The most fundamental changes of information exchange and communication in society today have been caused by the fast and thorough penetration of all facets of life through networked computers and mobile phones, which will both soon merge with our traditional TV. In this report, these developments will be discussed on four different levels: individuals, groups, organisations and networks. Furthermore contradictory developmental patterns are considered: global versus regional development, entrepreneurship on different scales, data availability versus data security, reality versus virtuality, education, (...) and the ethics of multimedia and the Internet. (shrink)
In this paper, the concept of Human-Centred Technology will be described with regard to the different dimensions of workplace, groupwork and networks and in terms of the frameworks of both society and the natural environment. These different aspects of Human-Centred Systems will be illustrated by a series of case studies representing several European countries. The report covers a wide range of research fields. The emphasis is on technology: the roles of control and information technology in enterprises today â including issues (...) of applying AI â and the strategies of designing and implementing technology taking into account the specific aspects which characterize human-centred systems. (shrink)
Richard Brandt is one of the most eminent and influential of contemporary moral philosophers. His work has been concerned with how to justify what is good or right not by reliance on intuitions or theories about what moral words mean but by the explanation of moral psychology and the description of what it is to value something, or to think it immoral. His approach thus stands in marked contrast to the influential theories of John Rawls. The essays reprinted in (...) this collection span a period of almost 30 years and include many classic pieces in metaethical and normative ethical theory. The collection is aimed at both those moral philosophers familiar with Brandt's work and at those philosophers who may be largely unfamiliar with his work. The latter group will be struck by the lucid unpretentious style and the cumulative weight of Brandt's contributions to topics that remain at the forefront of moral philosophy. (shrink)
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. (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...
Richard Brandt is one of the most influential moral philosophers of the second half of the twentieth century. He is especially important in the field of ethics for his lucid and systematic exposition of utilitarianism. This new book represents in some ways a summation of his views and includes many useful applications of his theory. The focus of the book is how value judgments and moral belief can be justified. More generally, the book assesses different moral systems and theories (...) of justice, and considers specific problems such as the optimal level of charity and the moral tenability of the criminal law. This book will be essential reading for all professional philosophers concerned with ethics, and will prove helpful to students as well. (shrink)
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. (shrink)
In the theory of judgment aggregation, it is known for which agendas of propositions it is possible to aggregate individual judgments into collective ones in accordance with the Arrow-inspired requirements of universal domain, collective rationality, unanimity preservation, nondictatorship and propositionwise independence. But it is only partially known for which agendas it is possible to respect additional requirements, notably non-oligarchy, anonymity, no individual veto power, or implication preservation. We fully characterize the agendas for which there are such possibilities, thereby answering the (...) most salient open questions about propositionwise judgment aggregation. Our results build on earlier results by Nehring and Puppe (2002), Nehring (2006) and Dietrich and List (2007a). (shrink)
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. (shrink)
Bayesian epistemology tells us with great precision how we should move from prior to posterior beliefs in light of new evidence or information, but says little about where our prior beliefs come from. It offers few resources to describe some prior beliefs as rational or well-justified, and others as irrational or unreasonable. A different strand of epistemology takes the central epistemological question to be not how to change one’s beliefs in light of new evidence, but what reasons justify a given (...) set of beliefs in the first place. We offer an account of rational belief formation that closes some of the gap between Bayesianism and its reason-based alternative, formalizing the idea that an agent can have reasons for his or her (prior) beliefs, in addition to evidence or information in the ordinary Bayesian sense. Our analysis of reasons for belief is part of a larger programme of research on the role of reasons in rational agency (Dietrich and List, Nous, 2012a, in press; Int J Game Theory, 2012b, in press). (shrink)
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)
There are both externalist and internalist theories of the phenomenal content of conscious experiences. Externalists like Dretske and Tye treat the phenomenal content of conscious states as representations of external properties (and events). Internalists think that phenomenal conscious states are reducible to electrochemical states of the brain in the style of the type-type identity theory. In this paper, we side with the representationalists and visit a dispute between them over the test case of Swampman. Does Swampman have conscious phenomenal (...) states or not? Dretske and Tye disagree on this issue. We try to settle the dispute in favor of Dretske's theory (to our own surprise). (shrink)
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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 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.
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.
The naturalistic fallacy is mentionedfrequently by evolutionary psychologists as anerroneous way of thinking about the ethicalimplications of evolved behaviors. However,evolutionary psychologists are themselvesconfused about the naturalistic fallacy and useit inappropriately to forestall legitimateethical discussion. We briefly review what thenaturalistic fallacy is and why it is misusedby evolutionary psychologists. Then we attemptto show how the ethical implications of evolvedbehaviors can be discussed constructivelywithout impeding evolutionary psychologicalresearch. A key is to show how ethicalbehaviors, in addition to unethical behaviors,can evolve by natural selection.
