fMRI for severely brain injured patients: A media analysis

This thesis was submitted for the degree of Doctor of Philosophy and awarded by Brunel University .This thesis is set in the context of social science’s interest in the generation of expectations, the news media, and neurotechnologies. It is a qualitative case study that examines the nature and impact of news media reporting of some pioneering research, which used functional magnetic resonance imaging in an attempt to diagnose and communicate with severely brain-injured individuals. Previous news media studies exploring neurotechnologies have been quantitative, or have tended to focus on how or why the news media represents neurotechnologies and/or the impact of the reporting, but rarely all three together. My thesis looks at all three aspects of the news media reporting of my case study. I draw on three sets of empirical data. First, those related to the production of the media - the press releases which reported the research; ten semi-structured interviews with science press officers; and the relevant expert comments posted on the Science Media Centre’s website. Second, 51 newspaper articles reporting the research. Third, five semi-structured interviews with relatives of severely brain-injured patients. I show that the mood of excitement and ‘breakthrough’ present in the press release reporting of this research was closely echoed in the news coverage. This excitement influenced the views and beliefs of only some of the relatives I interviewed. I then examine the nature of hype and by drawing on Haraway’s concept of ‘situated knowledges’ (1988) I argue that individuals view hype differently depending on their profession, industry and/or socio-cultural background. Finally, I show how whilst both the news media and the scholarly literature portrayed this research as ethically contentious, the issues most prominently discussed by scholars and/or journalists do not necessarily equate with relatives’ concerns. My findings aim to contribute to the sociology of expectations, media theory, the sociology of bioethics and the public understanding of science

The UK’s 100,000 Genomes Project: manifesting policymakers’ expectations

The UK’s 100,000 Genomes Project has the aim of sequencing 100,000 genomes from UK National Health Service (NHS) patients while concomitantly transforming clinical care such that whole genome sequencing becomes routine clinical practice in the UK. Policymakers claim that the project will revolutionize NHS care. We wished to explore the 100,000 Genomes Project, and in particular, the extent to which policymaker claims have helped or hindered the work of those associated with Genomics England – the company established by the Department of Health to deliver the project. We interviewed 20 individuals linked to, or working for Genomics England. Interviewees had double-edged views about the context within which they were working. On the one hand, policymakers’ expectations attached to the venture were considered vacuous “genohype”; on the other hand, they were considered the impetus needed for those trying to advance genomic research into clinical practice. Findings should be considered for future genomes projects

Genomics England’s implementation of its public engagement strategy: blurred boundaries between engagement for the UK’s 100,000 Genomes Project and the need for public support

The UK’s 100,000 Genomes Project has the aim of sequencing 100,000 genomes from National Health Service patients such that whole genome sequencing becomes routine clinical practice. It also has a research-focused goal to provide data for scientific discovery. Genomics England is the limited company established by the Department of Health to deliver the project. As an innovative scientific/clinical venture it is interesting to consider how Genomics England positions itself in relation to public engagement activities. We set out to explore how individuals working at, or associated with Genomics England, enacted public engagement in practice. Our findings show that individuals offered a narrative in which public engagement performed more than one function. On one side public engagement was seen as ‘good practice’. On the other, public engagement was presented as core to the project’s success – needed to encourage involvement and ultimately recruitment. We discuss the implications of this in this paper

Drivers and constraints to environmental sustainability in UK-based biobanking: balancing resource efficiency and future value

Background: Biobanks are a key aspect of healthcare research; they enable access to a wide range of heterogenous samples and data, as well as saving individual researchers time and funds on the collection, storage and/or curation of such resources. However, biobanks are also associated with impacts associated with a depletion of natural resources (energy, water etc.) production of toxic chemicals during manufacturing of laboratory equipment, and effects on biodiversity. We wanted to better understand the biobanking sector in the UK as a first step to assessing the environmental impacts of UK biobanking. // Methods: We explored the sample storage infrastructure and environmental sustainability practices at a number of UK biobanks through a mixed methods quantitative and qualitative approach, including information gathering on an online platform, and eight in-depth interviews. // Results: Environmental sustainability was deprioritised behind biobanks’ financial sustainability practices. Nevertheless, both often aligned in practice. However, there was a tendency towards underutilisation of stored samples, the avoidance of centralisation, and providing accessibility to biosamples, and this conflicted with valuing sustainability goals. This related to notions of individualised and competitive biobanking culture. Furthermore, the study raised how value attachments to biosamples overshadows needs for both financial and environmental sustainability concerns. // Conclusions: We need to move away from individualised and competitive biobanking cultures towards a realisation that the health of the publics and patients should be first and foremost. We need to ensure the use of biosamples, ahead of their storage (‘smart attachments’), align with environmental sustainability goals and participants’ donation wishes for biosample use

The evaluation scale:exploring decisions about societal impact in peer review panels

Realising the societal gains from publicly funded health and medical research requires a model for a reflexive evaluation precedent for the societal impact of research. This research explores UK Research Excellence Framework evaluators’ values and opinions and assessing societal impact, prior to the assessment taking place. Specifically, we discuss the characteristics of two different impact assessment extremes – the “quality-focused” evaluation and “societal impact-focused” evaluation. We show the wide range of evaluator views about impact, and that these views could be conceptually reflected in a range of different positions along a conceptual evaluation scale. We describe the characteristics of these extremes in detail, and discuss the different beliefs evaluators had which could influence where they positioned themselves along the scale. These decisions, we argue, when considered together, form a dominant definition of societal impact that influences the direction of its evaluation by the panel

Efficiency is Not Enough: A Critical Perspective of Environmentally Sustainable AI

Artificial Intelligence (AI) is currently spearheaded by machine learning (ML) methods such as deep learning (DL) which have accelerated progress on many tasks thought to be out of reach of AI. These ML methods can often be compute hungry, energy intensive, and result in significant carbon emissions, a known driver of anthropogenic climate change. Additionally, the platforms on which ML systems run are associated with environmental impacts including and beyond carbon emissions. The solution lionized by both industry and the ML community to improve the environmental sustainability of ML is to increase the efficiency with which ML systems operate in terms of both compute and energy consumption. In this perspective, we argue that efficiency alone is not enough to make ML as a technology environmentally sustainable. We do so by presenting three high level discrepancies between the effect of efficiency on the environmental sustainability of ML when considering the many variables which it interacts with. In doing so, we comprehensively demonstrate, at multiple levels of granularity both technical and non-technical reasons, why efficiency is not enough to fully remedy the environmental impacts of ML. Based on this, we present and argue for systems thinking as a viable path towards improving the environmental sustainability of ML holistically.Comment: 24 pages; 6 figure