Volume 3, Number 5 May 2009 www.thereasoner.org ISSN 1757-0522 to new people; to the question “What do you do?” you proudly answer “Philosophy”; the regard is usually puzzled, so you promptly rectify: “Philosophy of science”; unfortunately, this doesn’t do any better. I also tried with ‘epistemology’, ‘methodology of science’, ‘conceptual problems in the sciences’ . . . Here is the second situation. You are chatting with old friends or yours, or with good acquaintances, and those people finally take the courage to ask you how you spend your day doing research in philosophy: “Do you sit and wait for illuminating philosophical thoughts to come?” Usually, finding out that you spend your time reading, writing, discussing, preparing seminars, talks and classes is quite disappointing to them. No philosophical ‘illumination’, after all . . . Last, try to explain to an immigration officer that even if you do research in philosophy of science, it doesn’t mean that you manipulate explosive materials or the like. Now, step back from the hilarity of the situations above. What philosophy is, even after more than twothousand years of philosophy, is far from being an obvious question, not to mention how contentious the answer is. I always thought that a good answer lies in the Greek origin of the word ‘philosophy’—i.e., love of knowledge—which gives the perspective one takes toward ‘things’ without fixing either the object or the scope of philosophy (and of philosophical questions). Thus, I feel somehow uncomfortable with views according to which, for instance, Contents §1 Editorial 1 §2 Features 2 §3 News 8 §4 What’s Hot in . . . 11 §5 Introducing ... 12 §6 Events 13 §7 Jobs 16 §8 Courses and Studentships 17 §1 Editorial It is with great pleasure that I return as guest editor. Before I leave you with this month’s interviewee Luciano Floridi, I’d like to share just a quick thought. It must have happened to other philosophers too— a slight sense of embarrassment and awkwardness when asked what philosophy is or what in fact we do when we do philosophy. Perhaps not with other academics, but this may happen in some everyday situations. Here are my favourite three situations. You are in a party and you are introducing yourself 1 into philosophy of information, or rather, how did you ‘invent’ it? LF: The Philosophy of Information (PI) has many roots and it is the result of a long process of ‘slow cooking’ in the philosophical pot. For some time I had been searching for an approach to some key philosophical questions (the nature of knowledge, the structure of reality, the difference between mental and artificial intelShould we then exclude very specific and concrete ligence, the ethical role of agents and so forth) which issues—e.g., what interpretation of probability best fits could be at the same time rigorous, in the best sense of cancer epidemiology—from the realm of the philosoph- our analytic tradition, non-psychologistic, in a Fregean ical problems? sense, conversant with our scientific knowledge, capaI promised that I’d be brief, so it’s time to wind up. ble of dealing with contemporary lively issues, and less This preamble was to say that I tried to turn those ques- prone to metaphysical armchair speculations and idtions to Luciano. For him, however, the task was even iosyncratic intuitions. I was looking for a concept of more challenging. If you had hard times explaining knowledge that was not obsessed with the knowing subwhat philosophy of science or philosophical logic is, try ject. And one day I realised that what I really had in with philosophy of information . . . mind was information. I was at Wolfson College, seating near the bank of the river Cherwell. It was 1999 Federica Russo and I gave a talk in London entitled “Should there be Philosophy, Louvain & Kent a Philosophy of Information?”. Once I saw the peak of the mountain all that remained to do was to plan the expedition as carefully as possible. So I’ve been climbing ever since. Deep down I’m a German philosopher, I §2 love being systematic and I love big projects. FR: Could you tell us what exactly ‘philosophy of Features information’ is? LF: On the one hand, PI is a way of doing philosoInterview with Luciano Floridi phy, by elaborating and applying information-theoretic Luciano Floridi is Professor of Philosophy at the and computational concepts, tools and theories to philoUniversity of Hertfordshire, where he holds the sophical problems. So PI is a method to deal with clasResearch Chair in Philosophy of Information, and sic and new problems. It goes hand in hand with what Fellow of St Cross College, University of Ox- some colleagues call formal epistemology, for example. ford. He is the founder and director of the Ox- On the other hand, PI is a new area of research, conford University Information Ethics research group, cerned with the critical investigation of the conceptual and best known for his research on the philos- nature and basic principles of information, including its ophy of information and on information ethics. dynamics, utilisation and sciences. PI is a new way of His forthcoming books are: The appropriating a very specific interpretation of the classic Philosophy of Information (OUP); ‘ti esti . . . ?’ (what is . . . ?) question. What is informaInformation, (OUP, VSI series); tion? PI seeks to answer such a basic question, not difand the Handbook of Information ferently from the way in which epistemology, for examand Computer Ethics (CUP). He is ple, seeks to answer the question ‘what is knowledge?’. currently President of the InternaThe great advantage is that ‘information’ is turning out tional Association for Computing to be a concept as fundamental and important as ‘being’, And Philosophy and principal in‘knowledge’, ‘life’, ‘intelligence’, ‘meaning’ or ‘good vestigator of the AHRC-funded reand evil’, all pivotal concepts with which it is interdesearch project on the construction of personal identities pendent and so equally worthy of autonomous investionline. In 2009, he became the first philosopher ever gation. It is also a more impoverished concept, in terms to be appointed Gauss Professor by the Academy of of which the other can be expressed and interrelated, Sciences in Göttingen, and was awarded the Barwise when not analysed. Medal by the American Philosophical Association for FR: What does it mean that philosophy of informahis foundational research in the philosophy of informa- tion ‘evolved’ from other areas such as philosophy of tion. artificial intelligence, logic of information, cybernetics, Federica Russo: It is now established tradition that social theory, ethics or the study of language and inforour interviewees tell us (briefly!) about their intellec- mation? Does it mean that philosophy of information tual history. Luciano, would you tell us how you got inherits the peculiar problems of all those disciplines [. . . ] philosophy is the study of problems which are ultimate, abstract and very general. These problems are concerned with the nature of existence, knowledge, morality, reason and human purpose. (Teichmann J. and Evans K. C., Philosophy: A Beginner’s Guide, Blackwell Publishing, 1999) 2 or that there is a substantial re-elaboration of their respective questions, or what? In other words, are there completely new philosophical questions, or are there old questions that require new answers in the light of the advancements of information science? LF: I would like to read the ‘or’ in the question as inclusive. PI is more like a philosophical paradigm. In the past, philosophers had to take care of the whole chain of knowledge production, from raw data to scientific theories, as it were. Throughout its history, philosophy has progressively identified classes of empirical and logicomathematical problems and outsourced their investigations to new disciplines. It has then returned to these disciplines and their findings for controls, clarifications, constraints, methods, tools and insights but philosophy itself consists of conceptual investigations whose essential nature is neither empirical nor logico-mathematical. To mis-paraphrase Hume: “if we take in our hand any volume, let us ask: Does it contain any abstract reasoning concerning quantity or number? Does it contain any experimental reasoning concerning matter of fact and existence?” If the answer is yes, then search elsewhere, because that is science, not yet philosophy. Philosophy is not a conceptual aspirin, a super-science, the manicure of language, or an intellectual cleaning-lady. It is the art of identifying conceptual problems and designing, proposing and evaluating explanatory models that seek to solve them. As conceptual engineering, it is the last stage of reflection, where the effort to provide meaning to life (or, to put it more dramatically, the semanticisation of Being) is pursued and kept open. Its critical and creative investigations tackle problems that are intrinsically capable of different and possibly irreconcilable solutions, problems that are genuinely open to debate and honest disagreement, even in principle. These investigations are often entwined with empirical and logico-mathematical issues and so scientifically constrained but, in themselves, they are neither. They constitute a space of inquiry broadly definable as normative. It is an open space: anyone can step