Interagency Data Sharing

Definition

Interagency Data Sharing is the systematic design and evaluation of interagency data sharing within the capacity of public institutions to procure, govern, deploy and evaluate AI in ways that deliver public value.

Why this matters

Weak interagency data sharing can lead to unsafe deployment, unlawful or unauthorised action, wasted public resources, loss of rights, poor accountability and declining institutional trust.

Research questions

Which controls, evidence and institutional arrangements make interagency data sharing effective in practice, and how do outcomes vary by sector, system risk, organisational maturity and operating context?

Hypotheses

An explicit, testable and continuously evidenced approach to interagency data sharing, with clear ownership, independent review, runtime telemetry and recovery, will outperform policy-only or periodic compliance approaches.

Proposed methods

capability maturity assessment; procurement review; service-design research; workforce study; benefit evaluation; rights-impact assessment; stakeholder interviews; document and control review; fault and incident simulation; longitudinal implementation assessment; methods adapted specifically to Interagency Data Sharing

Stakeholders and beneficiaries

citizens; public servants; executives; boards; regulators; auditors; legal and risk teams; technology teams; service users; civil society; suppliers