Eric Dietrich

What is it about serial killers that grips our imaginations? They populate some of our most important literature and art, and to this day, Jack the Ripper intrigues us. In this paper, we examine this phenomenon, exploring the idea that serial killers in part represent something in us that, if not good, is at least admirable. To get at this, we have to peel off layers of other causes of our attraction, for our attraction to serial killing is complex (it mixes with repulsion, too). For example, part of the attraction is curiosity associated with the pragmatic desire to understand serial killers. Another part is the allure of safe violence, the very same allure that causes us to slow down to look at traffic accidents and that makes movies like Saw box office gold. Once we are through the initial layers of attraction, we expose the one we are interested in. Humans are not really Homo sapiens (the wise human), but rather Homo oboediens (the rule‐following human), and these rules can become oppressive. Serial killers, properly sanitized, show us something, albeit in a twisted way, that we long for – a life unfettered by rules, a life where we can do exactly what we want. We close by noting the paradox that an actual serial killer is not free at all.

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

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.

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?

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.

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.

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 by these points to explore existing literature on the topic. Despite this literature, pluralism has garnered very little attention from broader cognitive science. We end by briefly considering what it might mean for theoretical cognitive science.

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.

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 gap in the argument cannot be closed

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.

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.

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 me of The Origin of Species . I have talked t o many people about The Conscious Mind and watched many philosophy students read it, and after they are done, they all take consciousness more seriously than they did before and they are all struck by its deep mystery, yet few accept Chalmers’ specific theory of consciousness and his explanation of its odd nature.

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.

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

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 and darker reasons why AI, especially, is so often the brunt of polemics, see Dietrich, 2000.) But the truth is this: AI is making exciting progress, and will one day make a robot as intelligent as a person; indeed the robot will be conscious. And all this is because of another truth: the computational paradigm is the best thing to come down the pike since the wheel.

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.

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.

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.).

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.

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?

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 out to prove propositions, the psychologists, neuroscientists, and other empirical types among us, set out to show that a proposition is supported by the data, and that it is the best such proposition so supported. The philosophers among us, when they are not causing trouble by arguing that AI is a dead end or that cognitive science can get along without representations, work pretty much like the mathematicians: we set out to prove certain propositions true on the basis of logic, first principles, plausible assumptions, and others' data. But, back to the book of real analysis counterexamples. If some mathematician happened t o think that some proposition about continuity, say, was plausibly true, he or she would then set out to prove it. If the proposition was in fact not a theorem, then a lot of precious time would be wasted trying to prove it. Wouldn't it be great to have a book that listed plausibly true propositions that were in fact not true, and listed with each such proposition a counterexample to it? Of course it would.