How governments handle data matters for inclusion (phys.org)
TLDR; Summary
- Researchers highlight bias in predictive policing due to inaccurate data
- Governments rely on data for services like mobility, welfare, and policing
- Algorithms and AI change how governments use data for public services
- Data handling affects equity, inclusion, and outcomes for communities
- Government data practices divided into data collection, storage, analysis, and use
- Poor-quality data worsens inequalities and can lead to oversurveillance
- Storage decisions can unintentionally restrict citizen access to services
- Analysis by external experts may reinforce inequalities
- Data use can lead to disproportionate surveillance and misuse
- Building inclusion into data practices requires ethical reflection and diverse voices