We have submitted evidence to two government consultations, making the case for stronger safeguards around artificial intelligence and defending open access to public sector data.
AI regulation
In our response to the government's call for evidence on data regulation in the age of AI, we argued that effective data regulation must go beyond how data is collected and shared to consider whether AI systems are producing reliable, fair and accountable outcomes. Our response highlighted the importance of data quality, transparency and ongoing monitoring, warning that poor-quality or unrepresentative data can lead to harmful decisions when used in AI systems.
Our response also stressed:
Finally, we made the argument that public trust in AI will depend not only on legal compliance but also on confidence that systems are accurate, understandable and subject to meaningful human oversight.
Protecting open access to public sector data
In a separate consultation on charging for the re-use of public sector data, we argued that public sector data should remain open and accessible wherever possible. While recognising the need for investment in data infrastructure and data services, we remain unconvinced that expanding charging powers is the right solution.
Our response warned that wider charging powers could create barriers for researchers, charities, smaller organisations and civil society groups, potentially reducing innovation and limiting the public value generated through data reuse. We believe that many of the challenges facing data sharing stem from funding structures, organisational incentives and cultural barriers rather than a lack of charging powers.
These latest submissions reflect our ongoing commitment to championing statistics and data for the public good.
Read our evidence on data regulation in the age of AI and marginal cost restriction on public sector data reuse online.