1,721,073 research outputs found
Ethics: A Checklist for Investigators, Ethics Boards and Reviewers
No full textThe BigMedilytics (BML) project involved a series of exploratory studies aimed at understanding how advanced, Artificial Intelligence (AI)- enabled and Big Data, technologies might be introduced into different healthcare scenarios, and whether such inclusion would be acceptable to patients and clinicians and institutions. This in the first place because of the target cohort – namely patients who are intrinsically vulnerable – and the sensitivity of their personal data. Therefore, these studies require appropriate oversight from a regulatory as well as ethical perspective. Against the backdrop of what has already been written on Ethics, Big Data and AI, BML offers a unique opportunity to explore stakeholder attitudes to the ethical treatment of their data and the effects advanced technologies might have on what they expect from healthcare usage thereof. This chapter reports the findings of several surveys, including the BML partners, which provide insight into stakeholder attitudes and concerns regarding the use of advanced technologies. Homing in specifically on the ethical principles of justice and respect for the individual, the chapter considers three ethical theories as they relate to assessing the benefit of research using advanced technologies, followed by a review of the different types of informed consent. This leads to a set of proposed review questions to guide researcher, ethics committees and institutions when evaluating research proposals involving advanced technologies in healthcare
Technology Acceptance in Healthcare
No full textTechnology acceptance has traditionally been predicted on the basis of perceived ease-of-use and perceived usefulness: namely, characteristics of the technology. This may not be the case, though, for clinical interventions or healthcare apps. In this chapter, I report the findings of two empirical surveys to the general public and to members of the BigMedylitics (BML) consortium to establish what is important in healthcare apps specifically and in the integration of advanced, Artificial-Intelligence (AI) enabled technology. Whilst stakeholders like the BML consortium recognised that advanced technologies must be understood by all stakeholders and within a complex cultural and socio-technical ecosystem, the general public reported a willingness to engage with technology. The most influential factors affecting the acceptance of healthcare technologies include self-efficacy, disruptiveness, usability and trust. The results of the two surveys together suggest that users (patients) are sophisticated in how they use technology. They are therefore capable of having conversations about how advanced technologies should be developed and deployed along with other stakeholders in the complex ecosystem of healthcare
A Second Life: an Interpretative Phenomenological Analysis of Online Transgender Identity Formation
No full textSocial identity theory provides a robust account of group processes applicable across multiple contexts. Based on self-categorisation with typical members, group affiliation can offer protective influences. However, for those such as transgender individuals who feel marginalised and subject to prejudice and misunderstanding, finding identification with suitable group members who may not be directly accessible is problematic. In a digital world, technology offers opportunities to interact with similar others and gain support. Using Interpretative Phenomenological Analysis, this study seeks to understand the lived experience of being transgender and the potential of technology. Results suggest that initial confusion can be resolved online while seeking information and support from remote others, rather than retreating into defensive tribalism. More significantly, with authenticity comes a willingness to engage prosocially offline. Despite limitations, this critical interpretation of experience offers an extended view of social identity theory: cyber-technical systems allow the search for identification to extend spatially as well as temporally
Trust, but verify: informed consent, AI technologies, and public health emergencies
No full textTo use technology or engage with research or medical treatment typically requires user consent: agreeing to terms of use with technology or services, or providing informed consent for research participation, for clinical trials and medical intervention, or as one legal basis for processing personal data. Introducing AI technologies, where explainability and trustworthiness are focus items for both government guidelines and responsible technologists, imposes additional challenges. Understanding enough of the technology to be able to make an informed decision, or consent, is essential but involves an acceptance of uncertain outcomes. Further, the contribution of AIenabled technologies not least during the COVID-19 pandemic raises ethical concerns about the governance associated with their