SR Rafi
7 months ago
Ensuring Well-Being in the Age of Generative AI Edinburgh Napier University in United Kingdom
Degree Level
PhD
Field of study
Computer Science
Funding
Full funding availableDeadline
December 31, 2026Country
United Kingdom
University
Edinburgh Napier University

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About this position
This PhD project at Edinburgh Napier University, within the School of Computing, Engineering & the Built Environment, investigates the impact of generative AI on human well-being across diverse professional sectors. While generative AI offers significant productivity gains, it also introduces new challenges such as increased performance expectations, reduced autonomy, and career uncertainty, particularly in AI-augmented environments. The project highlights sector-specific concerns: in education, generative tools may erode teachers’ professional judgment and empathy; in IT, coding assistants can diminish creative ownership and intensify deadline pressure; and in healthcare, AI diagnostics may undermine clinicians’ trust in their expertise and accountability. Additionally, the reuse of open-source content by large language models (LLMs) raises ethical and emotional issues related to authorship and the value of creative work.
Organisationally, the rapid adoption of generative AI by large companies like Amazon sets aggressive industry benchmarks, while smaller organisations often lack the resources and governance structures to implement AI responsibly, potentially widening capability gaps and amplifying workplace stress and inequity. The proposed research aims to develop a human-centred, evidence-informed framework to identify and mitigate well-being risks associated with generative AI adoption. Key objectives include mapping risk pathways, conceptualising well-being indicators, and articulating governance patterns that balance innovation with dignity, autonomy, and fairness.
The project moves beyond technical and efficiency-driven narratives to establish well-being assurance as a core principle in the future of AI-enabled work and society. Applicants should have a first degree (minimum 2:1) in Computer Science, experience in software engineering, programming skills, knowledge of machine learning, and strong communication abilities.
Knowledge of statistics is desirable. English proficiency (IELTS 6.5 overall, minimum 6.0 in each component) is required. The studentship covers full UK or international tuition fees and provides a standard living allowance at the RCUK rate (£21,383 per annum), but international applicants must cover visa and NHS surcharge costs. The application process requires a completed form, CV, two academic references, a two-page research outline, a one-page motivation statement, and evidence of English proficiency.
The project code 'SCEBE1125' and the advertised title must be used. The studentship starts in October 2026, with a deadline of January 9, 2026. For informal enquiries, contact Dr SR Rafi at [email protected].
Funding details
Full funding including tuition fees and living expenses is available for this position. The scholarship covers all educational costs and provides a monthly stipend.
How to apply
Please submit your application including a cover letter, CV, academic transcripts, and contact information for two references. Applications should be sent via the online portal before the deadline.
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