NEWS26 October 2021

Ethics guidance issued for machine learning in research

AI Data analytics News Privacy UK

UK – The UK Statistics Authority’s Centre for Applied Data Ethics has published ethics guidance focused on the use of machine learning for research and official statistics.

magnifiying glass on backgrounds shaded in grey

The Statistics Authority set up the Centre for Applied Data Ethics earlier in 2021 to help the research and statistics sectors address emerging ethical challenges.

The centre aims to work with partners in the UK and overseas to develop practical guidance and advice on the effective use of data for the public good.

As part of the guidance, the Statistics Authority has developed six ethical principles for researchers to consider during projects, focused on: ensuring the public good of research and statistics; maintaining data confidentiality; understanding the potential risks and limitations in new research methods and technologies; compliance with legal requirements; considering public acceptability of the project; and transparency in the collection, use and sharing of data.

The guidance also includes a checklist for ethical considerations, with questions for practitioners to consider, including:

  • Have the benefits of using machine learning for a project been clearly documented?
  • Is machine learning the most suitable method to use?
  • Has transparency in the collection, use, retention and sharing of data been considered?

Tom Smith, managing director at the Data Science Campus and member of the Centre for Applied Data Ethics, said: “The guidance provides an overview of key ethical issues for analysts to consider and a foundation from which to apply these concepts to current projects.

“This is particularly useful in scenarios where analysts, data scientists and statisticians are developing experimental approaches and analysing data sources that are more novel or innovative in their application and use; in these cases, additional ethical issues may emerge that have not been encountered or considered before.”