The Future Evolution of Consciousness

ABSTRACT. What potential exists for improvements in the functioning of consciousness? The paper addresses this issue using global workspace theory. According to this model, the prime function of consciousness is to develop novel adaptive responses. Consciousness does this by putting together new combinations of knowledge, skills and other disparate resources that are recruited from throughout the brain. The paper’s search for potential improvements in the functioning of consciousness draws on studies of the shift during human development from the use of implicit knowledge to the use of explicit (declarative) knowledge. These studies show that the ability of consciousness to adapt a particular domain improves significantly as the transition to the use of declarative knowledge occurs in that domain. However, this potential for consciousness to enhance adaptability has not yet been realised to any extent in relation to consciousness itself. The paper assesses the potential for adaptability to be improved by the conscious adaptation of key processes that constitute consciousness. A number of sources (including the practices of religious and contemplative traditions) are drawn on to investigate how this potential might be realised

Reflective Composition: the declarative composition of roles to unify objects, roles, and aspects [poster session]

As bases for object-orientation, both class-based and prototype-based organization have limitations. We argue that roles have significant benefits as a foundation for organizing objects. We further argue that these benefits can be realised most flexibly using logic meta-programming. Additional benefits from this approach are to reduce redundancy and subsume aspects

Emergent processes as generation of discontinuities

In this article we analyse the problem of emergence in its diachronic dimension. In other words, we intend to deal with the generation of novelties in natural processes. Our approach aims at integrating some insights coming from Whitehead’s Philosophy of the Process with the epistemological framework developed by the “autopoietic” tradition. Our thesis is that the emergence of new entities and rules of interaction (new “fields of relatedness”) requires the development of discontinuous models of change. From this standpoint natural evolution can be conceived as a succession of emergences — each one realizing a novel “extended” present, described by distinct models — rather than as a single and continuous dynamics. This theoretical and epistemological framework is particularly suitable to the investigation of the origin of life, an emblematic example of this kind of processes

Pattern Reification as the Basis for Description-Driven Systems

One of the main factors driving object-oriented software development for information systems is the requirement for systems to be tolerant to change. To address this issue in designing systems, this paper proposes a pattern-based, object-oriented, description-driven system (DDS) architecture as an extension to the standard UML four-layer meta-model. A DDS architecture is proposed in which aspects of both static and dynamic systems behavior can be captured via descriptive models and meta-models. The proposed architecture embodies four main elements - firstly, the adoption of a multi-layered meta-modeling architecture and reflective meta-level architecture, secondly the identification of four data modeling relationships that can be made explicit such that they can be modified dynamically, thirdly the identification of five design patterns which have emerged from practice and have proved essential in providing reusable building blocks for data management, and fourthly the encoding of the structural properties of the five design patterns by means of one fundamental pattern, the Graph pattern. A practical example of this philosophy, the CRISTAL project, is used to demonstrate the use of description-driven data objects to handle system evolution.Comment: 20 pages, 10 figure

Governance, scale and the environment: the importance of recognizing knowledge claims in transdisciplinary arenas

Any present day approach of the world’s most pressing environmental problems involves both scale and governance issues. After all, current local events might have long-term global consequences (the scale issue) and solving complex environmental problems requires policy makers to think and govern beyond generally used time-space scales (the governance issue). To an increasing extent, the various scientists in these fields have used concepts like social-ecological systems, hierarchies, scales and levels to understand and explain the “complex cross-scale dynamics” of issues like climate change. A large part of this work manifests a realist paradigm: the scales and levels, either in ecological processes or in governance systems, are considered as “real”. However, various scholars question this position and claim that scales and levels are continuously (re)constructed in the interfaces of science, society, politics and nature. Some of these critics even prefer to adopt a non-scalar approach, doing away with notions such as hierarchy, scale and level. Here we take another route, however. We try to overcome the realist-constructionist dualism by advocating a dialogue between them on the basis of exchanging and reflecting on different knowledge claims in transdisciplinary arenas. We describe two important developments, one in the ecological scaling literature and the other in the governance literature, which we consider to provide a basis for such a dialogue. We will argue that scale issues, governance practices as well as their mutual interdependencies should be considered as human constructs, although dialectically related to nature’s materiality, and therefore as contested processes, requiring intensive and continuous dialogue and cooperation among natural scientists, social scientists, policy makers and citizens alike. They also require critical reflection on scientists’ roles and on academic practices in general. Acknowledging knowledge claims provides a common ground and point of departure for such cooperation, something we think is not yet sufficiently happening, but which is essential in addressing today’s environmental problems

Learning from AI : new trends in database technology

Recently some researchers in the areas of database data modelling and knowledge representations in artificial intelligence have recognized that they share many common goals. In this survey paper we show the relationship between database and artificial intelligence research. We show that there has been a tendency for data models to incorporate more modelling techniques developed for knowledge representations in artificial intelligence as the desire to incorporate more application oriented semantics, user friendliness, and flexibility has increased. Increasing the semantics of the representation is the key to capturing the "reality" of the database environment, increasing user friendliness, and facilitating the support of multiple, possibly conflicting, user views of the information contained in a database