AI: Inventing a new kind of machine.

A means-ends approach to engineering an artificial intelligence machine now suggests that we focus on the differences between human capabilities and the best computer programs. These differences suggest two basic limitations in the "symbolic" approach. First, human memory is much more than a storehouse where structures are put away, indexed, and rotely retrieved. Second, human reasoning involves more than searching, matching, and recombining previously stored descriptions of situations and action plans. Indeed, these hypotheses are related: Remembering and reasoning both involve reconceptualization. This short paper outlines recent work in situated cognition, robotics, and neural networks that suggests we frame the problem if AI in terms of inventing a new kind of machine

Does Phenomenal Consciousness Overflow Attention? An Argument from Feature-Integration

In the past two decades a number of arguments have been given in favor of the possibility of phenomenal consciousness without attentional access, otherwise known as phenomenal overflow. This paper will show that the empirical data commonly cited in support of this thesis is, at best, ambiguous between two equally plausible interpretations, one of which does not posit phenomenology beyond attention. Next, after citing evidence for the feature-integration theory of attention, this paper will give an account of the relationship between consciousness and attention that accounts for both the empirical data and our phenomenological intuitions without positing phenomenal consciousness beyond attention. Having undercut the motivations for accepting phenomenal overflow along with having given reasons to think that phenomenal overflow does not occur, I end with the tentative conclusion that attention is a necessary condition for phenomenal consciousness

Towards Exascale Scientific Metadata Management

Advances in technology and computing hardware are enabling scientists from all areas of science to produce massive amounts of data using large-scale simulations or observational facilities. In this era of data deluge, effective coordination between the data production and the analysis phases hinges on the availability of metadata that describe the scientific datasets. Existing workflow engines have been capturing a limited form of metadata to provide provenance information about the identity and lineage of the data. However, much of the data produced by simulations, experiments, and analyses still need to be annotated manually in an ad hoc manner by domain scientists. Systematic and transparent acquisition of rich metadata becomes a crucial prerequisite to sustain and accelerate the pace of scientific innovation. Yet, ubiquitous and domain-agnostic metadata management infrastructure that can meet the demands of extreme-scale science is notable by its absence. To address this gap in scientific data management research and practice, we present our vision for an integrated approach that (1) automatically captures and manipulates information-rich metadata while the data is being produced or analyzed and (2) stores metadata within each dataset to permeate metadata-oblivious processes and to query metadata through established and standardized data access interfaces. We motivate the need for the proposed integrated approach using applications from plasma physics, climate modeling and neuroscience, and then discuss research challenges and possible solutions

How we might be able to Understand the Brain

Current methodologies in the neurosciences have difficulty in accounting for complex phenomena such as language, which can however be quite well characterised in phenomenological terms. This paper addresses the issue of unifying the two approaches. We typically understand complicated systems in terms of a collection of models, each characterisable in principle within a formal system, it being possible to explain higher-level properties in terms of lower level ones by means of a series of inferences based on these models. We consider the nervous system to be a mechanism for implementing the demands of an appropriate collection of models, each concerned with some aspect of brain and behaviour, the observer mechanism of Baas playing an important role in matching model and behaviour in this context. The discussion expounds these ideas in detail, showing their potential utility in connection with real problems of brain and behaviour, important areas where the ideas can be applied including the development of higher levels of abstraction, and linguistic behaviour, as described in the works of Karmiloff-Smith and Jackendoff respectively

Autism genetics: searching for specificity and convergence.

Advances in genetics and genomics have improved our understanding of autism spectrum disorders. As many genes have been implicated, we look to points of convergence among these genes across biological systems to better understand and treat these disorders

Evolutionary psychologically predicted biases in the manifestation of cognitive dissonance : an exploration : a thesis presented in partial fulfilment of the requirements for the degree of Master of Arts in Psychology, Massey University, Palmerston North, New Zealand

It was hypothesised that over evolutionary time, selection pressures have generated a cerebral modularity which detects survival and reproduction related contradictions preferentially over others. It was also hypothesised that contradiction-detecting mechanisms are rendered less effective if contradictions are implicit rather than explicit, or refer to the future rather than the immediate present. Explicit and implicit contradictions pertaining to the above conditions were embedded in narratives to test these hypotheses. Participants read the narratives via a computer screen, pressing the keyboard space bar to progress through the narratives line by line. A programme recorded reading times (RTs) of each narrative line. An extended RT for a line contradicting an earlier one was interpreted as indicating the generation of cognitive dissonance consequent to detecting the contradiction. A questionnaire was used to ascertain participants' subjective reactions. Analysis of the RTs provided some evidence that the hypothesised modularity exists for reproduction-related contradictions. The results, particularly those relating to survival, suggest that detection of subject matter related modularity is hindered by heterogeneous phrasing and/or the generation of mortality-related emotions. As predicted, implicit contradictions were less frequently noticed. The phrasing employed did not yield any timeframe-related difference in noticeability