Don't miss our weekly PhD newsletter | Sign up now Don't miss our weekly PhD newsletter | Sign up now

  Artificial Intelligence as Source of Police Intelligence and Evidence (Advert Reference: RDF21/BL/LAW/OSWALD)


   Faculty of Business and Law

This project is no longer listed on FindAPhD.com and may not be available.

Click here to search FindAPhD.com for PhD studentship opportunities
  Dr Marion Oswald, Dr Kyriakos Kotsoglou, Prof C McCartney  No more applications being accepted  Funded PhD Project (UK Students Only)

About the Project

Project Rationale and Description

This project will examine the growth and development of artificial intelligence and machine learning within law enforcement from a socio-legal perspective, complementing a growing body of research within the field of AI in criminal justice. The use of a variety of artificial intelligence and machine learning tools within many aspects of law enforcement is increasing. Live facial recognition has been deployed in policing trials and has been considered by the courts of England and Wales in what is thought to be the first case of its kind in the world. Police forces are deploying location-based predictive methods as well as individualised predictive tools, designed to assist in their risk assessment and public protection duties. Data captured by commercially produced tools incorporating elements of machine learning may increasingly be considered in an evidential way, raising questions around validity and access to commercially confidential information. These developments raise a host of legal, ethical and social questions, combined with questions around scientific and statistical validity and reliability. Debates around  ethics and privacy, although important, do not capture key concerns around the use of outputs  from AI in specific contexts as police intelligence or as evidence, contexts which raise very particular legal, technical quality, management and governance issues. This project should critically scrutinise the current AI developments within law enforcement with reference to police intelligence and evidential uses. It will be multi- and inter-disciplinary, calling upon law, ethics, science and criminology.

Eligibility and How to Apply:

Please note eligibility requirement:

  • Academic excellence of the proposed student i.e. 2:1 (or equivalent GPA from non-UK universities [preference for 1st class honours]); or a Masters (preference for Merit or above); or APEL evidence of substantial practitioner achievement.
  • Appropriate IELTS score, if required.
  • Applicants cannot apply for this funding if currently engaged in Doctoral study at Northumbria or elsewhere.

For further details of how to apply, entry requirements and the application form, see

https://www.northumbria.ac.uk/research/postgraduate-research-degrees/how-to-apply/ 

Please note: Applications that do not include a research proposal of approximately 1,000 words (not a copy of the advert), or that do not include the advert reference (e.g. RDF21/BL/LAW/OSWALD) will not be considered.

Deadline for applications: 29 January 2021

Start Date: 1 October 2021

Northumbria University takes pride in, and values, the quality and diversity of our staff. We welcome applications from all members of the community.

For informal enquiries, please contact Marion Oswald ([Email Address Removed])

Computer Science (8) Law (22) Philosophy (28) Sociology (32)

Funding Notes

The studentship is available to Home students and includes a full stipend, paid for three years at RCUK rates (for 2020/21, this is £15,285 pa) and full tuition fees.
Please note: to be classed as a Home student, candidates must meet the following criteria:
• Be a UK National (meeting residency requirements), or
• have settled status, or
• have pre-settled status (meeting residency requirements), or
• have indefinite leave to remain or enter.
If a candidate does not meet the criteria above, they would be classed as an International student.

Where will I study?

Search Suggestions
Search suggestions

Based on your current searches we recommend the following search filters.