself is dialetheic: it generates limit paradoxes. How science proceeds despite this fact is briefly discussed, as is (...) the connection between our results and the realism-antirealism debate. We conclude by suggesting a position of epistemic modesty. (shrink)

Mostly philosophers cause trouble. I know because on alternate Thursdays I am one -- and I live in a philosophy department where I watch all of them cause trouble. Everyone in artificial intelligence knows how much trouble philosophers can cause (and in particular, we know how much trouble one philosopher -- John Searle -- has caused). And, we know where they tend to cause it: in knowledge representation and the semantics of data structures. This essay is about a recent case (...) of this sort of thing. One of the take-home messages will be that AI ought to redouble its efforts t o understand concepts. (shrink)

This book surveys and examines the most famous philosophical arguments against building a machine with human-level intelligence. From claims and counter-claims about the ability to implement consciousness, rationality, and meaning, to arguments about cognitive architecture, the book presents a vivid history of the clash between the philosophy and AI. Tellingly, the AI Wars are mostly quiet now. Explaining this crucial fact opens new paths to understanding the current resurgence AI (especially, deep learning AI and robotics), what happens when philosophy meets (...) science, and the role of philosophy in the culture in which it is embedded. -/- Organising the arguments into four core topics - 'Is AI possible', 'Architectures of the Mind', 'Mental Semantics and Mental Symbols' and 'Rationality and Creativity' - this book shows the debate that played out between the philosophers on both sides of the question, and, as well, the debate between philosophers and AI scientists and engineers building AI systems. Up-to-date and forward-looking, the book is packed with fresh insights and supporting material, including: -/- - Accessible introductions to each war, explaining the background behind the main arguments against AI - Each chapter details what happened in the AI wars, the legacy of the attacks, and what new controversies are on the horizon. - Extensive bibliography of key readings. (shrink)

Concern over the nature of AI is, for the tastes many AI scientists, probably overdone. In this they are like all other scientists. Working scientists worry about experiments, data, and theories, not foundational issues such as what their work is really about or whether their discipline is methodologically healthy. However, most scientists aren’t in a field that is approximately fifty years old. Even relatively new fields such as nonlinear dynamics or branches of biochemistry are in fact advances in older established (...) sciences and are therefore much more settled. Of course, by stretching things, AI can be said to have a history reaching back t o Charles Babbage, and possibly back beyond that to Leibnitz. However, all of that is best viewed as prelude. AI’s history is punctuated with the invention of the computer (and, if one wants t o stretch our history back to the 1930s, the development of the notion of computation by Turing, Church, and others). Hence, AI really began (or began in earnest) sometime in the late 1940s or early 1950s (some mark the conference a t Dartmouth in the summer of 1957 as the moment of our birth). And since those years we simply have not had time to settle into a routine science attacking reasonably well understood questions (for example, many of the questions some of us regard as supreme are regarded by others as inconsequential or mere excursions). (shrink)

Under the Superstition Mountains in central Arizona toil those who would rob humankind o f its humanity. These gray, soulless monsters methodically tear away at our meaning, our subjectivity, our essence as transcendent beings. With each advance, they steal our freedom and dignity. Who are these denizens of darkness, these usurpers of all that is good and holy? None other than humanity’s arch-foe: The Cognitive Scientists -- AI researchers, fallen philosophers, psychologists, and other benighted lovers of computers. Unless they are (...) stopped, humanity -- you and I -- will soon be nothing but numbers and algorithms locked away on magnetic tape. (shrink)

The perennial nature of some of philosophy’s deepest problems is a puzzle. Here, one problem, the realism–anti-realism debate, and one type of explanation for its longevity, are examined. It is argued that realism and anti-realism form a dialetheic pair: While they are in fact each other’s logical opposite, nevertheless, both are true (and both false). First, several reasons why one might think such a thing are presented. These reasons are merely the beginning, however. In the following sections, the dialetheic conclusion (...) is directly argued for by showing how realism and anti-realism satisfy Priest’s “inclosure schema”. In the last section and the conclusion, the conscious mind’s role in creating realism and anti-realism is discussed. This role further supports the conclusion that realism and anti-realism form a dialetheic pair. (shrink)