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 <span class='Hi'>that</span> pervade human interaction. But, as everyone knows, all this goodness is more than balanced by human depravity. Moral corruption infests our being. Why?
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 (...) strange, almost mysterious, phenomenon of felt experience. (shrink)
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. (shrink)
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. (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)
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. (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)
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)
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)
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.
There is a surprising disconnect between formal rational choice theory and philosophical work on reasons. The one is silent on the role of reasons in rational choices, the other rarely engages with the formal models of decision problems used by social scientists. To bridge this gap, we propose a new, reason-based theory of rational choice. At its core is an account of preference formation, according to which an agent's preferences are determined by his or her motivating reasons, together with a (...) 'weighing relation' between different combinations of reasons. By explaining how someone's preferences may vary with changes in his or her motivating reasons, our theory illuminates the relationship between deliberation about reasons and rational choices. Although primarily positive, the theory can also help us think about how those preferences and choices ought to respond to normative reasons. (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)
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. (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)
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)
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.
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)
There is a surprising disconnect between formal rational choice theory and philosophical work on reasons. The one is silent on the role of reasons in rational choices, the other rarely engages with the formal models of decision problems used by social scientists. To bridge this gap, we propose a new, reason-based theory of rational choice. At its core is an account of preference formation, according to which an agent’s preferences are determined by his or her motivating reasons, together with a (...) ‘weighing relation’ between different combinations of reasons. By explaining how someone’s preferences may vary with changes in his or her motivating reasons, our theory illuminates the relationship between deliberation about reasons and rational choices. Although primarily positive, the theory can also help us think about how those preferences and choices ought to respond to normative reasons. (shrink)
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.
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. (shrink)
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 response to recent work on the aggregation of individual judgments on logically connected propositions into collective judgments, it is often asked whether judgment aggregation is a special case of Arrowian preference aggregation. We argue for the converse claim. After proving two impossibility theorems on judgment aggregation (using "systematicity" and "independence" conditions, respectively), we construct an embedding of preference aggregation into judgment aggregation and prove Arrow’s theorem (stated for strict preferences) as a corollary of our second result. Although we thereby (...) provide a new proof of Arrow’s theorem, our main aim is to identify the analogue of Arrow’s theorem in judgment aggregation, to clarify the relation between judgment and preference aggregation, and to illustrate the generality of the judgment aggregation model. JEL Classi…cation: D70, D71.. (shrink)
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.
We again press the case for computationalism by considering the latest in illconceived attacks on this foundational idea. We briefly but clearly define and delimit computationalism and then consider three authors from a new anticomputationalist collection.
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)
How can the propositional attitudes of several individuals be aggregated into overall collective propositional attitudes? Although there are large bodies of work on the aggregation of various special kinds of propositional attitudes, such as preferences, judgments, probabilities and utilities, the aggregation of propositional attitudes is seldom studied in full generality. In this paper, we seek to contribute to filling this gap in the literature. We sketch the ingredients of a general theory of propositional attitude aggregation and prove two new theorems. (...) Our first theorem simultaneously characterizes some prominent aggregation rules in the cases of probability, judgment and preference aggregation, including linear opinion pooling and Arrovian dictatorships. Our second theorem abstracts even further from the specific kinds of attitudes in question and describes the properties of a large class of aggregation rules applicable to a variety of belief-like attitudes. Our approach integrates some previously disconnected areas of investigation. (shrink)
Some features of the concept of a want, and of the explaining relation in which a want may stand to an action, have not received sufficient attention. In what follows we shall offer some suggestions and descriptions which may be one step toward remedy of this situationi. We shall be at pains to point out the extent to which the features we describe fit in with a conception of the explanations of actions conforming to the inferential (deductive or inductive) and (...) nomological patterns of scientific explanation, and also to point out where perhaps the fit is not so snug. (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 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.
