We all highly depend and rely on the trustworthiness of information and services provided by various parties and institutions. Reputation systems are one possibility to support individuals in distinguishing trustworthy partners from malicious and unreliable parties. In this paper, we discuss possibilities and limitations of different types of reputation systems and their underlying trust models. We address in especially the properties of trust relations, the quantification and representation of trust values as well as reasoning and computation with trust.
The recent development of the research field of Computing and Philosophy has triggered investigations into the theoretical foundations of computing and information.This thesis consists of two parts which are the result of studies in two areas of Philosophy of Computing (PC) and Philosophy of Information (PI) regarding the production of meaning (semantics) and the value system with applications (ethics).The first part develops a unified dual-aspect theory of information and computation, in which information is characterized as structure, and computation is the information dynamics. This enables naturalization of epistemology, based on interactive information representation and communication. In the study of systems modeling, meaning, truth and agency are discussed within the framework of the PI/PC unification.The second part of the thesis addresses the necessity of ethical judgment in rational agency illustrated by the problem of information privacy and surveillance in the networked society. The value grounds and socio-technological solutions for securing trustworthiness of computing are analyzed. Privacy issues clearly show the need for computing professionals to contribute to understanding of the technological mechanisms of Information and Communication Technology.The main original contribution of this thesis is the unified dual-aspect theory of computation/information. Semantics of information is seen as a part of the data-information-knowledge structuring, in which complex structures are self-organized by the computational processing of information. Within the unified model, complexity is a result of computational processes on informational structures. The thesis argues for the necessity of computing beyond the Turing-Church limit, motivated by natural computation, and wider by pancomputationalism and paninformationalism, seen as two complementary views of the same physical reality. Moreover, it follows that pancomputationalism does not depend on the assumption that the physical world on some basic level is digital. Contrary to many believes it is entirely compatible with dual (analogue/digital) quantum-mechanical computing.
This work draws on the cultural historical activity-theory and the theory of social systems to model socio-technical systems. The concepts of practice, system, and context work as core concepts to represent processes and activities such as learning and working. Current modeling approaches in the field of learning and work resemble the notion of workflows, relating input and output in a means-end-manner and prescribing the processes, and hence fall short in describing the situated and socially mediated nature of practices. Against this background the paper presents and describes an alternative modeling approach as well as its theoretical foundation and practical implications. It is characterized by (1) going beyond de-contextualized actions, objects, and resources and by (2) going beyond the decomposition of activities as it does not equate the sequence of actions with the respective activity.
In this paper I argue that recent technological transformations in the life-cycle of information have brought about a fourth revolution, in the long process of reassessing humanity’s fundamental nature and role in the universe. We are not immobile, at the centre of the universe (Copernicus); we are not unnaturally distinct and different from the rest of the animal world (Darwin); and we are far from being entirely transparent to ourselves (Freud). We are now slowly accepting the idea that we might be informational organisms among many agents (Turing), inforgs not so dramatically different from clever, engineered artefacts, but sharing with them a global environment that is ultimately made of information, the infosphere. This new conceptual revolution is humbling, but also exciting. For in view of this important evolution in our self-understanding, and given the sort of IT-mediated interactions that humans will increasingly enjoy with a variety of other agents, whether natural or synthetic, we have the unique opportunity of developing a new ecological approach to the whole of reality.
This paper discusses current conceptions of ontology in computer science focussing on cultural specification and temporalization. It is pointed out, first, that ontologies arrange the world, they do not represent it; second, that ontologies, except logical Formal Ontologies, can be developed within a cultural framework; third, Top Level and Domain Ontologies have to be complemented by Pragmatic Ontologies, if they are to be used in every-day life; fourth, Pragmatic Ontologies magnify the problem of temporalizing ontologies.
The paper presents a paradoxical feature of computational systems that suggests that computationalism cannot explain symbol grounding. If the mind is a digital computer, as computationalism claims, then it can be computing either over meaningful symbols or over meaningless symbols. If it is computing over meaningful symbols its functioning presupposes the existence of meaningful symbols in the system, i.e. it implies semantic nativism. If the mind is computing over meaningless symbols, no intentional cognitive processes are available prior to symbol grounding. In this case, no symbol grounding could take place since any grounding presupposes intentional cognitive processes. So, whether computing in the mind is over meaningless or over meaningful symbols, computationalism implies semantic nativism.
