PhD studentship opportunity
I am offering a PhD studentship as part of my Chancellor's Fellow programme of work: 'Artificial intelligence in practice: implementing AI and data-driven technologies in organizations.' If you know of any interested students please do pass the link below onto them – also please do circulate around your network!
Many thanks Luciana.
About the Project
The use of AI is increasingly advocated to make up for longstanding deficiencies in healthcare including serious diagnostic errors, mistakes in treatment, a significant waste of resources, inefficiencies in workflow, and inequities. And yet, the integration of human and artificial intelligence for medicine has only barely begun. This results in a considerable gap between theoretical technology claims and actual implementation and results. Filling this gap is important due to the pervasiveness of AI and the potentially beneficial or unwanted effects this may bear on people, processes and organizations.
The overall aim of this PhD is to analyse the implications of AI – and related data-driven technologies - in practice. This includes the effects on organizational processes and practices and their outcomes as well as on practitioners and the wider healthcare system.
The student will draw on their analysis to develop action-driven methodologies and frameworks which can be used by organizations adopting AI technologies as well as the designers of AI healthcare systems to advance understanding of AI and its practical applications. State-of-the-art AI technologies are already used in the management of healthcare diagnostic and prognostic decisions as well as processes of care delivery within healthcare providers and beyond. The student will gain access to state-of-the-art case studies of the introduction of AI technologies in healthcare (e.g. clinical decision support, workflow automation, etc.) at Edinburgh and beyond.
While the selected student will be supervised within the Usher Institute, Centre for Medical Informatics, they will also have opportunities to become involved in collaborative interdisciplinary cohort activities across schools and colleges at Edinburgh. These include the Futures Institute's Baillie Gifford programme in the Ethics of Data and Artificial Intelligence; the interdisciplinary EPSRC AI Centre for Doctoral Training; and the newly awarded Advanced Care Research Centre (ACRC).
The student will be able to cultivate multi-disciplinary skills and knowledge in the application of practical frameworks to data-driven technologies. More broadly, the goal is to develop the shared vocabulary and methodologies needed to support new frameworks and models for the design and use of data-driven and AI technologies in healthcare organizations.
1. How is AI changing healthcare processes and practices, such as decision-making and problem-solving (e.g. diagnostics, treatment, prognostics); how is AI reshaping healthcare delivery practices (e.g. clinical pathways and patient workflows)?
2. What are the effects of AI on healthcare processes and practices and their outcomes? How are they reconfiguring activities and roles within healthcare organizations and beyond (e.g. across the community)?
3. How can the insights derived from 1) and 2) be used to draw frameworks and models which can inform more efficient, flexible, reliable and ethical design of AI systems for healthcare?
This project explores ideas of fundamental importance to the development of AI. The supervisor offers deep domain knowledge including the formulation of theory-driven models and frameworks to improve AI design, adoption and use in healthcare organizations. This PhD will inform academic and policy debates around the implementation of AI-led healthcare processes and practices. It will also directly support technology and service providers of AI-enabled healthcare systems.
Dr Luciana D'Adderio
Chancellor's Fellow in Data Driven Innovation
Centre for Medical Informatics - Usher Institute
The University of Edinburgh
Glaser V., Pollock N. D'Adderio, L. (forthcoming). The biography of an algorithm: performing algorithmic technologies in organizations. Organization Theory.