into it, no matter what the starting point is, and disagreement is always possible. It is also a dynamic space, for when its cultural environment changes, philosophy follows suit and evolves. Having outsourced various forms of knowledge, philosophy’s pulling force of innovation has become necessarily external. It has been made so by philosophical reflection itself. This is the full sense in which Hegel’s metaphor of the Owl of Minerva is to be interpreted. In the past, the external force has been represented by factors such as Christian theology, the discovery of other civilisations, the scientific revolution, the foundational crisis in mathematics and the rise of mathematical logic, evolutionary theory, the emergence of new social and economic phenomena, the crisis of Newtonian physics, quantum physics and the the- ory of relativity, just to mention a few of the most obvious examples. Nowadays, the pulling force of innovation is represented by the complex world of information and communication phenomena, their corresponding sciences and technologies and the new environments, social life, existential and cultural issues that they have brought about. This is why PI can present itself as an innovative paradigm. It does inherit much of the past problems, but it re-shapes and models them in the light of our contemporary life. FR: Do you think that computer science has also changed the way we do philosophy, besides leading to a new discipline? How? LF: I do not think so, at least not in the sense that we shall ever do ‘computational philosophy’. I take computer science to play a leading role in making our reflection focus on new aspects of old issues and new problems. I also believe that it often provides a better approach to philosophical questions. But I would not like to see this confused with some sort of calculemus (“let’s calculate”) dear to Leibniz. As I mentioned above, genuinely philosophical problems are those that remain intrinsically open to informed and rational disagreement, if we could compute their answers they would not be philosophical in the first place. FR: I guess you strongly encourage your students to plunge into philosophy of information. What’s so exciting about that? LF: I have actually done that but only very recently, and with plenty of warnings. Philosophy is a very conservative discipline. She might fancy knowledge but she would rather marry the status quo of whatever current Weltanschauung (comprehensive world view) is available. So it can be risky to be a bit too innovative, or ahead of one’s time, or unorthodox if one does not have the support of the philosophical establishment. The recent change in my attitude is due to a number of positive signs from many academic venues. Whether one’s research is considered to be fringe and marginal or advanced and cutting-edge depends sometimes on the observer’s position. Since that seems to have changed, I feel I’m less irresponsible in inviting graduates to work on PI. What is exciting about it? It’s like having a whole unexplored continent at one’s disposal. It does not happen often in philosophy. If a graduate student would like to work on issues that are relevant to our contemporary world, or on classic problems without treating them as mummified diatribes, and that may provide insights into our lives as we know them today, PI is a great area of research. FR: I know you long fought the heavy historical perspective of much Italian and continental philosophy. Yet, one might argue that the key issues of philosophy of information were anticipated in the works of e.g. Charles Sanders Pierce, Alan Turing, or Claude Shannon & Warren Weaver. Do you think there’s something 3 we can or should learn from them? If so, what is, in your view, the right way a philosopher should approach historical issues? LF: Years of work within the analytic tradition have taught me that the history of philosophy is an essential part of a philosopher’s training, because too often I see brilliant students reinvent the wheel or end up in well-known blind alleys. Reading the classics is also a great way to unhinge one’s ideas when they become dogmatic or sterile, and challenge them with alternative views. It remains one of the best mental gyms one can join to exercise the brain. But the history of philosophy is only one tool among many in the bag of a good researcher. Too much of it stifles one’s reflection and undermines any attempt to innovate the conceptual tradition. Culture should not become culturism, if you allow me to expand the previous metaphor. In Italy, it is most unfortunate that many graduates treat philosophy as something separate and often in conflict with science. They cannot even conceive (and they are often not allowed) to work on problems first-hand. They work on authors, whom they treat almost religiously, and often on authors speaking about other authors. I still recall my frustration when I was told that, for my master thesis in Rome, I could not work on some aspects of the anti-realism debate, as I wished, but only on Dummett’s interpretation of Wittgenstein’s position about semantic anti-realism. Even when graduates do finally tackle some philosophical issue, they tend to do so through some authors/authorities, as if one could do philosophy only by ventriloquising. This is a pity. Especially because anyone trained in a history-based and history-oriented way not only can find doing philosophy very hard, but looses the capacity to do it in the future, like a child who, having failed to learn a natural language at the right age, will never be able to speak it properly. Classic authors are precious sources, and need to be treated as such, but we should not build churches around them, let alone treat their texts as Holy Scriptures. Commenting on Wittgenstein is not doing philosophy, it is doing history of ideas. It is a very valuable kind of research, but it belongs to a different department. FR: Some eight years ago you gave the Herbert A. Simon Lecture on Computing and Philosophy at CMU on the ‘open’ problems in philosophy of information. Have any of those problems been solved? What are the open problems today? LF: In that lecture I listed around twenty problems. I have tackled some of them in the past few years in a series of articles. I’m delighted to say that I am completing a book, entitled The Philosophy of Information (to be published by OUP), where I have collected and revised such solutions. But let me qualify what I have just said. Philosophical problems are solved in the sense that solutions are provided which are acceptable by in- formed and rational interlocutors but can be rejected when better solutions become available. ‘Better solutions’ simply means solutions that are conceptually less expensive, in terms of assumptions or, for example, incompatibilities with our scientific and ordinary knowledge. I take Bacon’s view of the market of ideas very seriously. So I believe that some of the open problems in PI have been solved economically so far, but there is room for huge improvements. This particular market of ideas is not mature yet. FR: Between 1995 and 2008, you were the founder and editor of the SWIF, the Italian online journal of philosophy, a publication that worked both as a national portal and as an e-publisher for the discipline. Now that the project is concluded, is there any fond or dreadful experiences or any learnt lessons that you might wish to share? LF: The SWIF was a great project, but in the end it had to be completed and closed because, after more than ten years, it had stopped being innovative. When I started designing it, in the early nineties, I had envisioned a gopher (a distributed system for Internet documents, predating the Web). But when I presented the project to several institutions nobody showed any interest and I met with a lot of skepticism. In the end, I discovered some unused funding that nobody was applying for, got some vital and enlightened support from the University of Bari, and with a small grant I started working on the first few web pages (by then the Web had become the standard). It was a rudimentary website, but one of the first in Italy. Some years later, SWIF even won a national prize by the Sole 24 Ore (the equivalent in Italy of the Financial Times). At some point we were hundreds of volunteers working on tens of projects. The basic idea might be compared today to a mix between Wikipedia and the Stanford Encyclopedia of Philosophy: a way of collecting common knowledge and channelling energies into a free-for-all service, that could rely on the contribution of a thousand drops of user-provided content, and that, by being peer-reviewed, could serve the philosophical community effectively. What became soon clear, however, was that the project required a full-time commitment, and that the lack of funding, of serious technical support, and hence the total dependency on volunteers’ time, energy, good will and skills was going to be an increasingly tighter bottleneck for any future growth. Some of the lessons I learnt were negative. People will rather have fixed rules and protocols than have to use their intelligence to take decisions and then be forced to be directly accountable for them. Some academics would rather die than have the courage of disagreeing with their peers and interact critically with each other in public. I