36 found
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  1. There Is No Progress in Philosophy.Eric Dietrich - 2011 - Essays in Philosophy 12 (2):9.
    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 (...)
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  2. Explanatory pluralism in cognitive science.Rick Dale, Eric Dietrich & Anthony Chemero - 2009 - Cognitive Science 33 (2):739-742.
    This brief commentary has three goals. The first is to argue that ‘‘framework debate’’ in cognitive science is unresolvable. The idea that one theory or framework can singly account for the vast complexity and variety of cognitive processes seems unlikely if not impossible. The second goal is a consequence of this: We should consider how the various theories on offer work together in diverse contexts of investigation. A final goal is to supply a brief review for readers who are compelled (...)
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  3. In defense of representation.Arthur B. Markman & Eric Dietrich - 2000 - Cognitive Psychology 40 (2):138--171.
    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 (...)
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  4. Discrete thoughts: Why cognition must use discrete representations.Eric Dietrich & Arthur B. Markman - 2003 - Mind and Language 18 (1):95-119.
    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 (...)
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  5. Computationalism.Eric Dietrich - 1990 - Social Epistemology 4 (2):135-154.
    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.
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  6. Semantics and the Computational Paradigm in Cognitive Psychology.Eric Dietrich - 1989 - Synthese 79 (1):119-141.
    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 (...)
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  7. How Much Like Us Do We Want AIs to Be?Eric Dietrich, Chris Fields, John P. Sullins, Bram Van Heuveln & Robin Zebrowski - 2024 - Techné Research in Philosophy and Technology 28 (2):137-168.
    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 (...)
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  8. Homo sapiens 2.0 Why we should build the better robots of our nature.Eric Dietrich - 2011 - In Michael Anderson & Susan Leigh Anderson (eds.), Machine Ethics. Cambridge Univ. Press.
    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?
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  9. Analogy and Conceptual Change, or You can't step into the same mind twice.Eric Dietrich - 2000 - In Eric Dietrich Art Markman (ed.), Cognitive Dynamics: Conceptual change in humans and machines. Lawrence Erlbaum. pp. 265--294.
    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 (...)
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  10.  51
    When Science Confronts Philosophy: Three Case Studies.Eric Dietrich - 2020 - Axiomathes 30 (5):479-500.
    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 (...)
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  11. After the Humans are Gone.Eric Dietrich - 2007 - Philosophy Now 61 (May/June):16-19.
    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.
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  12. Why Philosophy Makes No Progress.Eric Dietrich - 2023 - Global Philosophy 33 (2):1-14.
    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. (...)
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  13. Role of the Frame Problem in Fodor's Modularity Thesis.Eric Dietrich & Chris Fields - 1996 - In Kenneth M. Ford & Zenon W. Pylyshyn (eds.), The Robot's Dilemma Revisited: The Frame Problem in Artificial Intelligence. Ablex.
    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.
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  14. Equivalence of the Frame and Halting Problems.Eric Dietrich & Chris Fields - 2020 - Algorithms 13 (175):1-9.
    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 (...)
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  15. Science Generates Limit Paradoxes.Eric Dietrich & Chris Fields - 2015 - Axiomathes 25 (4):409-432.
    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 (...)
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  16. The Prepared Mind: The Role of Representational Change in Chance Discovery.Eric Dietrich, Arthur B. Markman & Michael Winkley - 2003 - In Yukio Ohsawa Peter McBurney (ed.), Chance Discovery by Machines. Springer-Verlag, pp. 208-230..
    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 (...)
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  17. Excellent Beauty: The Naturalness of Religion and the Unnaturalness of the World.Eric Dietrich - 2015 - Columbia University Press.
    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 (...)
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  18. Let's dance! The equivocation in Chalmers' dancing qualia argument.B. van Heuveln, Eric Dietrich & M. Oshima - 1998 - Minds and Machines 8 (2):237-249.
    David Chalmers' dancing qualia argument is intended to show that phenomenal experiences, or qualia, are organizational invariants. The dancing qualia argument is a reductio ad absurdum, attempting to demonstrate that holding an alternative position, such as the famous inverted spectrum argument, leads one to an implausible position about the relation between consciousness and cognition. In this paper, we argue that Chalmers' dancing qualia argument fails to establish the plausibility of qualia being organizational invariants. Even stronger, we will argue that the (...)
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  19. Realism and Anti-Realism Are Both True (and False).Eric Dietrich - 2020 - Mind and Matter 18 (2):121-148.
    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 (...)
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  20. AI and the Mechanistic Forces of Darkness.Eric Dietrich - 1995 - J. Of Experimental and Theoretical AI 7 (2):155-161.
    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 (...)
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  21. The Bishop and Priest: Toward a point-of-view based epistemology of true contradictions.Eric Dietrich - 2008 - Logos Architekton 2 (2):35-58..
    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 (...)
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  22. The Paradox of Consciousness and the Realism/Anti-Realism Debate.Eric Dietrich & Julietta Rose - 2009 - Logos Architekton 3 (1):7-37.
    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 (...)
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  23. Some strangeness in the proportion, or how to stop worrying and learn to love the mechanistic forces of darkness.Eric Dietrich - 2008 - Phenomenology and the Cognitive Sciences 7 (3):349-352.
