This funded PhD project will focus specifically on the development of a participatory Responsible AI methodology and tools that support stakeholders to agree on the features and values against which a particular AI technology should be audited – including priorities over these and the tradeoffs that are acceptable – and then to audit the tool accordingly. The project will use techniques from computational argumentation to support collaborative participatory decisions about which features and values to prioritise in the audit, and produce a protocol that specifies the auditing process. The tools and protocol that are developed will be evaluated with different language communities of wikipedia editors, considering the use of AI writing assistants for article generation.
The successful candidate will contribute to the UKRI research project PHAWM (Participatory Harm Auditing Workbenches and Methodologies), a major project (with £3.5M of investment) involving 7 UK universities and 23 partner organisations. PHAWM will produce workbenches to enable diverse AI stakeholders to audit AI technologies, and will develop participatory audit methodologies which guide how, when and who carries out these audits. The PHAWM project will train stakeholders in carrying out participatory audits and work towards a certification framework for AI solutions. The research is grounded in four use cases: Health, Media Content, Cultural Heritage, Collaborative Content Generation.
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Summary
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Benefits
Full tuition & £22,780 Stipend
Requirements
- Applicants will normally be expected to have a First Class Honours at BSc level (or equivalent) in computer science or other discipline related to the project. However, in exceptional cases (e.g., where extenuating circumstances apply, or where the candidate has compensating relevant experience) we may consider other qualifications.
- Applicants must meet Band D of the King’s College London English Language Requirements.
- Applications from individuals with non-standard backgrounds (e.g. those from industry or returning from a career break) and from underprivileged backgrounds are encouraged, as are applications from women, candidates with disabilities, and candidates from ethnic minorities, who are currently under-represented in the sector.
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Application Deadline
August 25, 2025How To Apply
Are you qualified and interested in this opportunity? Kindly go to
King's College London on apply.kcl.ac.uk to apply
Make your application via the application portal at: King's Apply
Programme name: “UKRI CDT in Safe and Trusted Artificial Intelligence (MPhil/PhD)”
Under “Employment Details”:
- Select “Yes” to “Do you have relevant work experience you would like to add?”
- Upload a CV detailing any relevant work or academic experience.
Under “Supporting Statement”, under “Research Proposal”:
- In the “Project Title/Reference” section, enter “STAI-CDT-2025-PHAWM”.
- In the “Brief synopsis of your research proposal” section, enter “STAI-CDT-2025-PHAWM”.
- Upload a 3 – 4 page Research Proposal, with:
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- your ideas on the specific challenges you would want to address within the project,
- a brief review of the relevant state of the art, identifying any limitations or open questions, and
- your initial plan of the research you would carry out.
Under the “Funding” section of the application:
- Select: “5. I am applying for a funding award or scholarship administered by King’s College London.”
- In the “Award Scheme Code or Name” box that appears when you select the option above, enter “STAI-CDT-2025-PHAWM”.
- Optionally, you can also upload an Extenuating Circumstance Statement (up to one page).
- If you have faced significant personal or medical challenges that have impacted on your academic performance or relevant experience, you can explain these here. For example, these might include significant caring responsibilities, chronic illness or disability, experience of the care system, or coming from a deprived background. You should explain clearly your circumstances and how these have impacted you.
- The admissions panel will consider these circumstances in assessing your application. Note, you may be asked to provide evidence of your circumstances (e.g., medical evidence, evidence you grew up in an area of socio-disadvantage according to the ACORN methodology or an area with a low proportion of students participating in higher education as measured by POLAR4, evidence you were eligible for Free School Meals or have experience of the care system).
After applying via the King’s application portal, you must also complete a STAI-CDT Application Information Form.
For more details, visit King's College Scholarship webpage