remember an academic threatening us to send a legal complaint from her lawyer, if we did not modify a negative review of a text she had published (the 4 review had been kind, I have to say, and no, we did not change it of course). Another sent me some long and elaborate emails, to illustrate how unjust a reviewer had been towards a collection of essays he had published. When I offered him the opportunity to reply, he declined the invitation as out of the question, but kept bothering us anyway. As editor, you see some of the pettiest and ugliest corners of academia. But then you also encounter wonderful colleagues, ready to volunteer their time, energy and skills for a project, enthusiastically collaborative, or entirely and fully reliable even in the worst moments. And this is the human side of the SWIF that I like to remember. For many years, I used to say that we managed the SWIF as a (very idealised, don’t get me wrong) British Island: meritocracy, no favours to friends, responsibility and accountability, no exploitation of younger people, a transparent editorial strategy, peer-reviewing, no position guaranteed (those who failed to deliver were in the end gently asked to leave). I even had a ready text with a long reference to the famous film “The Bridge on the River Kwai”, which I used to send to potential volunteers in order to explain the spirit with which we were building the SWIF. For some years, we felt we were making a difference. I’m no longer sure we did, but I certainly learnt a lot from it. values, and this presupposition is not independently plausible. (2002: 196) Drai also put forward a slingshot argument which employs (Dox) instead of (Log) (see “Slingshot arguments: two versions”, The Reasoner, 3(4)). The reason that Drai gives for preferring (Dox) over (Log) is that (Dox) is supported by the analogy between sentences and names, whereas (Log) is not. Drai, having explained what it means for two sentences to be doxastically synonymous, hasn’t really defined how doxastic synonymy of names or other sub-sentential expressions is to be understood, though. There are a few ways these details can be filled in and I won’t discuss and compare them all. For instance, we could say that a name α is doxastically synonymous to a name β if and only if it is impossible that someone who understands these names (=grasps their descriptive content) believes that α , β. Now, indeed, it seems plausible that: (SN) Doxastically synonymous names are co-referential. Drai argues that (Log) cannot be justified as an extension of a rule applying to names: This is because the rule in the old domain must be: logically equivalent expressions have the same reference. But the notion of logical equivalence applies only to sentences and not to sub-sentential expressions such as proper names. That is, it does not apply to expressions in the old domain. . . it is meaningless when applied to sub-sentential expressions. (2002: 198) Doxastic synonymy vs. logical equivalence Say two sentences A and B are doxastically synonymous (A ∼d B) iff it is not possible for someone who understands A and B to believe one of them without believing the other. Consider the following two principles: (Log) Logically equivalent sentences are co-referential. Drai also explicitly opts for the descriptive theory of proper names: (Dox) Doxastically synonymous expressions are co-referential. I assume with Frege two basic theses about the reference of names: 1) names have sense, 2) the sense of a name determines its reference [. . . ] It is not my aim in this paper to contribute to the century-long controversy about the sense of names. My aim is to show that a valid version of the slingshot argument can be constructed based on a Fregean conception of names. (2002: 198) (Log) is used as one of the premises in classical variants of the so-called slingshot arguments (those are arguments to the effect that all true sentences denote the same object, if sentences denote at all). Recently, Drai (2002: The Slingshot Argument: an Improved Version, Ratio (new series), XV(2)) objected to (Log): The main objection to this argument is that (Log) is unjustified. Logically equivalent sentences have, by definition, the same truth value in every possible world. But only by begging the question about reference can we claim that they have the same reference in every possible world. The only way to justify [the assumption] that logically equivalent sentences have the same reference, is by presupposing that sentences refer to their truth Thus, for the sake of argument, I will assume the descriptive theory of proper names. I do believe, however, that even on the direct reference theory of names, difficulties analogous to those discussed in this paper can be raised against Drai’s view. So, the problem seems to be that we cannot meaningfully claim: (LN) Logically equivalent names have the same denotation. 5 Given the descriptive theory of proper names in the background, how does one go about justifying the claim that (SN) is meaningless? I’m not sure. Although attempts at solving philosophical problems by saying that some claims are meaningless does have a venerable tradition, no decisive methodology is available. On the other hand, I’m inclined to say that if one can give a fairly intuitive explication of what is meant when it is said that two names are logically equivalent, and the linguistic intuitions of competent language users aren’t deeply offended by this proposal, this shows that logical equivalence claims about names are meaningful. Let’s stimulate our intuitions with the following example. Say we have four proper names n1 , n2 , n3 , n4 (respectively) associated with the following descriptions: (N1) (ιx)(P(x) → Q(x)) (N2) (ιx)(P(x) ∧ ¬Q(x)) (N3) (ιx)(¬Q(x) → ¬P(x)) (N4) (ιx)¬(P(x) → Q(x)) Drai’s slingshot raises also another interesting question that pertains to reference of singular terms and doxastic synonymy of expression containing them. It will be discussed in detail in “Bogus singular terms and substitution salva denotatione” (The Reasoner, 3(6)). Rafal Urbaniak Philosophy, Ghent & Gdansk University Gödel and the Material Conditional In the lecture notes for his course “The Introduction to Logic” at the University of Notre Dame (P. CassouNogues, 2009: ‘Gödel’s Introduction to Logic in 1939’, History and Philosophy of Logic, 30: 69-90) Gödel introduces an interesting addition to the standard reading of the truth table for the propositional connectives. Thus for example, the truth table for the conjunction ‘p and q’ may be read: true, iff it is consistent with p and q both being t(rue), and is inconsistent with either being f(alse). The distinction between this and the standard reading comes into play with the material conditional. Gödel writes: When asked what the pairs: n1 and n3 , n2 and n4 have in common, a plausible answer seems to be that they are, well, in some sense logically equivalent, because the formulae in the scopes of definite description operators in the definite descriptions associated with the names are logically equivalent. Hence, the following seems like a sensible explication of the notion of logical equivalence of names: . . . assume that . . . we know ‘If p then q’, but nothing else . . . .[I]t may certainly happen that p is false, because [. . . ] ‘if p then q’ says nothing about the truth or falsehood of p. And in this case where p is false, q may be true as well as false, because the assumption ‘If p then q’ says nothing about what happens to q if p is false, but only if p is true. So we have both possibilities p false, q true; and, p false, q false . . . .” (p. 82) (EN) Names α and β, associated (respectively) with descriptions (ιx)φ(x) and (ιx)ψ(x) are logically equivalent iff That is to say, it is not that if ‘if p then q’ is true then if p is f, the conditional is true whether q is t or f; but ∀ x (φ(x) = ψ(x)) rather, if the conditional is true then it is consistent with is logically necessary. p being f whether q is t or f. Thus the explanation for the truth value assignments given to the material con(the notion of logical equivalence can be extended to ditional in one direction, is transparently clear. Gödel other sub-sentential expressions). continues: “But we have also vice versa” (Ibid). The notion of logical equivalence of names thus However, the rationale for the truth value assignment defined is different than the notion of doxastic to the conditional from its truth table that Gödel chooses synonymy—there can be logically equivalent names to give is the traditional one; namely, that the only lines that are not doxastically synonymous. For instance, we of the truth table relevant to the truth of the conditional can introduce proper names associated (respectively) are the two where p is t. And if q is t where p is t, with descriptions (ιx)(x = a ∧ φ), (ιx)(x = a ∧ ψ) such the conditional is true; and if q is f where p is t, the that φ and ψ are logically equivalent, and nevertheless conditional is false. But the traditional approach leaves φ is not doxastically synonymous to ψ if φ and ψ are unexplained why is it then that a conditional with a false so complex that one can understand φ and ψ without antecedent is true. believing they are equivalent. An answer is forthcoming if we apply Gödel’s novel The above considerations, however, do not show