development and deployment. Using three typical scenarios— contact tracing, big data analytics and research during public emergencies—this paper explores a trustbased alternative to consent. Unlike existing consent-based mechanisms, this approach sees consent as a typical behavioural response to perceived contextual characteristics. Decisions to engage derive from the assumption that all relevant stakeholders including research participants will negotiate on an ongoing basis. Accepting dynamic negotiation between the main stakeholders as proposed here introduces a specifically socio–psychological perspective into the debate about human responses to artificial intelligence. This trust-based consent process leads to a set of recommendations for the ethical use of advanced technologies as well as for the ethical review of applied research projects.</p
Roadmap for human-machine networks for Citizen Participation
No full textThis white paper presents a roadmap for human-machine networks for Citizen Participation. Based on a quantitative survey of 20 self-selecting stakeholders, key issues across stakeholders were identified along with potential conflicts between them. The challenges of developing and maintaining trust along with keeping motivation going are discussed. These are addressed in the first instance with manipulation of dimensions derived from the HUMANE typology to suggest ways in which conflict between stakeholders might be addressed. Finally, returning to the main concerns of trust and motivation, a non-linear timeline is proposed based on activities affecting HMNs and how such events might affect trust
HUMANE external case study: eVACUATE #2
No full textThis case study was conducted in September to October 2016 with the purpose of providing an external validation of the HUMANE typology and method. This eVACUATE case-study comprises four different engagements in order to ensure a comprehensive evaluation: a quantitative online survey on the HUMANE design patterns; a quantitative survey on the HUMANE typology used for characterising Human-Machine Networks (HMNs); and two focus groups evaluating the HUMANE method (covering the profiling process, network diagramming, implication analysis, and design pattern approach). A summary of results, along with focus group transcripts, surveys and survey results are included here.</span
HUMANE internal case study: eVACUATE #1
No full textThis case study was conducted on 14 December 2015. The purpose was to evaluate the usefulness of the HUMANE approach as perceived by relevant developers (software engineers), and additionally ask if the HUMANE typology facilitates cross-disciplinary understanding. The files included here provide a summary of the analysis and the transcript from a semi-structured focus group.</span
Privacy 501 dataset in support of the publication 'Person-centred data sharing: Empirical studies in private individuals’ attitudes'
No full textAnonymous dataset capturing 501 UK citizen (crowd-sourced via Prolific.co) attitudes to data sharing and privacy. The survey was generated following a UKRI project (DARE UK PRiAM); </span
Digital agenda for Europe annual progress report 2011
No full textThe Digital Agenda for Europe 20201, a European instrument to cover investment and research focus for the period 2010 to 2020, provides for specific effort to be invested in areas of ICT to enable and sustain European growth. The 2011 progress report2 has just been published, highlighting progress to date as well as setting on the next steps to be taken in the period 2012 and 2013 (the next 12 to 24 months). The SESERV deliverable D3.1: First Report on Social Future Internet Coordination Activities3 looked at the Digital Agenda in the context of societal challenges and trends, and how they may affect the Future Internet (FI). In addition, the SESERV Oxford Workshop6 in June 2011 and the SESERV Athens Workshop4 in January 2012, with participants from technology providers, social scientists, including economists, as well as policy makers, highlighted concerns and issues of various stakeholders in the light of how technology is developing. In this short report, we draw on the: 1 http://ec.europa.eu/information_society/digital-agenda/index_en.htm and associated documents. 2http://ec.europa.eu/information_society/newsroom/cf/itemdetail.cfm?item_id=7699&utm_campaign=isp&utm_medium=rss&utm_source=newsroom&utm_content=tpa-53 Available from http://www.seserv.org/publications/deliverables4 http://www.seserv.org/fise-conversation/Outcome-of-the-SESERV-workshop-on-the-interplay-of-economics-and-technolog
Dataset in support of the publication 'Person-centred data sharing: empirical studies in private individuals’ attitudes'
No full textAnonymous online survey, externally crowd-sourced, involving 800 respondents (in two tranches of 500 and 300) who were asked to identify and match cybersecurity threats and mitigations, and to respond to assertions from Protection Motivation Theory.
Article to be published in ORE (Open Research Europe)</span
- …
