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Institute for the Future of Work (IFOW) research has highlighted the growth in the use and adoption of ‘people analytics’ software in recruitment, hiring and algorithmic management in both traditional sectors and platform work. There is an emerging consensus around the need for AI and automated decision-making tools to be audited to promote compliance, best practice and build public trust but not about the limitations of statistical approaches, or practical solutions to overcome these.

While research has begun to consider mechanisms for citizen participation in the design and review of automated and semi-automated decision-making tools, IFOW have identified a significant gap in understanding as to how such processes can be effectively conducted in workplaces, involving workers as data subjects.

In this project, we build on the principles of meaningful human review at the level of individual decisions, to consider the involvement of data subjects in what should be regular auditing processes.

Specifically, this project aims to:

  1. Build the understanding of policy makers, industry and business leaders and workers on fairness related implications arising from the deployment of automated decision-making systems within the workplace, to enable informed dialogue during processes of auditing and human review.
  2. Develop and disseminate practical guidance and resources for firm leaders and worker representatives to advance meaningful worker involvement in processes of auditing and human review.


You can read more about the project and access the final outputs, including the Understanding AI at Work toolkit and the Good Work Algorithmic Impact Assessment, on the Institute for the Future of Work’s website: The Lab - IFOW

If you'd like more information, please contact the ICO's grants programme.