that approach in this direction as well. For it is hardly diseither (Log) or (Dox) is in fact plausible—the claim is putable that, only that if Drai’s justification of (Dox) is compelling, so is a parallel justification of (Log). (i) If p is consistent with the denial of ‘if p then q’, 6 then p is true. For the denial of ‘if p then q’, is ‘p and not q’. sentence-tokens of the sentence-type C* are not true.” And (i) is equivalent to The token is meaningless and we can therefore say (ii) if p is false then p is inconsistent with the denial of ‘if p then q’. That is, if p is false then ‘If p then q’ is true. “All the sentence-tokens of the sentence-type C* are not true” is not true. We could have done the same thing with the strengthened Liar: Alex Blum Philosophy, Bar-Ilan University This sentence is not true – M “This sentence is not true” is not true – T Divine Liars: The Answer where ‘M’ means meaningless and ‘T ’ means true. But “The famous paradox of C may well be resolved by the problem can be reformulated as a two line puzzle. noticing that the former is (demonstrably) nonsense and the latter (consequently) true” writes Martin Cooke C: The sentence C is not true – M (The Reasoner, 3(3):7). Yes, the paradox indeed is so resolved. The paradox in question is the two line D: The sentence C is not true – T puzzle: C: The sentence C is not true which leads us to the conclusion that sentence-token C has a different meaning than the sentence-token D. If we did the same thing with C*, e.g.: D: The sentence C is not true Cooke continues: “But even so one might wonder how C and D could differ so much in what they mean, the natural presumption being that the words of D mean the same, there, as they do in C.” The presumption is correct—the words of D mean the same, there, as they do in C. So why do C and D have different meanings? Because the meaning of a sentence is not the sum of the meanings of its parts. Rather the truth value of a sentence is determined by an algorithm (below) applied to the parts. The algorithm yields different results for C and D. “The naming of an object isn’t normally the sort of activity that could change its content” (Ibidem). Why can the naming of an object change its content? In our case the object is a sentence. It refers to an object (a sentence) by its name. The naming of the sentence determines if the sentence does or does not refer to itself. It alters its property of being self-referential. This in turn changes the meaning. “Let ‘[4***]’ name the sentence-type of the following sentence-token (of modern English): No omniscient being believes that a token of the sentence-type [4***] could be expressing a literal truth during March 2009 AD. . . . its truth would clearly imply its untruth and its untruth its truth.” (Ibidem, p.7) But its meaninglessness would imply nothing. Let us streamline the problem: C*: ‘No sentence-token of sentence-type C* is true” – M D*: “No sentence-token of sentence-type C* is true” – T D* would cause a contradiction. But we of course cannot do so because C* does not refer to a token. We have concluded above that “All the sentencetokens of the sentence-type C* are not true” is not true, and we ought to be able to generalize it to all the tokens of the same type. So we do just that: G: All the sentence-tokens of the same type as “All the sentence-tokens of the sentencetype C* are not true” are not true. The sentence-token G has different meaning than the sentence-token H. H: All the sentence-tokens of the sentencetype C* are not true. Let us now return to the evaluation “algorithm” mentioned at the beginning. The semantics proposed by Gaifman resembles the semantics of the programming languages (Gaifman 2000: Pointers to Propositions, Circularity, Definition, and Truth, pp. 79-121). “The sentence x is not true” is evaluated as follows: Def: ‘C*’ is the name of the sentencetype of the following sentence-token: “All the 1) Go to the label x 7 2) Evaluate the sentence next to it epistemology and decision theory, broadly construed. Topics include (but are not limited to) uncertain and am3) If the sentence is not true then pliative inference, coherence, paradoxes of belief and / or action, belief revision, disagreement and consensus, “The sentence x is not true” is true causal discovery, epistemology of religion, etc. And the else formal tools used to pursue questions within these topics include (but are not limited to) game theory and de“The sentence x is not true” is false cision theory, formal learning theory, probability theory We see that if we substitute C for x and we evaluate and statistics, networks and graphs, and formal logic. Confirmed Choice & Inference contributors include: the sentence token C, the “program” will go into infinite Alan Hájek, Franz Huber, Gregory Wheeler, Horacio recursion. In this case we assign the value M to C. Arló-Costa, Jake Chandler, Jan Sprenger, Jan-Willem We can prove by mathematical induction that the Romeijn, Jeffrey Helzner, Jon Williamson, Katie evaluation procedure for C will not halt. Whether the Steele, Kevin Zollman, Luc Bovens, Richard Bradley, procedure halts or not is thus decidable; either it will Stephan Hartmann, Ted Poston, Tomoji Shogenji, Trent halt or we prove by induction that it will not. So an Dougherty, and Vincenzo Crupi. Also, Choice & Inferalgorithm exists that returns either T , F or M. ence is run with the support of three external affiliates: Let’s try to evaluate D. We go to the label C. We (1) Carnegie Mellon University; (2) The Formal Episevaluate the sentence next to it. It has the value M, i.e. it temology Project, Katholieke Universiteit Leuven; and is not true. Then according to 3), D is true. (3) The Tilburg Center for Logic and Philosophy of Science, Tilburg University. 1. Go to the label H The blog is shaping up to be a wonderful resource to 2. Evaluate the sentence next to it those doing formal work related to rationality! Anyone working within the relevant fields who is interested in When we apply this procedure to H we find that H is becoming a contributor to Choice & Inference is welnot true: come to contact either of the blog administrators, Jake According to Gaifman’s semantics if v(α(a)) = T for Chandler or Jonah Schupbach. all α in the range of ‘x’, then v((x)α(a)) = T (Gaifman 2000: pp. 79-121). It means that we have to evaluate Jonah Schupbach all the sentence-tokens of the same type as H. Assume TiLPS, Tilburg there are three such tokens: H1, H2, H. We continue: 3.1) Evaluate the sentence token H1. Models and Fiction, 12–13 March 3.2) Evaluate the sentence token H2. Recent philosophy of science has seen a growing interest in the practice of scientific modelling. And yet some feel that this literature lacks a comprehensive account of No matter how many tokens there are, sooner or later models. A number of authors have begun to look to parwe will run into the token H and we will be in an infinite allels between models and works of fiction for such an loop again. Hence we assign M to H. account. The aim of this workshop was to explore these According to Gaifman, the sentence C does have a parallels in detail in order to address two main quesmeaning but it does not express a proposition. tions: What are models? And how do they represent the He takes the evaluation procedure to be the meaning world? of the sentence. The difference is mainly terminologiThe conference began with a welcome address by cal. The practical result is the same. Barry Smith (Institute of Philosophy) and an overview X.Y. Newberry of the literature by the conference organisers, Roman Frigg (LSE) and Michael Weisberg (Penn State). Frigg (‘Why we need fictions to understand models’) then argued against the view that models are mathematical §3 structures and presented an alternative account based on Kendall Walton’s ‘make-believe’ theory of fiction. News On Frigg’s account, the descriptions scientists write down when they model a system prescribe imagining a Choice & Inference ‘model-system’ (or ‘imaginary object’) which, in turn, Choice & Inference is a new group blog providing a fo- represents the system being modelled. Peter Godfreyrum for dialogue and news within the fields of formal Smith (Harvard, ‘Models and mongrels’) adopts a sim- 3.3) Evaluate the sentence token H. 8 Evidence, Science and Public Policy, 26–28 March ilar account, describing models as ‘imagined concrete objects’, while aiming to remain non-committal on the nature of these objects. The second Sydney-Tilburg conference took place 26– 28 March 2009 in Sydney, and focused on an interdisAdam Toon (Cambridge, ‘Models, fiction and imag- ciplinary topic: “Evidence, Science and Public Policy”. ination’) offered an account of modelling which was To represent the variety of perspectives on the topic adealso based on Walton’s theory but which differed from quately, three speakers with different backgrounds were Frigg’s. On Toon’s account, there are no imaginary invited: John Worrall (LSE) from the home discipline of objects that satisfy scientists’ modelling assumptions; the organizers, philosophy of science, the ecologist and instead, the descriptions scientists write down when risk analyst Mark Burgman (U/Melbourne), and John they model a system represent that system directly, by Quiggin (U/Queensland) who works on the economics prescribing imaginings about it. Arnon Levy (Har- of climate change. Approximately 30 contributed talks vard, ‘Idealization, fiction and causal understanding’) in two parallel sessions complemented the program. focussed on the problem of understanding how idealised A few days before the conference two major shocks models, which misrepresent the world, can nevertheless occurred: Mark Burgman had to cancel his participabe explanatory. Levy suggested that such models pro- tion due to illness, and host organizer Mark Colyvan vide causal information in a form that is useful for form- could not be present due to urgent family issues. Deing predictions. spite these potential setbacks, Mark’s assistant Rodney Taveira helped the organizers to make final preparations and the conference became a real success. The variDeena Skolnick Weisberg (Rutgers, ‘A psychologi- ety of the participants’ backgrounds could have been cally realistic account of models as fictions’) presented an obstacle, but it turned out that interdisciplinary comempirical work suggesting that the same cognitive pro- munication went smoothly, and we had a lot of excitcesses underlie reasoning about reality and what is ‘true ing discussions. One major focus was on evidencein fiction’. Chris Pincock (Purdue, ‘Discerning the truth based medicine, in the line of John Worrall’s opening in fiction’) argued that fiction-based accounts of models talk. Many talks discussed evidence-based policy in cannot meet ‘the export challenge’, that is, they cannot general, with a lot of applications from environmental specify how the fictional content of a model is related decision-making in general and the challenge of climate to its representational content. Martin Thomson-Jones change in particular. Here, philosophical and concep(Oberlin, ‘The adventure of missing systems’) criticised tual issues were dealt with as well as practical, problemFrigg and Godfrey-Smith’s talk of ‘imagined concrete oriented questions. To that end, it was helpful that some objects’ before exploring some alternative accounts of speakers did not work in academia, but were affiliated the ontology of models based on realist accounts of with governmental agencies, and could enrich theoretifictional entities. In the final talk, Michael Weisberg cal discussions with their experiences from practice. Fi(‘Maths and Fictions’) acknowledged the important role nally, there were a couple of analyses of group decisionplayed by scientists’ ‘folk ontology’, which leads some making focusing on reaching agreement among a group to take models to be ‘imagined concrete objects’; never- of decision-makers. It is safe to say that the quality of theless, he argued, models are mathematical, not imag- talks was quite high, and the two keynotes deserved that ined, objects. moniker. The atmosphere at the conference was very friendly and cheerful, and the setting at the veranda of the VetEach day ended with a productive comment and diserinary Science Conference Center and the pleasant cussion session. In the first, Tim Crane (UCL) distinweather certainly contributed to its success. Participants guished more ‘inflationary’ positions, such as that prospent a lot of time with each other when the official proposed by Frigg, from ‘deflationary’ accounts, such as gram was over, and quite a few future collaborations that put forward by Toon. In the second session, Stawere formed. On the evening of 26 March, a delicious cie Friend (Heythrop) suggested that in order to develop conference dinner took place in a Thai restaurant on a coherent theory of modelling, ‘deferral strategies’ on King Street. The general success of the conference enthe ontology of models must eventually be abandoned, courages the Sydney Centre for the Foundations of Scieither by providing a realist account of the nature of ence and the Tilburg Center for Logic and Philosophy ‘model-systems’ or else by adopting an anti-realist, deof Science to continue their efforts, and to organize a flationary position. third conference in Tilburg, in Spring 2010. Finally, we Adam Toon would also like to thank the Australian Centre of ExHistory and Philosophy of Science, Cambridge cellence for Risk Analysis (ACERA) and the Applied Environmental Decision Analysis research hub (AEDA) 9 once more for their generous support of the event. Jan Sprenger Tilburg Center for Logic and Philosophy of Science Computational Linguistic Aspects Grammatical Inference, 30–31 March of The International Community of Grammatical Inference organizes biennial conferences, called ICGI, in the even years and in the odd years it organizes co-located workshops or tutorials. These events are typically colocated with conferences that fall within the application areas of grammatical inference: in previous occasions machine learning or artificial intelligence conferences were chosen. This year, a workshop, called Computational Linguistic Aspects of Grammatical Inference (CLAGI) was organized by Menno van Zaanen and Colin de la Higuera. This event was co-located with the triennial conference of the European Chapter of the Association Computational linguistics in Athens, Greece. The CLAGI workshop consisted of eight talks, an invited talk and a panel session. The talks were divided into three sessions. The invited talk was given by Damir Cavar. He gave an overview of work in the field of grammatical inference applied to linguistics. This illustrates the search for the holy grail: a general grammar induction model that learns all aspects of natural languages. The first session contained three talks on transduction. Jeroen Geertzen presented a novel grammatical inference system that finds regularities in (human) dialogs and uses these regularities to predict future dialog acts. Dana Angluin and Leonor Becerra-Bonache concentrated on a formal description of the language learning task where the focus lies on incorporating semantics. Finally, Jorge Gonzalez and Francisco Casacuberta described their machine translation toolkit that uses a transducer inference system. The second session was on language models and parsing. Alexander Clark, Remi Eyraud and Amaury Habrard discussed properties of the class of contextual binary feature grammars (which are known to be efficiently learnable) in comparison to the class of natural languages. Next, Herman Stehouwer and Menno van Zaanen illustrated an application of parallel n-gram language models in the context of typographical error correction. This was followed by a presentation by Marie-Hélène Candito, Benoit Crabbé and Djamé Seddah describing experiences with statistical parsing of French. Finally, Franco M. Luque and Gabriel InfanteLopez investigated the performance of unambiguous non-terminally separated grammars in the context of natural language learning. 10 The last session on morphology contained one talk. Katya Pertsova analyzed a collection of learners that analyze boolean partitions. These learners are applied to the task of learning morphological paradigms. Following the talks, Jeroen Geertzen, Alexander Clark, Colin de la Higuera and Menno van Zaanen briefly presented their experiences and ideas on competitions in the areas of computational linguistics and grammatical inference. This lead to a panel discussion with much interaction from the audience on possibilities of future competitions and their impact. Overall, the workshop contained a wide variety of talks, ranging from technical and theoretical research on learnability of language to descriptions of practical natural language learning experiments. This variety illustrated the wide applicability of grammatical inference, but at the same time the workshop showed that people in the field of computational linguistics are unfamiliar with the field of grammatical inference and vice versa, even though their research is highly relevant to both fields. This workshop should be seen as an initial attempt at bringing these fields closer together. Menno van Zaanen ILK, Tilburg Colin de la Higuera Laboratoire Hubert Curien, Sait-Etienne (France) Sparsity in Machine Learning and Statistics, 1–3 April Sparsity has emerged as one of the most important modelling tools of the past decade. Its popularity is easy to grasp; it is both conceptually simple, and the estimation methods that follow as its consequence have already been implemented for several decades in geophysics, as well as in image estimation, signal processing, statistics and machine learning. The aim of the workshop on Sparsity in Machine Learning and Statistics, organized by the UCL Centre for Computational Statistics and Machine Learning (CSML) and sponsored by the PASCAL Network of Excellence and the Royal Statistical Society, was not only to highlight research questions that are currently receiving particular attention, but also to draw the common threads from different fields, in particular statistics, signal processing and machine learning. This second aim of the workshop aligns closely with the CSML Centre that is working to promote cross-fertilisation between these fields as well as application of relevant techniques across the sciences. The concept of sparsity is simple; in whatever family of models we may assume our data was generated by, the true model can be described by a small number of parameters. Sparsity can therefore be thought of as a mathematical version of Occams razor. It is not hard to understand why