    Understanding humans requires viewing them as mechanisms of some sort, since understanding anything requires seeing it as a mechanism. It is science’s job to reveal mechanisms. But science reveals much more than that: it also reveals enduring mystery—strangeness in the proportion. Concentrating just on the scientific side of Selinger’s and Engström’s call for a moratorium on cyborg discourse, I argue that this strangeness prevents cyborg discourse from diminishing us.
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  24. Whither structured representation?Arthur B. Markman & Eric Dietrich - 1999 - Behavioral and Brain Sciences 22 (4):626-627.
    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.
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  25. Concepts: Fodor's little semantic BBs of thought - A critical look at Fodor's theory of concepts -.Eric Dietrich - 2001 - J. Of Experimental and Theoretical AI 13 (2):89-94.
    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.
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  26. AI, Situatedness, Creativity, and Intelligence; or the Evolution of the Little Hearing Bones.Eric Dietrich - 1996 - J. Of Experimental and Theoretical AI 8 (1):1-6.
    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, (...)
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  27. AI, Concepts, and the Paradox of Mental Representation, with a brief discussion of psychological essentialism.Eric Dietrich - 2001 - J. Of Exper. And Theor. AI 13 (1):1-7.
    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 (...)
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  28. (1 other version)Subvert the dominant paradigm!Eric Dietrich - 2002 - J. Of Experimental and Theoretical AI.
    We again press the case for computationalism by considering the latest in ill- conceived attacks on this foundational idea. We briefly but clearly define and delimit computationalism and then consider three authors from a new anti- computationalist collection.
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  29. Banbury Bound, or Can a machine be conscious?Eric Dietrich - 2001 - J. Of Experimental and Theoretical AI 13 (2):177-180.
    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, (...)
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  30. A Counterexample t o All Future Dynamic Systems Theories of Cognition.Eric Dietrich - 2000 - J. Of Experimental and Theoretical AI 12 (2):377-382.
    Years ago, when I was an undergraduate math major at the University of Wyoming, I came across an interesting book in our library. It was a book of counterexamples t o propositions in real analysis (the mathematics of the real numbers). Mathematicians work more or less like the rest of us. They consider propositions. If one seems to them to be plausibly true, then they set about to prove it, to establish the proposition as a theorem. Instead o f setting (...)
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  31. (1 other version)A Connecticut Yalie in King Descartes' Court.Eric Dietrich & Valerie Gray Hardcastle - 2002 - Newsletter of Cognitive Science Society (Now Defunct).
    What is consciousness? Of course, each of us knows, privately, what consciousness is. And we each think, for basically irresistible reasons, that all other conscious humans by and large have experiences like ours. So we conclude that we all know what consciousness is. It's the felt experiences of our lives. But that is not the answer we, as cognitive scientists, seek in asking our question. We all want to know what physical process consciousness is and why it produces this very (...)
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  32. Analogical insight: toward unifying categorization and analogy.Eric Dietrich - 2010 - Cognitive Processing 11 (4):331-346.
    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 (...)
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  33. The Ubiquity of Computation.Eric Dietrich - 1993 - Think (misc) 2 (June):27-29.
    For many years now, Harnad has argued that transduction is special among cognitive capacities -- special enough to block Searle's Chinese Room Argument. His arguments (as well as Searle's) have been important and useful, but not correct, it seems to me. Their arguments have provided the modern impetus for getting clear about computationalism and the nature of computing. This task has proven to be quite difficult. Which is simply to say that dealing with Harnad's arguments (as well as Searle's) has (...)
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  34. (1 other version)Review of David Chalmers, The Conscious Mind. [REVIEW]Eric Dietrich - 1998 - Minds and Machines 8 (3):441-461.
    When Charles Darwin died in April, 1882, he left behind a world changed forever. Because of his writings, most notably, of course, The Origin of Species, by 1882, evolution was an almost universally acknowledged fact. What remained in dispute, however, was how evolution occurred. So because of Darwin’s work, everyone accepted that new species emerge over time, yet few agreed with him that it was natural selection that powered the change, as Darwin hypothesized. Chalmers’ book, The Conscious Mind , reminds (...)
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  35. It Does So: Review of Jerry Fodor, The Mind Doesn't Work That Way. [REVIEW]Eric Dietrich - 2001 - AI Magazine 22 (4):121-24.
    Objections to AI and computational cognitive science are myriad. Accordingly, there are many different reasons for these attacks. But all of them come down to one simple observation: humans seem a lot smarter that computers -- not just smarter as in Einstein was smarter than I, or I am smarter than a chimpanzee, but more like I am smarter than a pencil sharpener. To many, computation seems like the wrong paradigm for studying the mind. (Actually, I think there are deeper (...)
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  36. Dynamic Systems and Paradise Regained, or How to avoid being a calculator. [REVIEW]Eric Dietrich - 1999 - J. Of Experimental and Theoretical AI 11 (4):473-478.
    The new kid on the block in cognitive science these days is dynamic systems. This way of thinking about the mind is, as usual, radically opposed to computationalism - - the hypothesis that thinking is computing. The use of dynamic systems is just the latest in a series of attempts, from Searle's Chinese Room Argument, through the weirdnesses of postmodernism, to overthrown computationalism, which as we all know is a perfectly nice hypothesis about the mind that never hurt anyone.
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