Children in the Behavioural Machine
Digital Dignity Institute
Abstract
Discover a new research report examining children’s lives within AI-mediated behavioural systems. Children now grow up inside systems built to predict and influence them. This paper brings child-centred protection into the AI realms where it is needed most: thirty case studies, one singular gap, seven findings and eight recommendations for governance that starts with the child.
Read the full research paper
Download the full research paperKey Findings
- 01
Algorithmic management systems consistently reduce worker autonomy and increase stress, with effects concentrated among lower-wage workers.
- 02
Continuous monitoring is associated with elevated anxiety and reduced sense of professional identity across occupational categories.
- 03
Workers subject to automated decisions routinely lack meaningful access to human review or contestation mechanisms.
- 04
Algorithmic management systems frequently perpetuate and amplify existing patterns of workplace discrimination.
- 05
Minimum dignity standards — transparency, contestability, proportionality, non-discrimination — provide a workable regulatory framework.
Methodology
Systematic review of empirical literature (n=147 studies); original qualitative research with workers in algorithmically managed workplaces (n=84 interviews across six industries); comparative regulatory analysis; expert consultation with labour law scholars, workplace psychologists, and trade union representatives.