sparsity has become so important; with our capacity for collecting larger volumes of data, superficial model complexity must grow. However, implicit in the notion of trying to explain the observed data is the assumption that some simple(r) mechanism for its generation must exist. For physically unrealistic degrees of simplicity, with some chosen estimation methods, we can in some instances be sure to recover the true sparse model. Unfortunately, in real life, we rarely have such extreme degrees of simplicity or lack of interconnectedness between explanatory variables for which results have been shown. This often leads to overestimating the degree of complicatedness of the model. The answer to this problem seems to be to abandon the simplicity of commonly used methods, for harder optimization problems. Of great interest are also more intricate notions of sparsity which are being developed to analyse heterogeneous datasets. Here, different data of similar phenomena are obtained, possibly under different observation modalities, and we may try to estimate common sparsity patterns across the data; in machine learning this is known as multitask or multiview learning. Sparsity as an area of research is transitioning from completely virgin territory to a more established area, gradually following the path of neural networks, or wavelets. The next decade will see considerable developments in this area, and as remarked by a participant, results developed for particular learning or estimation methods, as more general theory will undoubtedly lead to very crude bounds of performance. As our data collection continues to increase sparsity becomes a necessity, and will continue as a fundamental theoretical tool in our understanding of the world we live in. Sofia Olhede Statistics, UCL Massimiliano Pontil Computer Science, UCL John Shawe-Taylor Computer Science, UCL Calls for Papers Intuitionistic Modal Logics and Applications: Special issue of Information and Computation, deadline 31 May. Logic and the Foundations of Physics: Special issue of Studia Logica, 31 May. 11 Deconstruction and Science: Special issue of Derrida Today, 30 June. Causality in the Sciences A volume of papers on causality across the sciences Deadline 1 July Is Logic Universal?: Special issue of Logica Universalis, 31 August. Logic and Social Interaction: Special issue of Synthese KRA, 1 September. Experimental Philosophy: Forthcoming issue of The Monist, deadline April 2011. §4 What’s Hot in . . . We are looking for columnists willing to write pieces of 100-1000 words on what’s hot in particular areas of research related to reasoning, inference or method, broadly construed (e.g., Bayesian statistical inference, legal reasoning, scientific methodology). Columns should alert readers to one or two topics in the particular area that are hot that month (featuring in blog discussion, new publications, conferences etc.). If you wish to write a “What’s hot in . . . ?” column, either on a monthly or a one-off basis, just send an email to features@thereasoner.org with a sample first column. Formal Epistemology Handy tips and helpful advice from the Formal Philosophy Seminar series at the Formal Epistemology Project, University of Leuven. Adam Rieger’s Indicative Conditionals defended a material conditional account of indicative conditionals via an elaboration on the assertability conditions account that side-steps some problems for Jackson’s view. The suggestion is that speakers’ confusions between narrow and wide scope of operators plays as large a role in explaining the problem cases as do confusions between truth and assertability conditions. Ofra Magidor’s (co-authored with John Hawthorn) Assertion, Context, and Epistemic Accessibility argued that Stalnaker’s metasemantic framework has problems when it interacts with extra-theoretical facts about epistemic access. Paul Egre’s Soritical Series and Fisher Series led a radical argument for unifying vagueness and ambiguity, two categories traditionally kept distinct. The key is to examine perceptual ambiguity, as opposed to the purely lexical cases. Relatedly, I have just finished teaching my half of a graduate class on Formal Epistemology (Richard Dietz is taking part-2). Fun was had by all! I took the intrepid grads through Vincent F. Hendricks’s Main- manager, Rasmus Rendsvig. stream and Formal Epistemology. Philosophers among Olivier Roy you will recall that, back when you began philosophy, Philosophy, Groningen you were told that epistemology was about knowledge. Then, somehow, it stopped being about knowledge, and was suddenly about our concept of knowledge . . . This happens everywhere in philosophy (consider conscious§5 ness, and mental representation). It is a mark of his methodological sobriety that Vincent goes to the lengths Introducing ... in his book that he does in order to keep epistemic and doxastic phenomena on the one hand, and our concepts In this section we introduce a selection of key terms, texts and authors connected with reasoning. Entries of such phenomena on the other, distinct. Next month, Hannes Leitgeib, Wiebe van der Hoek, will be collected in a volume Key Terms in Logic, to be published by Continuum. If you would like to conRichard Bradley, and Luc Bovens. tribute, please click here for more information. If you Click for the pics of the FPS seminars and for the full have feedback concerning any of the items printed here, FPS program. please email features@thereasoner.org with your comSebastian Sequoiah-Grayson ments. Formal Epistemology Project, Leuven Theory of Argumentation Argumentation theory is the study of argument, particularly those aspects which resist deductive formalization. It is often taken to coincide with or subsume inLogic and Rational Interaction formal logic and critical thinking. Aristotle’s Organon, The Logic and Rational Interaction (LORI) website is famous as the first study of formal logic, actually pays intended at gathering information for all researchers greater attention to informal reasoning. Notably, Arisworking at the intersection of logic and the theory of totle introduces ‘enthymemes’, latterly over-simplified rational interaction. In this monthly column I summa- as syllogisms with missing premisses, to characterize rize for the readers of The Reasoner some of the key plausible non-deductive inferences. Logic retained this items that appeared on the website. You can read more broader scope into the early twentieth century, until the increasingly successful mathematical approach eclipsed about each of them on http://loriweb.org. all others. For almost two years, the Danish police kept an eye The modern revival of argumentation theory began on Vincent Hendricks. Indeed, he has been teaching with two works: Chaim Perelman and Lucie Olbrechtslogic to officers and investigators, and has even put it Tyteca’s La Nouvelle Rhétorique (1958: Paris) and to use to track and catch suspects! You can read more Stephen Toulmin’s The Uses Of Argument (1958: Camabout this in a short interview he gave to LORI. bridge). Both emphasize jurisprudential over matheSome interesting new publications that have been an- matical approaches to reasoning. Toulmin’s major connounced on the website this month: a new book by tribution was the ‘layout’ which analyzes arguments Christian List and Philip Petit, a working paper on into six components. The data (or grounds) provide learning theory and dynamic epistemic logic by Cédric qualified support for the claim in accordance with a warDégremont, Nina Gierasimczuk, and a summary of a re- rant, which may in turn be supported by backing or adcent work by Gaelle Fontaine and Johan van Benthem mit exceptions or rebuttals. on (dynamic epistemic) mu-calculus. On the functionToulmin’s influence was greatest outside philosophy, ality side, let me point out that you can now register and recent work is strongly interdisciplinary, encomto the LORI newsletter, to receive by periodical email passing communication theory, artificial intelligence, summaries of the new entries on the website. Sim- and law. For instance, ‘pragma-dialectics’, the influenply visit http://loriweb.org and fill-in your email- tial programme of Amsterdam communication theorists address! Frans van Eemeren and Rob Grootendorst, advocates a Logic and Rational Interaction is a collaborative ven- normative ideal for critical discussion. This is characture. We welcome any contributions relevant to the terized by ‘Ten Commandments’: rules claimed to intheme, and are also constantly looking for new collab- crease the likelihood of reaching a reasonable outcome orators. So, if you would like to joint the team, of if in a disagreement. Conversely, some artificial intelliyou have information to share with the broader research gence research connects argumentation to formal accommunity, please do not hesitate to contact our web counts of defeasible reasoning, such as non-monotonic 12 logic. Much recent attention has focused on ‘argumentation schemes’: stereotypical patterns of plausible reasoning. These may be seen as reinventing Aristotle’s ‘topoi’, which linked the premisses to the conclusion in his enthymemes. Argumentation schemes are important to the long-standing problem of characterizing informal fallacies. Fallacies may be understood as pathological instances of plausible but not invariably sound