The question of how to best regulate artificial intelligence (AI) is one lawmakers are still addressing, as they are trying to balance innovation with risk mitigation. Meanwhile, state and local governments are creating their own regulations in the absence of a comprehensive federal policy.
The new white paper, from the Data Foundation, a nonprofit supporting data-informed public policy, is intended to be a comprehensive resource. It outlines three key pieces of effective data policy: high-quality data, effective governance principles and technical capacity.
The 21-page document includes a summary of existing legal frameworks on federal data governance, a guide to AI-related data policy considerations and the AI-Ready Data Policy Tool, which acts as a rubric designed to better assess and improve policy.
As Corinna Turbes, director of the foundation’s Center for Data Policy, said in a statement, the resource “will help advance a discussion about creating a comprehensive public-policy framework for data that aligns with government objectives and the public interest.” To develop the resource, members of the Data Foundation’s Data Coalition actually joined in an AI working group.
The timing of the guide’s release comes as the federal government assesses more than 700 reported AI use cases across executive branch agencies. And while some governments are still exploring policy, it is important to note that AI is already in use by many organizations. Starting with data may make the technology work more effectively.
“Organizations are going to see they can’t just throw themselves off the cliff and do some majestic AI that everyone’s going to be impressed with,” Wisconsin Department of Natural Resources CIO Ricki Koinig said recently. “It’s going to go back to data.”
