Document Type

Article

Publication Title

George Washington Journal of Law & Technology

Volume

1

Publication Date

2025

Abstract

In the 2010s, the open government data movement—a confluence of government transparency and open source advocacy—succeeded in making most federal data disclosed by default and free of restriction on downstream use. However, keen-eyed observers noted a “new ambiguity” in open government data policies. It was not clear if the appropriate focus of these policies was government—in the sense of accountability and transparency—or data—in the sense of downstream use and reuse of government datasets by public and private actors. Even as federal government data policies moved from Executive Branch prerogative to statutory mandate, that ambiguity remained unresolved. But the rise of artificial intelligence—and its accompanying demand for new data sources—tipped the scale in favor of data.

This Article does not seek to resolve the ambiguity in the other direction or rebalance the scales. Instead, this Article articulates how open government principles have a role to play even when federal open data are viewed primarily as an asset or resource to build, train, and test artificial intelligence systems. Further, that role may require refinements in how we think about the “open” part of open government data. There are compelling reasons to condition certain reuses of federal open data on the disclosure of the use even if that would make the use of that data less “open” in some senses.

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