Initial estimates of the number of jobs to be replaced by AI related technologies have been heavily revised downwards in recent studies and it is becoming increasingly clear that in many sectors the nature of professional roles are starting to be reconsidered and redesigned in response to the opportunities and limitations of new technologies. This raises questions regarding our understanding of the future of professions, which activities will be valued, what skills and training will be required, what will career progression entail, and how may technology be designed to augment rather than replace people.
This project will begin by examining understandings of the types of tasks and activities which new technologies (including machine learning, AI and data analytics) are able to automate now, and into the foreseeable future. While initially considered to be labour-replacing, technological productivity benefits are increasingly understood to arise from the significant re-design of work in order that technology augments people. Taking a case-study based approach to a small number of professions, it will examine how new technologies have begun to alter the number of practitioners, entry criteria, the content and accreditation of roles, the services provided and billed to clients, practitioner remuneration, and associated training and progression. It will examine the extent to which change to date has been technologically and managerially led versus practitioner led, and the opportunities for practitioners to shape the implementation of technology and the future design of their professions. It will also consider notions of the changing value of different types of work and perspectives on job quality.
We envisage an interpretive methodological approach, involving review of primary and secondary source information and interviews with a range of stakeholders including key technology providers, professional accreditation bodies, trade bodies and journals, employer and employee representatives, major sectoral organisations, and the association of graduate careers advisory services. It will likely focus upon one country, e.g. UK, but may draw comparisons with changes to professions in other countries or supranational regions.
A successful applicant is expected to have a very good undergraduate degree: a minimum of a 2:1, and preferably a first class honours. They should also hold, or expect to achieve, a very good Master’s degree (at least a merit and preferably at distinction level) in a Business or relevant subject. Their references will attest to qualities of academic achievement and research potential that make the candidate stand out above their peers. They may have already won academic prizes within their home institutions and /or internationally. The project will be supervised by Dr. Malika Hamadi and Dr. Ziwen Bu.
Applications will be assessed on (a) the quality of the student’s academic achievements and preparedness for doctoral level study; (b) the quality of the research proposal; (c) the potential to contribute to cutting edge research; and (d) the match of the proposal to areas of research strength within Birmingham Business School. Since we are particularly keen to build on existing areas of research strength, all applicants are strongly advised to contact potential supervisors and to discuss their proposal with them prior to online submission.
How to apply
Potential candidates for the Birmingham Business School Doctoral Scholarship must have an offer of a place to study for a PhD. If you do not already have an offer, you must apply by 30 April 2021 and mark your electronic application Birmingham Business School Scholarships. At the same time, you should send a separate Birmingham Business School Scholarship application form
form
, which can be downloaded along with your research proposal, to Dr Danny McGowan, Director of the Doctoral Programme ([Email Address Removed]) and mark your email ‘Birmingham Business School Scholarships’.
For further information on the application process, please contact the Business School: [Email Address Removed].