The double dance of agency: a socio-theoretic account of how machines and humans interact

The nature of the relationship between information technology (IT) and organizations has been a long-standing debate in the Information Systems literature. Does IT shape organizations, or do people in organisations control how IT is used? To formulate the question a little differently: does agency (the capacity to make a difference) lie predominantly with machines (computer systems) or humans (organisational actors)? Many proposals for a middle way between the extremes of technological and social determinism have been put advanced; in recent years researchers oriented towards social theories have focused on structuration theory and (lately) actor network theory. These two theories, however, adopt different and incompatible views of agency. Thus, structuration theory sees agency as exclusively a property of humans, whereas the principle of general symmetry in actor network theory implies that machines may also be agents. Drawing on critiques of both structuration theory and actor network theory, this paper develops a theoretical account of the interaction between human and machine agency: the double dance of agency. The account seeks to contribute to theorisation of the relationship between technology and organisation by recognizing both the different character of human and machine agency, and the emergent properties of their interplay.

How much do we spend to save? Calculating the embodied carbon costs of retrofit

The drive to reduce carbon emissions from domestic housing has led to a recent shift of focus from new-­‐build to retrofit. However there are two significant differences. Firstly more work is needed to retrofit existing housing to the same energy efficiency standards as new-­‐build. Secondly the remaining length of service life is potentially shorter. This implies that the capital expenditure – both financial and carbon -­‐ of retrofit may be disproportionate to the savings gained over the remaining life. However the Government’s definition of low and zero carbon continues to exclude the capital (embodied) carbon costs of construction, which has resulted in a lack of data for comparison. The paper addresses this gap by reporting the embodied carbon costs of retrofitting four individual pilot properties in Rampton Drift, part of an Eco-­‐Town Demonstrator Project in Cambridgeshire. Through collecting details of the materials used and their journeys from manufacturer to site, the paper conducts a ‘cradle-­‐to-­‐gate’ life cycle carbon assessment for each property. The embodied carbon figures are calculated using a software tool being developed by the Centre for Sustainable Development at the University of Cambridge. The key aims are to assess the real embodied carbon costs of retrofit of domestic properties, and to test the new tool; it is hoped that the methodology, the tool and the specific findings will be transferable to other projects. Initial changes in operational energy as a result of the retrofit works will be reported and compared with the embodied carbon costs when presenting this paper.

How neurons migrate: a dynamic in-silico model of neuronal migration in the developing cortex.

BACKGROUND: Neuronal migration, the process by which neurons migrate from their place of origin to their final position in the brain, is a central process for normal brain development and function. Advances in experimental techniques have revealed much about many of the molecular components involved in this process. Notwithstanding these advances, how the molecular machinery works together to govern the migration process has yet to be fully understood. Here we present a computational model of neuronal migration, in which four key molecular entities, Lis1, DCX, Reelin and GABA, form a molecular program that mediates the migration process. RESULTS: The model simulated the dynamic migration process, consistent with in-vivo observations of morphological, cellular and population-level phenomena. Specifically, the model reproduced migration phases, cellular dynamics and population distributions that concur with experimental observations in normal neuronal development. We tested the model under reduced activity of Lis1 and DCX and found an aberrant development similar to observations in Lis1 and DCX silencing expression experiments. Analysis of the model gave rise to unforeseen insights that could guide future experimental study. Specifically: (1) the model revealed the possibility that under conditions of Lis1 reduced expression, neurons experience an oscillatory neuron-glial association prior to the multipolar stage; and (2) we hypothesized that observed morphology variations in rats and mice may be explained by a single difference in the way that Lis1 and DCX stimulate bipolar motility. From this we make the following predictions: (1) under reduced Lis1 and enhanced DCX expression, we predict a reduced bipolar migration in rats, and (2) under enhanced DCX expression in mice we predict a normal or a higher bipolar migration. CONCLUSIONS: We present here a system-wide computational model of neuronal migration that integrates theory and data within a precise, testable framework. Our model accounts for a range of observable behaviors and affords a computational framework to study aspects of neuronal migration as a complex process that is driven by a relatively simple molecular program. Analysis of the model generated new hypotheses and yet unobserved phenomena that may guide future experimental studies. This paper thus reports a first step toward a comprehensive in-silico model of neuronal migration.