The neutral and nearly neutral theories of molecular evolution are sometimes characterized as theories about drift alone, where drift is described solely as an outcome, rather than a process. We argue, however, that both selection and drift, as causal processes, are integral parts of both theories. However, the nearly neutral theory explicitly recognizes alleles and/or molecular substitutions that, while engaging in weakly selected causal processes, exhibit outcomes thought to be characteristic of random drift. A narrow focus on outcomes obscures the (...) significant role of weakly selected causal processes in the nearly neutral theory. (shrink)
Standard impossibility theorems on judgment aggregation over logically connected propositions either use a controversial systematicity condition or apply only to agendas of propositions with rich logical connections. Are there any serious impossibilities without these restrictions? We prove an impossibility theorem without systematicity that applies to most standard agendas: Every judgment aggregation function (with rational inputs and outputs) satisfying a condition called unbiasedness is dictatorial (or e¤ectively dictatorial if we remove one of the agenda conditions). Our agenda conditions are tight. Applied (...) illustratively to (strict) preference aggregation represented in our model, the result implies that every unbiased social welfare function with universal domain is e¤ectively dictatorial. Keywords: judgment aggregation, logic, impossibility, May’s neutrality.. (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.
In this paper, we present a simple axiomatic justification for indifference before opening, avoiding any expectation reasoning, which is often considered problematic in infinite cases. Although the two-envelope paradox assumes an expectation-maximizing agent, we show that analogous paradoxes arise for agents using difierent decision principles such as maximin and maximax, and that our justification for indifierence before opening applies here too.
Rational choice theory analyzes how an agent can rationally act, given his or her preferences, but says little about where those preferences come from. Instead, preferences are usually assumed to be …xed and exogenously given. We introduce a framework for conceptualizing preference formation and preference change. In our model, an agent’s preferences are based on certain ‘motivationally salient’properties of the alternatives over which the preferences are held. Preferences may change as new properties of the alternatives become salient or previously salient (...) ones cease to be so. We suggest that our approach captures endogenous preferences in various contexts, and helps to illuminate the distinction between formal and substantive concepts of rationality, as well as the role of perception in rational choice. (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)
Condorcet's famous jury theorem reaches an optimistic conclusion on the correctness of majority decisions, based on two controversial premises about voters: they are competent and vote independently, in a technical sense. I carefully analyse these premises and show that: (i) whether a premise is justified depends on the notion of probability considered and (ii) none of the notions renders both premises simultaneously justified. Under the perhaps most interesting notions, the independence assumption should be weakened.
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)
In the emerging literature on judgment aggregation over logically connected propositions, expert rights or liberal rights have not been investigated yet. A group making collective judgments may assign individual members or subgroups with expert knowledge on, or particularly a¤ected by, certain propositions the right to determine the collective judgment on those propositions. We identify a problem that generalizes Sen’s ‘liberal paradox’. Under plausible conditions, the assignment of rights to two or more individuals or subgroups is inconsistent with the unanimity principle, (...) whereby unanimously accepted propositions are collectively accepted. The inconsistency can be avoided if individual judgments or rights satisfy special conditions. (shrink)
If a group is modelled as a single Bayesian agent, what should its beliefs be? I propose an axiomatic model that connects group beliefs to beliefs of group members, who are themselves modelled as Bayesian agents, possibly with di¤erent priors and di¤erent information. Group beliefs are proven to take a simple multiplicative form if people’s information is independent, and a more complex form if information overlaps arbitrarily. This shows that group beliefs can incorporate all information spread over the individuals without (...) the individuals having to communicate their (possibly complex and hard-to-describe) private information; communicating prior and posterior beliefs su¢ ces. JEL classi…cation: D70, D71.. (shrink)
The article addresses the issue of rationing health care services, a topic currently being hotly debated in many countries. The author argues that the aspect of causal responsibility ought to play a decisive role in the allocation of limited medical resources. Starting out from Ronald Dworkin's distinction between option luck and brute luck, the appropriate and meaningful uses of the term causal responsibility are clarified first. A discussion of the conditions which might justify giving lower priority to patients whose illnesses (...) are the result of unhealthy behavior, like e.g. alcohol abuse, follows. Causal responsibility is then viewed in the context of private health insurance and the club model of organ donation. It is argued that individuals themselves are basically responsible for their decisions regarding insurance coverage and membership in organ donors' clubs. Causal responsibility is shown to be a more suitable criterion for rationing scarce medical resources than other criteria which might alternatively be considered, such as patients' age. (shrink)