schemes. This programme has been developed at length by the prolific Canadian logician Douglas Walton. Andrew Aberdein Florida Institute of Technology Brouwer’s Programme Brouwer’s Programme, which he called ‘Intuitionism’, aims to provide a philosophical foundation for pure mathematics. The idea is that mathematics is first of all the activity of making exact constructions in the mind. The material out of which these constructions are made is abstracted from the intuition of the flow of time in consciousness. Accordingly, there is no mathematical reality outside the mind, and with every new construction grows not only our mathematical knowledge but also the mathematical universe itself. Brouwer sharply distinguished Intuitionism from psychology, logic, and the study of languages and formal systems, which he all considered to be forms of applied mathematics. As it turns out, various parts of classical mathematics cannot be reconstructed intuitionistically. Conversely, Brouwer introduced objects and principles of reasoning about them that are not acceptable in classical mathematics. For example, Intuitionism rejects Cantorian set theory and the universal validity of the Principle of the Excluded Middle, but introduces choice sequences. Brouwer used these to develop a constructive theory of the continuum that does not let it fall apart into atoms, as a set-theoretical analysis does. Mark van Atten IHPST, Paris §6 Events May University, 7–10 May. Metaphysical Indeterminacy, the State of the Art: University of Leeds, 9 May. AAMAS: The Eighth International Joint Conference on Autonomous Agents and Multi-Agent Systems, Budapest, 10–15 May. Understanding Human Nature: University of Antwerp, 11 May. Conditional Logic: University of Düsseldorf, 11 May. ACL2: International Workshop on the ACL2 Theorem Prover and Its Applications, Northeastern University, Boston, 11–12 May. MSDM: Multi-agent Sequential Decision-Making in Uncertain Domains, AAMAS, Budapest, 11 or 12 May. Philosopher’s Rally: University of Twente campus, Enschede, the Netherlands, 12–13 May. PhiLang: International Conference on Philosophy of Language and Linguistics, Lódź, Poland, 14–15 May. Carnap Colloquium: Carnap’s Ideal of Explication: Logic, Metalogic, and Wissenschaftslogik, Paris, 14–16 May. Philosophy and Cognitive Science: The XIXth edition of the Inter-University Workshop, Zaragoza, 18–19 May. Benelearn: 18th Annual Belgian-Dutch Conference on Machine Learning, Tilburg University, 18–19 May. UR: Uncertain Reasoning, Special Track of FLAIRS, Island, Florida, USA, 19–21 May. Philosophy of Biology: Madison, 21–23 May. Evidence in Context: Fifth annual conference of the Graduate Student Society at the Institute for the History and Philosophy of Science and Technology, University of Toronto, 23 May. AI: The twenty-second Canadian Conference on Artificial Intelligence, Kelowna, British Columbia, 25–27 May. Science and Values—The Politicisation of Science: Center for Interdisciplinary Research (ZiF), Bielefeld, Germany, 25–30 May. CSHPS: The Canadian Society for History and Philosophy of Science, annual conference as part of the Congress of the Humanities and Social Sciences (CFHSS), Carleton University, Ottawa, 26–28 May. Causality in Statistical Investigation: Royal Statistical Society, London, 27 May. Preference Change Workshop: London School of Economics, 28–30 May. Second Formal Epistemology Festival: Causal Decision Theory and Scoring Rules, University of Michigan, 29–31 May. Foundations of Mathematics: Philosophy and Foundations of Mathematics—Epistemological and Ontologi- June cal Aspects, SCAS, Uppsala, 5–8 May. Logic of John Duns Scotus: 44th International IRMLeS: Inductive Reasoning and Machine Learning Congress on Medieval Studies at Western Michigan on the Semantic Web, Heraklion, Crete, 1 June. 13 Argument Cultures: Ontario Society for the Study of Argumentation, Windsor, Canada, 3–6 June. O-Bayes: International Workshop on Objective Bayes Methodology, Wharton School of the University of Pennsylvania, Philadelphia, PA, 5–9 June. MODGRAPH: Probabilistic graphical models for integration of complex data and discovery of causal models in biology, Nantes, France, 8 June. Philosophy of Probability II: Graduate Conference, Centre for Philosophy of Natural and Social Science, London School of Economics, 8–9 June. CNL: Controlled Natural Languages, Marettimo Island, Sicily, 8–10 June. Groups and Models: Cherlin Bayrami, Bilgi University, Istanbul, Turkey, 8–12 June. Formal methods in the Epistemology of Religion: KULeuven (Leuven, Belgium), 10–12 June. Toward a Science of Consciousness: Hong Kong, 11– 14 June. Vagueness: Predication and Truth: Workshop on Vagueness organised by the Vagueness Research Group, University of Navarra, 12–13 June. Society for Philosophy and Psychology: Indiana University, Bloomington, 12–14 June. NA-CAP: Networks and Their Philosophical Implications, Indiana University in Bloomington, 14–16 June. NAFIPS: 28th North American Fuzzy Information Processing Society Annual Conference, University of Cincinnati, Cincinnati, Ohio, 14–17 June. ICML: The 26th International Conference On Machine Learning, Montreal, Canada, 14–18 June. SPSP: Society for Philosophy of Science in Practice, University of Minnesota, Minneapolis, 18–20 June. Formal Epistemology Workshop: Carnegie Mellon University, 18–21 June. UAI: The 25th Conference on Uncertainty in Artificial Intelligence, Montreal, Canada, 18–21 June. Non-Classical Mathematics: Hejnice, Czech Republic, 18–22 June. Pragmatism & Science Conference: Center for Inquiry, Amherst, NY, 19–20 June. PNSE: International Workshop on Petri Nets and Software Engineering, Paris, 22–23 June. WoLLIC: 16th Workshop on Logic, Language, Information and Computation, Tokyo, Japan, 21–24 June. LOGICA: The 23rd in the series of annual international symposia devoted to logic, Hejnice (northern Bohemia, 22-26 June. Consciousness and the Self: Department of Philosophy, University of Liverpool, 25 June. Metaphysics of Physics: Department of Philosophy, University of Birmingham, 25 June. Multiplicity and Unification in Statistics and Probability University of Kent, Canterbury, UK, 25–26 June 14 Annual Conference: Society for Applied Philosophy, University of Leeds, 26–28 June. ACM SIGKDD International Workshop: Knowledge Discovery from Uncertain Data, Paris, France, 28 June. July Two Streams in the Philosophy of Mathematics: Rival Conceptions of Mathematical Proof, University of Hertfordshire, Hatfield, UK, 1–3 July. EDM: Educational Data Mining, Cordoba, Spain, 1–3 July. ECSQARU: 10th European Conference on Symbolic and Quantitative Approaches to Reasoning with Uncertainty, Verona (Italy), 1–3 July. E-CAP: Computing and Philosophy, Universitat Autònoma de Barcelona, 2–4 July. Metaphysics of Science: University of Melbourne, 2–5 July. Proof Theory and Constructivism: Leeds, 3–16 July. Set Theory Meeting: in Honour of Ronald Jensen, Mathematical Research and Conference Center, Bedlewo, Poland, 5–10 July. CALCULEMUS: 16th Symposium on the Integration of Symbolic Computation and Mechanised Reasoning, Ontario, Canada, 6–7 July. FTP: International Workshop on First-Order Theorem, Oslo, Norway, 6–7 July. TARK: Twelfth Conference on Theoretical Aspects of Rationality and Knowledge, Stanford University, 6–8 July. Information Fusion: 12th International Conference, Grand Hyatt, Seattle Washington, 6–9 July. TABLEAUX: Automated Reasoning with Analytic Tableaux and Related Methods Oslo, Norway, 6–10 July. SPT: Converging Technologies, Changing Societies, 16th International Conference of the Society for Philosophy and Technology, University of Twente, Enschede, The Netherlands, 8–10 July. IC-EpsMsO: 3rd International Conference on Experiments / Process / System, Modelling / Simulation / Optimization, Athens, Greece, 8–11 July. Interdisciplinary Social Science: Athens, 8–11 July. ARCOE: Automated Reasoning about Context and Ontology Evolution, Pasadena, 11-12 July. Aim of Belief: Centre for the Study of Mind in Nature, University of Oslo, 11–13 June. IJCAI: 21st International Joint Conference on Artificial Intelligence, Pasadena, CA, 11–17 July. ISHPSSB: International Society for the History, Philosophy, and Social Studies of Biology, Emmanuel College, St. Lucia, Brisbane, Australia, 12–16 July. Logic and Heresy in the Middle Ages: Leeds Medieval Congress, 13–16 July. DMIN: International Conference on Data Mining, Las Vegas, 13–16 July. ICAI: International Conference on Artificial Intelligence, Las Vegas, 13–16 July. ICLP: 25th International Conference on Logic Programming, Pasadena, California, 14–17 July. ISIPTA: 6th International Symposium on Imprecise Probability: Theories and Applications, Durham University, 14–18 July. DGL: Third Workshop in Decisions, Games & Logic, HEC Lausanne, Switzerland, 15–17 June. ISSCSS: First Graduate International Summer School in Cognitive Sciences and Semantics, University of Latvia, Riga, 16-26 July. AIME: 12th Conference on Artificial Intelligence in Medicine, Verona, Italy, 18–22 August. ViC: Vagueness in Communication, Bordeaux, France, 20–24 July. IWSM24: 24th International Workshop on Statistical Modelling, Cornell University in Ithaca, NY, 20–24 July. LMSC: Workshop Logical Methods for Social Concepts, Bordeaux, France, 20–31 July. ICCBR: Eighth International Conference on CaseBased Reasoning, Seattle, Washington, 