Why Open Data Needs Market Signals
Government agencies often focus resources on a few high-profile datasets, neglecting the broader potential of their data inventories. This approach mirrors a Monopoly strategy where limited investment yields limited returns, failing to stimulate a thriving data economy. To maximize value, agencies must shift from concentrating on isolated statistics to developing a diverse range of data assets that drive innovation and solve complex problems. Determining which datasets deserve investment requires active feedback from stakeholders, as agencies cannot predict usage patterns in isolation. While some data functions as a public good, much of it involves privacy concerns and technical barriers that require significant resources to anonymize and format. By engaging through public comment periods, reviewing open data plans, and analyzing Freedom of Information Act requests, users can signal demand and help agencies prioritize investments that balance openness with privacy protection. This participatory approach is critical for establishing trustworthy artificial intelligence, which relies on well-documented, high-quality training data. When stakeholders clearly articulate their needs and usage cases, they provide the evidence agencies need to justify publishing machine-readable data with clear provenance. This collective signaling ensures that government data efforts support not just immediate utility, but also the ethical and reliable deployment of AI systems across federal operations.
Source: forbes.comPublished on 2026-01-22