PhD Studentship - Investigating GenAI as a Tool to Support Complex and Long-term Decision-making

Project summary: This project will investigate generative AI as a tool to support decision-making in the context of complex and uncertain combinations of future events. Specifically, the project will investigate decisions relating to technology selection -- providing analytical evidence to engineering managers regarding comparative performance and costs of technology options under future scenarios.

Deadline: 3^rd April 2024

Duration: 36 months

Funding details: Fully-funded scholarship for 3 years covers all university tuition fees (at UK level) and an annual tax-free stipend. International students are also eligible to apply, but they will need to find other funding sources to cover the difference between the home and international tuition fees. Exceptional international candidates may be provided funding for this difference.

Number of places: 1

There will be a shortlisting and interview process.

Eligibility: The PhD project requires a highly numerate graduate with interests in statistical modelling and data analytics. Candidates should have at least a First Class Honours degree or equivalent (e.g., a B.Sc. degree with 3.4 GPA in a 4.0 system), and/or preferably a Master’s degree in a quantitative discipline such as statistics, data science, analytics, operations research, industrial engineering, mathematics, or computer science (amongst others). Experience and fundamental knowledge in statistical data analysis and interpretation, including AI and generative AI, are not essential but highly desirable (there will be training opportunities throughout PhD).

Study modes eligibility: Full-time

Project Details: Generative AI (GenAI) and its potentially negative impacts receive much publicity. In simple terms, GenAI predicts a complex sequence/combination of data rather than a single data measure - the typical output with standard AI and statistical analysis methods. A commonly discussed example of GenAI is ChatGPT, which generates sentences of text as output to a user query. Combining individual words into a coherent sentence is no small task, and combining these sentences into a coherent sequence of text that provides a narrative on a particular topic requires sophisticated modelling with complex interactions.

From an operational decision-making perspective, the effectiveness of a decision is measured against a (perhaps multi-pronged) sequence/combination of events/outcomes that unfold, and there is typically uncertainty as to which particular events will unfold. The extent to which this uncertainty is understood has a substantial impact on the effectiveness of the decision, and analytics has a key role in characterising this uncertainty.

A key constraint in analytical modelling is the information that is available for use. GenAI can generate complex sequences of data, potentially facilitating more data-hungry analytical approaches. But is it worth it - is operational decision-making actually improved?

This project will investigate the application of GenAI as a tool to support decision-making in the context of complex and uncertain combinations of future events, specifically to support decisions on technology selection for an organisation.

Primary Supervisor: Dr Euan Barlow.

Additional Supervisor/s: Professor Lesley Walls.

Further information: This project is part-funded through an ongoing project with an industrial partner.

Contact Details: euan.barlow@strath.ac.uk

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