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Privacy-preserving telemetric data minimisation in remote work contexts

   Cardiff School of Computer Science & Informatics

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  Dr Sandy Gould  No more applications being accepted  Competition Funded PhD Project (Students Worldwide)

About the Project

“Bossware” is a kind of technology used to surveil employees while they work. It has become more prevalent during the pandemic as people moved en masse to remote work, but telemetry-based tools for collecting, storing and managing information about workers’ behaviour have been used for a long time.

There are a number of privacy and non-privacy concerns with these kinds of surveillance technologies. One is that they do not fit with the principle of data minimisation, which requires the necessary data for a purpose and no more to be collected. Collecting excessive amounts of data about worker behaviour increases the potential for harmful breaches and unnecessarily compromises workers’ privacy and autonomy for little tangible benefit.

How can we measure important aspects of work using less data? How can we map and reduce high-frequency privacy-compromising measures into more tractable and manageable measures on people’s own devices? How can we give individual workers more control over the form in which they share their data with co-workers?

Project goals

The goal of the project is to understand how data minimisation methods can be used to reduce the amount of telemetry that devices need to ‘send home’. To do this, the project will need to:

·    Develop an understanding of people attitudes toward workplace telemetry and data minimisation principles

·    Explore the application of data minimisation methods to behavioural telemetry

·    Demonstrate the practical effects of data minimisation methods on worker privacy and control.

The project could focus on different working contexts, for example new digital-first work (e.g., platform work, crowdsourcing) and/or in more traditional forms of work where digital surveillance might be less integral to work.


The project will make use of empirical methods to develop a deeper understanding of telemetry and data minimisation. Methods will adapt to the prior experience of the successful applicant, but could include:

·      Statistical analyses (e.g., to understand the contribution of different telemetry sources)

·      Telemetry-based data collection from digital devices (so that minimised data can be compared with baselines).

·      Field experiments/interventions (e.g., to test data minimisation techniques)

·      Questionnaires

·      Interviews and focus groups (e.g., to understand workers’ attitudes workplace telemetry)

The supervisors will support the successful applicant in developing research methods skills suitable for conducting high-quality mixed-methods and multidisciplinary research.

Keywords: Bossware, telemetry collection, remote work, future of work, crowdwork, data minimisation, privacy

For more information about the project, please contact Dr Sandy Gould

Academic criteria: A 2:1 Honours undergraduate degree or a master's degree, in computing or a related subject or a 2:1 Honours undergraduate degree or a master's degree in a behavioural science (e.g., psychology). Applicants with appropriate professional experience are also considered.

Applicants for whom English is not their first language must demonstrate proficiency by obtaining an IELTS score of at least 6.5 overall, with a minimum of 6.0 in each skills component.

How to apply:

Please contact the supervisors of the project prior to submitting your application to discuss and develop an individual research proposal that builds on the information provided in this advert. Once you have developed the proposal with support from the supervisors, please submit your application following the instructions provided below

Please submit your application before the application deadline 29th April 2022 via Computer Science and Informatics - Study - Cardiff University

In order to be considered candidates must submit the following information: 

  • Supporting statement 
  • CV 
  • In the ‘Research Proposal’ section of the application enter the name of the project you are applying to and upload your Individual research proposal, as mentioned above in BOLD
  • In the funding field of your application, insert “I am applying for 2022 PhD Scholarship in Computer Science and Informatics”, and specify the project title and supervisors of this project in the text box provided.
  • Qualification certificates and Transcripts
  • References x 2 
  • Proof of English language (if applicable)

Interview - If the application meets the entrance requirements, you will be invited to an interview

If you have any questions or need more information, please contact [Email Address Removed]

Funding Notes

A School-Funded PhD Scholarship is available for entry 2022/23.
In the Funding field of your application, insert "I am applying for 2022 PhD Scholarship" and specify the project title and supervisor of this project in the fields provided.


Gould et al. (2018) Influencing and Measuring Behaviour in Crowdsourced Activities. In: Filimowicz M., Tzankova V. (eds) New Directions in Third Wave Human-Computer Interaction: Volume 2 - Methodologies.
Cecchinato et al. (2021) Self-Tracking & Sousveillance at Work: Insights from Human-Computer Interaction & Social Science. In AI, Automation & Work.
Gould, SJJ (Forthcoming) Consumption experiences in the research process. In CHI Conference on Human Factors in Computing Systems

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Research output data provided by the Research Excellence Framework (REF)

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