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Artificial intelligence and ethical decision making in a resource-limited health care environment

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  • Full or part time
    Prof E Harrison
    Dr S Cunningham-burley
    Prof S Wigmore
  • Application Deadline
    No more applications being accepted
  • Funded PhD Project (Students Worldwide)
    Funded PhD Project (Students Worldwide)

Project Description

In any healthcare system, decisions around the treatments offered to patients must balance costs against benefits. The allocation of treatments must be transparent and have a strong ethical basis, balancing the needs of individuals against those of wider society. Recently, artificial intelligence (AI) algorithms have been introduced to guide treatment decisions. These promise great benefits, while posing profound risks.

The overall aim of this PhD is to examine the role of AI in healthcare resource allocation and to produce an ethical framework, developed from empirical work, which can be broadly applied.

Complex algorithms are already used in the allocation of organs for liver transplantation. This will be a primary motivation and case study, before extending to other applications.

While the selected student will be supervised within the School, they will also take part in collaborative cohort activities as one of five Ph.D. students in the Edinburgh Futures Institute’s Baillie Gifford programme in the Ethics of Data and Artificial Intelligence. Headed by Shannon Vallor, the first Baillie Gifford Chair in the Ethics of Data and Artificial Intelligence (EFI), the aim of this programme is to cultivate multi-disciplinary skills and knowledge in the application of ethical values to data-driven technologies. More broadly, the goal is to develop the shared vocabulary and methodologies needed to support new models of education and research into the complex challenges and opportunities that data and AI present.

1. Fairness: Can bias and discrimination be detected and controlled in AI systems used to allocate healthcare resource?
2. Transparency: Can these AI systems avoid being a “blackbox” and be fully explainable to ‘lay’ and professional audiences?
3. Regulation: What ethical and practical considerations exist for approving and regulating AI systems and how can the public be involved?

This project explores ideas of fundamental importance to the development of AI. The supervisors offer deep domain knowledge including public involvement in developing governance models and ethical frameworks. This PhD will shape thinking and policy around the ethics of technology-led healthcare resource allocation.

• Prof Ewen M Harrison, Centre for Medical Informatics, The University of Edinburgh.
• Prof Sarah Cunningham-Burley, Centre for Biomedicine, Self and Society, The University of Edinburgh.
• Prof Stephen Wigmore, Clinical Surgery, The University of Edinburgh.

• A good first degree (at least 2:1), and a Masters or equivalent experience in a subject area cognate to the project.
• Demonstrate an interest in, and knowledge of contemporary higher education contexts, data privacy and ethics, and relevant data policies
• Prior study or experience related to data science, digital methods and/or innovative methods is desirable
• Demonstrate a strong interest in multidisciplinary research, teaching, and collaboration with partners within and beyond academia
• Demonstrate an ability to work with people in different roles and organisations.
• Demonstrate an ability to manage self and workload within competing deadlines.
• Ability to communicate effectively orally, in writing and through social media for various audiences (e.g. academic publications, practitioners and policy-makers, users of services).

Following interview, the selected candidate will need to apply and be accepted for a place on the Usher Institute Medical Informatics PhD programme. Details about the PhD programme can be found here:

Application procedure
Please provide a CV, a personal statement detailing your research interests and reasons for applying, degree certificate(s), marks for your degree(s) and 2 written academic reference. All documents should be in electronic format and sent via e-mail to:
[Email Address Removed]

The closing date for applications is: 15 May 2020

Interviews will be held at the end of May/Beginning of June

Funding Notes

• Tuition Fee and 4 years stipend at UKRI rates (estimated to be in the region of £15,245 for 2020/21)
• Annual research support budget of £2,000

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