20–23 July. ESSLLI: 21st European Summer School in Logic, Language and Information, Bordeaux, France, 20–31 July. Buffalo Ontology Week: A series of events relating to ontology, and the first International Conference on Biomedical Ontology, Buffalo, 20–27 July. Case-Based Reasoning in the Health Sciences: Seattle, Washington, 21 July. History of Science and Technology: XXIII International Congress of History of Science and Technology: Ideas and Instruments in Social Context, Budapest, Hungary, 28 July–2 August. Logic Colloquium: Sofia, 31 July–5 August. ICNC: The 5th International Conference on Natural Computation, Tianjin, China, 14–16 August. ASAI: X Argentine Symposium on Artificial Intelligence, Mar del Plata, Argentina, 24–25 August. ICSO: Issues in Contemporary Semantics and Ontology, Buenos Aires, 26–28 August. LGS6: Logic, Game Theory, and Social Choice 6, Tsukuba Center for Institutes, Japan, 26–29 August. PASR: Philosophical Aspects of Symbolic Reasoning in Early Modern Science and Mathematics, Ghent, Belgium, 27–29 August. EANN: Artificial Neural Networks in Engineering, University of East London, 27–29 August. Practice-based Philosophy of Logic and Mathematics: ILLC, Amsterdam, 31 August–2 September. September Foundations of Uncertainty: Probability and Its Rivals, Villa Lanna, Prague, Czech Republic, 1–4 September. Trends in Logic VII: Trends in the Philosophy of Mathematics, Goethe-University Frankfurt, 1–4 September. SOPHA: Triannual congress of the SoPhA, the Société de Philosophie Analytique, University of Geneva , 2–5 September. Naturalism and the Mind: Kazimierz Dolny, Poland, 4–8 September. UC: 8th International Conference on Unconventional Computation, Ponta Delgada, Portugal, 7-11 September. CLIMA: 10th International Workshop on Computational Logic in Multi-Agent Systems, Hamburg, Germany, 9–10 September. Mechanisms and Causality in the Sciences University of Kent, Canterbury, UK, 9–11 September Phloxshop II: Humboldt-Universität, Berlin, 9–11 September. MATES: Seventh German Conference on MultiAugust Agent System Technologies, Hamburg, Germany, 9–11 CADE-22: 22nd International Conference on Auto- September. mated Deduction, McGill University, Montreal, 2–7 MoS: Grand Finale Conference of the Metaphysics of August. Science AHRC Project, Nottingham, 12–14 September. Logic and Mathematics: University of York, 3–7 Au- The New Ontology of the Mental Causation Debate: gust. Old Shire Hall, Durham University, 14–16 September. Science in Society: University of Cambridge, United ISMIS: The Eighteenth International Symposium on Kingdom, 5–7 August. Methodologies for Intelligent Systems, University of Meaning, Understanding and Knowledge: 5th Interna- Economics, Prague, Czech Republic, 14–17 September. tional Symposium of Cognition, Logic and Communi- LPNMR: 10th International Conference on Logic Procation, Riga, Latvia, 7–9 August. gramming and Nonmonotonic Reasoning, Potsdam, LICS: Logic in Computer Science, Los Angeles, 9–11 Germany, 14–18 September. August. KI: 32nd Annual Conference on Artificial Intelligence, FSKD: 6th International Conference on Fuzzy Systems Paderborn, Germany, 15–18 September. and Knowledge Discovery, Tianjin, China, 14–16 Au- FroCoS: Frontiers of Combining Systems, Trento, Italy, 16–18 September. gust. 15 AAAI: Fall Symposium on Complex Adaptive Systems, Arlington, VA, 5–7 November. 4th Workshop on Combining Probability and Logic, AICI: The 2009 International Conference on Artificial special focus: new approaches to Intelligence and Computational Intelligence, Shanghai, rationality in decision making, China, 7–8 November. Groningen, The Netherlands, 17–18 September Epistemology, Context, and Formalism: Université Logic, Language, Mathematics: A Philosophy Con- Nancy 2, France, 12–14 November. ference in Memory of Imre Ruzsa, Budapest, 17–19 SPS: Science and Decision, Third Biennial Congress of September. the Societe de Philosophie des Sciences, Paris, 12–14 Evolution, Cooperation and Rationality: Bristol, 18– November. 20 September. M4M-6: 6th Workshop on Methods for Modalities, ICAPS: 19th International Conference on Automated Copenhagen, Denmark, 12–14 November. Planning and Scheduling, Thessaloniki, Greece, 19–23 VI Conference: Spanish Society for Logic, MethodolSeptember. ogy and Philosophy of Science, Valencia, Spain, 18–21 International Darwin Conference: Universitys Nor- November. croft Centre, University of Bradford, 24–26 Semptem- LENLS: Logic and Engineering of Natural Language ber. Semantics,Campus Innovation Center Tokyo, MinatoPASR: Philosophical Aspects of Symbolic Reasoning in ku, Tokyo, 19–20. Early Modern Science and Mathematics, University of ISKE: The 4th International Conference on Intelligent Ghent, Belgium, 28–29 August. Systems & Knowledge Engineering, Hasselt, Belgium, KES: Knowledge-Based and Intelligent Information & 27–28 November. Engineering Systems, Santiago, Chile, 28–30 September. ASCS: The 9th conference of the Australasian Society December for Cognitive Science, Macquarie University, Sydney, ICDM: The 9th IEEE International Conference on Data 30 September–2 October. Mining, Miami, 6–9 December. Progic October Joint Attention: Developments in Philosophy of Mind, Developmental and Comparative Psychology, and Cognitive Science, Bentley University, Greater Boston, 1–3 October. KMIS: International Conference on Knowledge Management and Information Sharing, Madeira, Portugal, 6–8 October. The Hugh MacColl Centenary Conference: Boulogne sur Mer, 9–10 October. EPIA: 14th Portuguese Conference on Artificial Intelligence, Universidade de Aveiro, Portugal, 12–15 October. Case Studies of Bayesian Statistics and Machine Learning: Carnegie Mellon University, Pittsburgh, PA, 16–17 October. Breaking Down Barriers: Blackwell Compass Interdisciplinary Virtual Conference, 19–30 October. EPSA: 2nd Conference of the European Philosophy of Science Association, 21–24 October. RR 2009: Third International Conference on Web Reasoning and Rule Systems, 25–26 October. Darwin Conference: Chicago, Illinois, 29–31 October. November ACML: 1st Asian Conference on Machine Learning, Nanjing, China, 2–4 November. 16 Interpretation and Sense-Making: University of Rouen, France, 9–11 December. MBR: Abduction, Logic, and Computational Discovery, Campinas, Brazil, 17–19 December. §7 Jobs Post-doc position: Behavioural Health and Technology, University of Viriginia, Department of Psychiatry and Neurobehavioral Sciences, position open until filled. Two visiting positions: Department of Philosophy at Grand Valley State University in Allendale, Michigan, review of applications starts 1 May. Assistant professor: Algebra & Logica group, Nijmegen, The Netherlands, review of application starts 1 May. Post-doc position: in philosophy, sociology and history of science, Henri Poincar Archives, Nancy, France, 1 May. 2 Lecturers in Philosophy: Department of Philosophy, University of Leeds, 1 May. Post-doc position: in the project “Cognitive Origins of Vagueness”, Institut Jean-Nicod, Paris, 13 May. 2 Post-doc positions: CAUSAPROBA project, IHPST, Paris, 14 May. Post-doc positions: Instituto de Investigaciones Filosficas, UNAM, Mexico, 14 May. Post-doc position: in the research project “Tarski’s Revolution: A New History—Semantics and Axiomatics from Bolzano to Tarski against the background of the Classical Model of Science”, Faculty of Philosophy, University Amsterdam, 1 June. Visiting Fellowships: Joseph L. Rotman Institute of Science and Values, University of Western Ontario, 1 July. §8 Courses and Studentships Courses HPSM: MA in the History and Philosophy of Science and Medicine, Durham University. Master Programme: Philosophy of Science, Technology and Society, Enschede, the Netherlands. MSc in Mathematical Logic and the Theory of Computation: Mathematics, University of Manchester. MA in Reasoning An interdisciplinary programme at the University of Kent, Canterbury, UK. Core modules on logical, causal, probabilistic, scientific, mathematical and machine reasoning and further modules from Philosophy, Psychology, Computing, Statistics, Social Policy and Law. MSc in Cognitive & Decision Sciences: Psychology, University College London. Master of Science: Logic, Amsterdam. Summer Institute on Argumentation: University of Windsor, Canada, contact H.V. Hansen or C.W. Tindale, 25 May–6 June. Summer School in Logic and Formal Epistemology: Canergie Mellon University, 8–26 June. NN: Summer School in Neural Networks in Classification, Regression and Data Mining, Porto, Portugal, 6– 10 July. ACAI: Advanced Course in Artificial Intelligence, School of Computing and Mathematics, University of Ulster, Northern Ireland, 23–29 August. 17 Fourth Cologne Summer School: Reliabilism and Social Epistemology: Problems and Prospects, Cologne, 24–28 August. Studentships PhD Scholarship in Logic: University of Groningen, The Netherlands, deadline 1 May. PhD Position in cognitive science: Department of Philosophy in Lund, Sweden, 13 May. 3 PhD fellowships: Department of Economics (IRES) and the Hoover Chair in Economic and Social Ethics, Louvain-la-Neuve, 15 May. PhD Position: Project “Context and Communication”, Instituto de Filosofia da Linguagem, Universidade nova de Lisboa, Portugal, 20 May. PhD Studentship: 3-year AHRC studentship in the Foundations of Logical Consequence project, University of St Andrews, until filled.