Optimising collective intelligence


Contact Dr Richard P Mann to discuss this project further informally.

Project description

Collective intelligence can be seen all around us, from insect colonies building a nest to the collective endeavours of scientists to understand the world. However, we also see many instances of collective failure, with increasingly polarised societies and examples of mass hysteria. Harnessing collective intelligence is vitally important in an increasingly connected world where communications.

How can we build intelligent systems and societies that bring together diverse expertise effectively, and avoid the problems of groupthink and polarisation?

This project will investigate how individuals, with differing types and levels of expertise can combine their knowledge most effectively when faced with uncertainty about the world, and what incentives can be used to motivate optimal collective behaviour. This interdisciplinary project will combine ideas from mathematical modelling, statistics and machine learning/AI.

Entry requirements

Applications are invited from candidates with or expecting a minimum of a UK upper second class honours degree (2:1), and/or a Master's degree in mathematics or relevant subject.

If English is not your first language, you must provide evidence that you meet the University's minimum English Language requirements.

How to apply

Formal applications for research degree study should be made online through the university's website. Please state clearly in the research information section that the PhD you wish to be considered for is 'Optimising collective intelligence' as well as Dr Richard P Mann as your proposed supervisor.

We welcome scholarship applications from all suitably-qualified candidates, but UK black and minority ethnic (BME) researchers are currently under-represented in our Postgraduate Research community, and we would therefore particularly encourage applications from UK BME candidates. All scholarships will be awarded on the basis of merit.

If you require any further information please contact the Graduate School Office, e: maps.pgr.admissions@leeds.ac.uk