Attitudes to data uses in different public sectors
On Living With Data, we focused on public sector data uses in welfare, media and health in our research, because these are important aspects of everyday life which are increasingly ‘datafied’. This page links to reports we have produced on attitudes to data uses in each of these three sectors. Links to the reports and a summary of main findings can be found below.
- Participants were concerned about the possibility of welfare data uses reinforcing inequalities, compared to the other public sector data uses we discussed with them. Data-driven discrimination was particularly concerning in this context because people who are disadvantaged by structural inequalities often depend on welfare services.
- Participants were concerned that welfare might have negative consequences for people from disadvantaged and minority groups who find it hard to use or engage with.
- Belonging to a disadvantaged or minority group influenced perceptions of welfare data uses.
- There was concern and confusion about third party involvement in Confirm Your Identity.
- People support uses of health data for the social good, and trust health sector data uses above those in other sectors.
- However, they are concerned about the involvement of commercial companies in the provision of health data services or infrastructures.
- There were concerns about potential future sharing of data.
- Trust and concern vary across groups. Older participants were most trusting of health sector data uses. LGBTQ+ participants were less trusting than heterosexual cisgendered participants because of historical misuses of data about sexuality and sexual health.
“You can’t get the genie back in the bottle.”Lewis, talking about health data sharing
- Most participants felt that engaging with public service media data systems was a choice: people could opt to use these systems, or not. For this reason, they felt these data uses were fair.
- Some participants were concerned about unequal access to public service media data-driven technologies, whereas others felt that it could help to overcome inequalities.
- Some participants were concerned that data from these systems could be used in unintended ways. Others were concerned errors resulting from algorithmic processing.