According to standard rational choice theory, as commonly used in political science and economics, an agent’s fundamental preferences are exogenously …xed, and any preference change over decision options is due to Bayesian information learning. Although elegant and parsimonious, this model fails to account for preference change driven by experiences or psychological changes distinct from information learning. We develop a model of non-informational preference change. Alternatives are modelled as points in some multidimensional space, only some of whose dimensions play a role (...) in shaping the agent’s preferences. Any change in these ‘motivationally salient’ dimensions can change the agent’s preferences. How it does so is described by a new representation theorem. Our model not only captures a wide range of frequently observed phenomena, but also generalizes some standard representations of preferences in political science and economics. (shrink)
All existing impossibility theorems on judgment aggregation require individual and collective judgment sets to be consistent and complete (in some recent results with completeness relaxed to deductive closure), arguably a demanding rationality requirement. They do not carry over to aggregation functions mapping pro…les of (merely) consistent individual judgment sets to (merely) consistent collective ones. We prove that, whenever the agenda of propositions under consideration exhibits mild interconnections, any such aggregation function that is "neutral" between the acceptance and rejection of each (...) proposition is dictatorial. We relate this theorem to the literature. (shrink)
The new …eld of judgment aggregation aims to merge many individual sets of judgments on logically interconnected propositions into a single collective set of judgments on these propositions. Judgment aggregation has commonly been studied using classical propositional logic, with a limited expressive power and a problematic representation of conditional statements (“if P then Q”) as material conditionals. In this methodological paper, I present a simple uni…ed model of judgment aggregation in general logics. I show how many realistic decision problems can (...) be represented in it. This includes decision problems expressed in languages of classical propositional logic, predicate logic (e.g. preference aggregation problems), modal or conditional logics, and some multi-valued or fuzzy logics. I provide a list of simple tools for working with general logics, and I prove impossibility results that generalise earlier theorems. (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)
In the 1960s molecular population geneticists used Monte Carlo experiments to evaluate particular diffusion equation models. In this paper I examine the nature of this comparative evaluation and argue for three claims: first, Monte Carlo experiments are genuine experiments: second, Monte Carlo experiments can provide an important meansfor evaluating the adequacy of highly idealized theoretical models; and, third, the evaluation of the computational adequacy of a diffusion model with Monte Carlo experiments is significantlydifferent from the evaluation of the emperical adequacy (...) of the same diffusion model. (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)
The aggregation of individual judgments over interrelated propositions is a newly arising …eld of social choice theory. I introduce several independence conditions on judgment aggregation rules, each of which protects against a speci…c type of manipulation by agenda setters or voters. I derive impossibility theorems whereby these independence conditions are incompatible with certain minimal requirements. Unlike earlier impossibility results, the main result here holds for any (non-trivial) agenda. However, independence conditions arguably undermine the logical structure of judgment aggregation. I therefore (...) suggest restricting independence to "premises", which leads to a generalised premise-based procedure. This procedure is proven to be possible if the premises are logically independent. JEL Classi…cation Numbers: D70, D71, D79. (shrink)
In solving judgment aggregation problems, groups often face constraints. Many decision problems can be modelled in terms the acceptance or rejection of certain propositions in a language, and constraints as propositions that the decisions should be consistent with. For example, court judgments in breach-of-contract cases should be consistent with the constraint that action and obligation are necessary and su¢ - cient for liability; judgments on how to rank several options in an order of preference with the constraint of transitivity; and (...) judgments on budget items with budgetary constraints. Often more or less demanding constraints on decisions are imaginable. For instance, in preference ranking problems, the transitivity constraint is often constrasted with the weaker acyclicity constraint. In this paper, we make constraints explicit in judgment aggregation by relativizing the rationality conditions of consistency and deductive closure to a constraint set, whose variation yields more or less strong notions of rationality. We review several general results on judgment aggregation in light of such constraints. (shrink)
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 (...) strange, almost mysterious, phenomenon of felt experience. (shrink)
Under the independence and competence assumptions of Condorcet’s classical jury model, the probability of a correct majority decision converges to certainty as the jury size increases, a seemingly unrealistic result. Using Bayesian networks, we argue that the model’s independence assumption requires that the state of the world (guilty or not guilty) is the latest common cause of all jurors’ votes. But often – arguably in all courtroom cases and in many expert panels – the latest such common cause is a (...) shared ‘body of evidence’ observed by the jurors. In the corresponding Bayesian network, the votes are direct descendants not of the state of the world, but of the body of evidence, which in turn is a direct descendant of the state of the world. We develop a model of jury decisions based on this Bayesian network. Our model permits the possibility of misleading evidence, even for a maximally competent observer, which cannot easily be accommodated in the classical model. We prove that (i) the probability of a correct majority verdict converges to the probability that the body of evidence is not misleading, a value typically below 1; (ii) depending on the required threshold of ‘no reasonable doubt’, it may be impossible, even in an arbitrarily large jury, to establish guilt of a defendant ‘beyond any reasonable doubt’. (shrink)