Many of our modern computerized activities, may they be personal, industrial or artistic, involve searching, classifying and browsing large numbers of digital objects. The tools we have at hand, however, are poorly adapted as they are often too formal: we illustrate this matter in the first section of this article, with the example of multimedia collections. We then propose a software tool for dealing with digital collections in a less formal manner. Finally, we see that our software design is strongly backed up by both artistic and psychological knowledge concerning the ancient human activity of collecting, which we will see can be described as a metaphor for categorization in which two irreducible cognitive modes are at play: aspectual similarity and spatio-temporal proximity. ReCollection, the software we have designed to experiment and demonstrate these ideas may be useful in many areas of musical creation, from sound synthesis to archiving, editing and publishing content, and also simulating musical perception.
Modern Information Science deals with tasks which include classifying, searching and browsing large numbers of digital objects. The problem today is that our computerized tools are poorly adapted to our needs as they are often too formal: we illustrate this matter in the first section of this article with the example of multimedia collections. We then propose a software tool, ReCollection, for dealing with digital collections in a less formal and more sustainable manner. Finally, we explain how our software design is strongly backed up by both artistic and psychological knowledge concerning the ancient human activity of collecting, which we will see can be described as a metaphor for categorization in which two irreducible cognitive modes are at play: aspectual similarity and spatio-temporal proximity.
The philosophical approach to searching the truth is akin to geophysical Baysian inversion of potential fields. Karl Popper proposed that science approaches the infinitely distant truth by challenging and falsifying existing hypotheses and theories. The kinship between the two is that " truth " is as much hidden in both fields of human endeavour. Bayesian inversion is built on the assumption that a " true " model exists which gives observable signals which are used to determine and to optimize the model parameters. For this we must know the " sensitivities " of the observations to changes of all the adjustable model parameters (i.e. the Jacobian). In geophysical potential fields as gravity and magnetics, inversion is infinitely ambiguous. An infinite set of mass models exist which generate the same external field; in other words, an infinite set of " difference models " generate no external field, the set is called the " null space ". On the other hand, there is an even larger model set which generates different fields. Any of such models can be excluded by gravity inversion. A reduction of the null space is possible by invoking a priori knowledge. It is an indispensable precondition for any meaningful inversion to be obtained. The Bayesian approach is to regard the a priori information as having the same categorical status as the observations to be " explained " or " fitted ". Both are treated in the same way. A priori model parameters are " optimized " within their error limits, as the model effects are fitted to the observations within their error limits. Solutions are as reliable, as the errors or uncertainties allow. It is therefore essential to estimate the errors and model uncertainties as " carefully " as possible. A few examples are presented to make the point. So, I think that philosophy is an inversion procedure. Philosophically, we attempt to understand complex and multiple observations and confront our pre-existing ideas, hypotheses, theories with them. We are in the same situation as the geophysicist. We build a models and " calculate " or predict their effects or consequences which can be checked by observations. From Bayesian inversion we can learn that we must be most concerned about the uncertainties of any of the complex model features and predictions. We must also be fully aware of the fact that agreement between prediction and observations is only a necessary …
Knowledge management systems (KMS) are increasingly becoming popular and important in managing organizational knowledge. This motivates a closer inspection of the degree of usability of various types of KMS. This paper is an analysis of KMS from a philosophical angle: with the help of veritistic social epistemology we analyze which KMS are likely to be used more in comparison to others. Veritistic social epistemology is oriented towards truth determination; it seeks to evaluate actual and prospective multi-person practices in terms of their tendency to produce true beliefs (versus false beliefs or no belief) in their users. We distinguish between KMS that manage structured knowledge and those that manage unstructured knowledge. It is argued that structured knowledge is more credible to the users than unstructured knowledge and that, because of this, KMS that manage structured knowledge bring more veritistic gains than those that manage unstructured knowledge.
I introduce the notion of knowledge relativityas a proposed conceptual link between different scientific disciplines. Examples from Informatics and Philosophy, particularly Newell’s knowledge level hypothesis and Popper’s world 3 of knowledge, are used to demonstrate the motivation for making this notion ex-
We examine the possibility of applying knowledge representation and automated reasoning in the context of philosophical ontology. For this purpose, we use the axioms and propositions in the first book of Spinoza’s Ethics as knowledge base and a tableau-based satisfiability tester as reasoner. We are able to reconstruct most of Spinoza’s system with formal logic, but this requires additional axioms which are assumed implicitly by Spinoza. This study illustrates how tools developed in computer science can be of practical use for philosophy.
