PhD Study : Causality and Counterfactuals in Explainable AI

Summary

The development of explainable AI (XAI) represents one of the main challenges within AI and ML. While deep learning (DL) techniques have achieved great predictive success in many applications, their lack of interpretability and the related difficulty of explaining their decisions can be a significant limitation. This can result in concerns about trustworthiness, fairness and accessibility [1].

Another limitation is that while ML identifies associations in data, most methods do not model causal relationships. However, associations are inadequate for reasoning about the effects of interventions (“If I take this medication, will I recover?”) and answering questions about counterfactual situations (“If I had not taken this medication, would I have recovered?”) [2].

Furthermore, these issues are closely linked since causality and counterfactuals are often considered to be indispensable components of explanation. As a result, there is a growing awareness of the need to incorporate causality into XAI [3]. While counterfactuals are often taken into account, standard techniques such as those used in model-agnostic approaches to XAI are not based on causality and can result in spurious correlations [4].

The goal of this project is to develop new algorithms for incorporating causality into XAI. This will involve exploring fundamental questions about causality and XAI including the role of abductive inference [5] and quantifying explanatory goodness [6]. The project is expected to make use of probabilistic graphical models and could proceed in one of several directions depending on the early stages of the research and the successful candidate’s interests and expertise. These include: causal approaches to model-agnostic explanations, causal models as an alternative to DL [7,8], or causal models that incorporate DL [9].

It is expected that the work will be applied to medical diagnosis given the importance of causality and explainability in that domain, though other options will also be considered.

Essential criteria

Applicants should hold, or expect to obtain, a First or Upper Second Class Honours Degree in a subject relevant to the proposed area of study.

We may also consider applications from those who hold equivalent qualifications, for example, a Lower Second Class Honours Degree plus a Master’s Degree with Distinction.

In exceptional circumstances, the University may consider a portfolio of evidence from applicants who have appropriate professional experience which is equivalent to the learning outcomes of an Honours degree in lieu of academic qualifications.

Desirable Criteria

If the University receives a large number of applicants for the project, the following desirable criteria may be applied to shortlist applicants for interview.

• First Class Honours (1st) Degree
• For VCRS Awards, Masters at 75%
• Completion of Masters at a level equivalent to commendation or distinction at Ulster
• Experience using research methods or other approaches relevant to the subject domain
• Sound understanding of subject area as evidenced by a comprehensive research proposal
• Publications - peer-reviewed

Equal Opportunities

The University is an equal opportunities employer and welcomes applicants from all sections of the community, particularly from those with disabilities.

Appointment will be made on merit.

Funding and eligibility

The University offers the following levels of support:

Vice Chancellors Research Studentship (VCRS)

The following scholarship options are available to applicants worldwide:

• Full Award: (full-time tuition fees + £19,000 (tbc))
• Part Award: (full-time tuition fees + £9,500)
• Fees Only Award: (full-time tuition fees)

These scholarships will cover full-time PhD tuition fees for three years (subject to satisfactory academic performance) and will provide a £900 per annum research training support grant (RTSG) to help support the PhD researcher.

Applicants who already hold a doctoral degree or who have been registered on a programme of research leading to the award of a doctoral degree on a full-time basis for more than one year (or part-time equivalent) are NOT eligible to apply for an award.

Please note: you will automatically be entered into the competition for the Full Award, unless you state otherwise in your application.

Department for the Economy (DFE)

The scholarship will cover tuition fees at the Home rate and a maintenance allowance of £19,237 (tbc) per annum for three years (subject to satisfactory academic performance).

This scholarship also comes with £900 per annum for three years as a research training support grant (RTSG) allocation to help support the PhD researcher.

• Candidates with pre-settled or settled status under the EU Settlement Scheme, who also satisfy a three year residency requirement in the UK prior to the start of the course for which a Studentship is held MAY receive a Studentship covering fees and maintenance.
• Republic of Ireland (ROI) nationals who satisfy three years’ residency in the UK prior to the start of the course MAY receive a Studentship covering fees and maintenance (ROI nationals don’t need to have pre-settled or settled status under the EU Settlement Scheme to qualify).
• Other non-ROI EU applicants are ‘International’ are not eligible for this source of funding.
• Applicants who already hold a doctoral degree or who have been registered on a programme of research leading to the award of a doctoral degree on a full-time basis for more than one year (or part-time equivalent) are NOT eligible to apply for an award.

Due consideration should be given to financing your studies. Further information on cost of living