In mid-May of 2001, I attended a fascinating workshop at Cold Spring Harbor Labs. The conference was held at the lab's Banbury Center, an elegant mansion and its beautiful surrounding estate, located on Banbury Lane, in the outskirts of Lloyd Harbor, overlooking the north shore of Long Island in New York. The estate was formerly owned by Charles Sammis Robertson. In 1976, Robertson donated his estate, and an endowment for its upkeep, to the Lab. The donation included the Robertson's mansion, (...) now called Robertson House, and a large, seven-car garage that would become the actual conference center. The Center was opened on Sunday, June 14, 1977, by Francis Crick who gave a talk entitled "How Scientists Work." For us, Banbury was an idyllic location with great food where we could talk about the most difficult problem in all o f science: what is the nature and cause of consciousness? (shrink)

Any time you have philosophers working on a problem, you know you’ve got troubles. If a question has attracted the attention of the philosophers that means that either it is intractably difficult with convolutions and labyrinthine difficulties that would make other researchers blanch, or that it is just flat out impossible to solve. Impossible problems masquerade as intractable problems until someone either proves the problem is impossible (which can only happen in mathematics), or someone shows all solutions to the problem (...) violate laws of physics (like the perpetual motion machine, for example), or until enough people fail so that declaring defeat is a reasonable move. The problem of consciousness is prototypical of this latter case. Indeed, one might say that it is the Platonic ideal of such a problem. The mere fact that philosophers wrestle with the problem of consciousness should be regarded by psychologists of all stripes as extremely bad news. If the philosophers can’t make any headway, psychologists are doomed. (shrink)

Beginning with the paradoxes of zombie twins, we present an argument that dualism is both true and false. We show that avoiding this contradiction is impossible. Our diagnosis is that consciousness itself engenders this contradiction by producing contradictory points of view. This result has a large effect on the realism/anti-realism debate, namely, it suggests that this debate is intractable, and furthermore, it explains why this debate is intractable. We close with some comments on what our results mean for metaphysics and (...) philosophy, in general. (shrink)

The purpose of this paper is to present two kinds of analogical representational change, both occurring early in the analogy-making process, and then, using these two kinds of change, to present a model unifying one sort of analogy-making and categorization. The proposed unification rests on three key claims: (1) a certain type of rapid representational abstraction is crucial to making the relevant analogies (this is the first kind of representational change; a computer model is presented that demonstrates this kind of (...) abstraction), (2) rapid abstractions are induced by retrieval across large psychological distances, and (3) both categorizations and analogies supply understandings of perceptual input via construing, which is a proposed type of categorization (this is the second kind of representational change). It is construing that finalizes the unification. (shrink)

O'Brien & Opie run into conceptual problems trying to equate stable patterns of neural activation with phenomenal experiences. They also seem to make a logical mistake in thinking that the brute association between stable neural patterns and phenomenal experiences implies that they are identical. In general, the authors do not provide us with a story as to why stable neural patterns constitute phenomenal experience.

I find it interesting that AI researchers don't use concepts very often in their theorizing. No doubt they feel no pressure to. This is because most AI researchers do use representations which allow a system to chunk up its environment, and basically all we know about concepts is that they are representations which allow a system to chunk up its environment.

Good sciences have good metaphors. Indeed, good sciences are good because they have good metaphors. AI could use more good metaphors. In this editorial, I would like to propose a new metaphor to help us understand intelligence. Of course, whether the metaphor is any good or not depends on whether it actually does help us. (What I am going to propose is not something opposed to computationalism -- the hypothesis that cognition is computation. Noncomputational metaphors are in vogue these days, (...) and to date they have all been equally plausible and equally successful. And, just to be explicit, I do not mean “IQ” by “intelligence.” I am using “intelligence” in the way AI uses it: as a semi-techical term referring to a general property of all intelligent systems, animal (including humans), or machine, alike.). (shrink)

In mid-May of 2001, I attended a fascinating workshop at Cold Spring Harbor Labs. The conference was held at the lab's Banbury Center, an elegant mansion and its beautiful surrounding estate, located on Banbury Lane, in the outskirts of Lloyd Harbor, overlooking the north shore of Long Island in New York. The estate was formerly owned by Charles Sammis Robertson. In 1976, Robertson donated his estate, and an endowment for its upkeep, to the Lab. The donation included the Robertson's mansion, (...) now called Robertson House, and a large, seven-car garage that would become the actual conference center. The Center was opened on Sunday, June 14, 1977, by Francis Crick who gave a talk entitled "How Scientists Work." For us, Banbury was an idyllic location with great food where we could talk about the most difficult problem in all o f science: what is the nature and cause of consciousness? (shrink)