Conceptual Modeling is a discipline of great relevance to several areas in Computer Science. In a series of papers [1,2,3] we have been using the General Ontological Language (GOL) and its underlying upper level ontology, proposed in [4,5], to evaluate the ontological correctness of conceptual models and to develop guidelines for how the constructs of a modeling language (UML) should be used in conceptual modeling. In this paper, we focus on the modeling metaconcepts of classifiers and objects from an ontological point of view. We use a philosophically and psychologically well-founded theory of universals to propose a UML profile for Ontology Representation and Conceptual Modeling. The formal semantics of the proposed modeling elements is presented in a language of modal logics with quantification restricted to Sortal universals.
Paradoxes, particularly Tarski’s liar paradox, represent an ongoing challenge that have long attracted special interest. There have been numerous attempts to give either a formal or a more realistic resolution to this area based on natural logical intuition or common sense. The present semantic analysis of the problem components concludes that the traditional language of logic fails to detect Tarski’s paradox, since the formalised version of the liar sentence does not represent a correct definition. Neither the formal language, nor the logical system is deficient in this respect. Only natural language statements cannot be interpreted adequately by traditional language of logic.
In the main research of internet-computing enabled knowledge management, we use some of the most advanced research scenarios, arguing that we critically need a system approach to question where knowledge comes from. In particular, within a given engineering domain, we synthesis the problems and reveal, that the knowledge is embraced by interactions among systems, system observers, observables, engineering objects and instruments; that the complex system interactions must be dispatched into infrastructural layers based on physicsontologies; that the ontologies must be dedicated to human and data communications. Such a synthesis would impact on knowledge technologies for solving engineering problems in scalabilities, as well as in collective vocabularies that must associate with the communication crossing the layers in the problem solving environment.
The collaboration of Language and Computing nv (L&C) and the Institute for Formal Ontology and Medical Information Science (IFOMIS) is guided by the hypothesis that quality constraints on ontologies for software applications purposes closely parallel the constraints salient to the design of sound philosophical theories. The extent of this parallel has been poorly appreciated in the informatics community, and it turns out that importing the benefits of philosophical insight and methodology into applications domains yields diverse improvements. L&C’s LinKBase® is one of the world’s largest medical domain ontologies. Its current primary use pertains to natural language processing applications, but it also supports intelligent navigation through a range of structured medical and bioinformatics information resources, such as UMLS, SNOMED, Swiss-Prot, and the Gene Ontology (GO). In this report we discuss how and why philosophical methods improve both the internal coherence of LinKBase®, and its capacity to serve as a translation hub, improving the interoperability of the ontologies it embeds.
In this paper, we show how the practice of buying CDs surreptitiously conditions our musical activities, and how the practice of classifying a priori, making changes one at a time, structured by buying and the notion of genre, will disappear, as develops an ad-hoc organization of auditory samples, centered on prototypes and similarity. This movement is a proof of the loss of importance of the instantiation of CD marketing categories. Thus appears similarity-based calculus, acting on considerable masses of samples, which continuously change the balance of the man-machine dialogue, in an appeal started again and again to compare information. We also show how some artistic creations which rely heavily on computers, especially in the domain of inter-media theater, proceed in the same way, masking instantiation and developing the calculation of the similarity of the comedian's expressive faces. Art and culture are linked in processes that take advantage of their massive digitalization.
In this paper we wish to examine a deeper issue underlying conceptual modeling, namely what could constitute conceptual meaning. Accordingly we have chosen to compare an analysis of “Metapattern” [8], with “Contragrammar” [4]. We note that there are distinct similarities between Metapattern and Contragrammar at the stage of (1) an exchange of redundancy, and (2) flexibility through relative concepts. Conceptual modeling is an important aspect of Knowledge Management, and, clearly, as concepts vary with ‘situations,’ conceptual modeling must accommodate those variations. From this paper, it is hoped that, by examining features of Metapattern in relation to Contragrammar, we can thereby see why ‘situations’ entail meaning, and why Metapattern works as a model of behaviour, and why Contragrams can capture an essential feature of that ‘situational’ meaning.
