What Can Artificial Intelligence Do for Scientific Realism?

The paper proposes a synthesis between human scientists and artificial representation learning models as a way of augmenting epistemic warrants of realist theories against various anti-realist attempts. Towards this end, the paper fleshes out unconceived alternatives not as a critique of scientific realism but rather a reinforcement, as it rejects the retrospective interpretations of scientific progress, which brought about the problem of alternatives in the first place. By utilising adversarial machine learning, the synthesis explores possibility spaces of available evidence for unconceived alternatives providing modal knowledge of what is possible therein. As a result, the epistemic warrant of synthesised realist theories should emerge bolstered as the underdetermination by available evidence gets reduced. While shifting the realist commitment away from theoretical artefacts towards modalities of the possibility spaces, the synthesis comes out as a kind of perspectival modelling

The future of human nature: a symposium on the promises and challenges of the revolutions in genomics and computer science, April 10, 11, and 12, 2003

This repository item contains a single issue of the Pardee Conference Series, a publication series that began publishing in 2006 by the Boston University Frederick S. Pardee Center for the Study of the Longer-Range Future. This was the Center's Symposium on the Promises and Challenges of the Revolutions in Genomics and Computer Science took place during April 10, 11, and 12, 2003. Co-organized by Charles DeLisi and Kenneth Lewes; sponsored by Boston University, the Frederick S. Pardee Center for the Study of the Longer-Range Future.This conference focused on scientific and technological advances in genetics, computer science, and their convergence during the next 35 to 250 years. In particular, it focused on directed evolution, the futures it allows, the shape of society in those futures, and the robustness of human nature against technological change at the level of individuals, groups, and societies. It is taken as a premise that biotechnology and computer science will mature and will reinforce one another. During the period of interest, human cloning, germ-line genetic engineering, and an array of reproductive technologies will become feasible and safe. Early in this period, we can reasonably expect the processing power of a laptop computer to exceed the collective processing power of every human brain on the planet; later in the period human/machine interfaces will begin to emerge. Whether such technologies will take hold is not known. But if they do, human evolution is likely to proceed at a greatly accelerated rate; human nature as we know it may change markedly, if it does not disappear altogether, and new intelligent species may well be created

Reasoning about correctness properties of a coordination programming language

Safety critical systems place additional requirements to the programming language used to implement them with respect to traditional environments. Examples of features that in uence the suitability of a programming language in such environments include complexity of de nitions, expressive power, bounded space and time and veri ability. Hume is a novel programming language with a design which targets the rst three of these, in some ways, contradictory features: fully expressive languages cannot guarantee bounds on time and space, and low-level languages which can guarantee space and time bounds are often complex and thus error-phrone. In Hume, this contradiction is solved by a two layered architecture: a high-level fully expressive language, is built on top of a low-level coordination language which can guarantee space and time bounds. This thesis explores the veri cation of Hume programs. It targets safety properties, which are the most important type of correctness properties, of the low-level coordination language, which is believed to be the most error-prone. Deductive veri cation in Lamport's temporal logic of actions (TLA) is utilised, in turn validated through algorithmic experiments. This deductive veri cation is mechanised by rst embedding TLA in the Isabelle theorem prover, and then embedding Hume on top of this. Veri cation of temporal invariants is explored in this setting. In Hume, program transformation is a key feature, often required to guarantee space and time bounds of high-level constructs. Veri cation of transformations is thus an integral part of this thesis. The work with both invariant veri cation, and in particular, transformation veri cation, has pinpointed several weaknesses of the Hume language. Motivated and in uenced by this, an extension to Hume, called Hierarchical Hume, is developed and embedded in TLA. Several case studies of transformation and invariant veri cation of Hierarchical Hume in Isabelle are conducted, and an approach towards a calculus for transformations is examined.James Watt ScholarshipEngineering and Physical Sciences Research Council (EPSRC) Platform grant GR/SO177

The future of human nature: a symposium on the promises and challenges of the revolutions in genomics and computer science, April 10, 11, and 12, 2003

This repository item contains a single issue of the Pardee Conference Series, a publication series that began publishing in 2006 by the Boston University Frederick S. Pardee Center for the Study of the Longer-Range Future. This was the Center's Symposium on the Promises and Challenges of the Revolutions in Genomics and Computer Science took place during April 10, 11, and 12, 2003. Co-organized by Charles DeLisi and Kenneth Lewes; sponsored by Boston University, the Frederick S. Pardee Center for the Study of the Longer-Range Future.This conference focused on scientific and technological advances in genetics, computer science, and their convergence during the next 35 to 250 years. In particular, it focused on directed evolution, the futures it allows, the shape of society in those futures, and the robustness of human nature against technological change at the level of individuals, groups, and societies. It is taken as a premise that biotechnology and computer science will mature and will reinforce one another. During the period of interest, human cloning, germ-line genetic engineering, and an array of reproductive technologies will become feasible and safe. Early in this period, we can reasonably expect the processing power of a laptop computer to exceed the collective processing power of every human brain on the planet; later in the period human/machine interfaces will begin to emerge. Whether such technologies will take hold is not known. But if they do, human evolution is likely to proceed at a greatly accelerated rate; human nature as we know it may change markedly, if it does not disappear altogether, and new intelligent species may well be created

Prototype of running clinical trials in an untrustworthy environment using blockchain.

Monitoring and ensuring the integrity of data within the clinical trial process is currently not always feasible with the current research system. We propose a blockchain-based system to make data collected in the clinical trial process immutable, traceable, and potentially more trustworthy. We use raw data from a real completed clinical trial, simulate the trial onto a proof of concept web portal service, and test its resilience to data tampering. We also assess its prospects to provide a traceable and useful audit trail of trial data for regulators, and a flexible service for all members within the clinical trials network. We also improve the way adverse events are currently reported. In conclusion, we advocate that this service could offer an improvement in clinical trial data management, and could bolster trust in the clinical research process and the ease at which regulators can oversee trials

Knowledge-based systems and geological survey

This personal and pragmatic review of the philosophy underpinning methods of geological surveying suggests that important influences of information technology have yet to make their impact. Early approaches took existing systems as metaphors, retaining the separation of maps, map explanations and information archives, organised around map sheets of fixed boundaries, scale and content. But system design should look ahead: a computer-based knowledge system for the same purpose can be built around hierarchies of spatial objects and their relationships, with maps as one means of visualisation, and information types linked as hypermedia and integrated in mark-up languages. The system framework and ontology, derived from the general geoscience model, could support consistent representation of the underlying concepts and maintain reference information on object classes and their behaviour. Models of processes and historical configurations could clarify the reasoning at any level of object detail and introduce new concepts such as complex systems. The up-to-date interpretation might centre on spatial models, constructed with explicit geological reasoning and evaluation of uncertainties. Assuming (at a future time) full computer support, the field survey results could be collected in real time as a multimedia stream, hyperlinked to and interacting with the other parts of the system as appropriate. Throughout, the knowledge is seen as human knowledge, with interactive computer support for recording and storing the information and processing it by such means as interpolating, correlating, browsing, selecting, retrieving, manipulating, calculating, analysing, generalising, filtering, visualising and delivering the results. Responsibilities may have to be reconsidered for various aspects of the system, such as: field surveying; spatial models and interpretation; geological processes, past configurations and reasoning; standard setting, system framework and ontology maintenance; training; storage, preservation, and dissemination of digital records