A  Statutory Revision of the Information Quality Act: A Bedrock Requirement for an Effective Artificial Intelligence Program

Dr. Michael Stumborg, a principal scientist at the Center for Naval Analysis, has published a paper in which he concludes:

Congress should make the data quality provisions of the Information Quality Act applicable to all federal government data, not just publicly disseminated data. The Office of Management and Budget guidelines should provide clear, binding, and quantifiable definitions of “utility,” “objectivity,” and “integrity.” Compliance then becomes measureable, and thus, enforceable.

Congress should also define the terms “influential scientific information,” and “affected parties” to make congressional intentions clear, thereby preventing circumvention of the law by discretionary interpretation.

Congress must recognize the clear differences between data held across the many different departments and agencies of the federal government. It should direct the Office of Management and Budget’s Office of Information and Regulatory Affairs to allow data quality definitions unique to each department and agency, but require that these “local” definitions also be clear, binding, and quantifiable to the maximum extent possible.

Congress should direct the Government Accountability Office to research data quality and information sharing law and policy enforcement mechanisms. Its report should identify enforcement provisions, mechanisms, tools, and resources, or the lack thereof. It should identify best practices for enforcement of existing data quality and information sharing laws and policies, if any.

Congress should act on the resulting report to make all policies and laws enforceable.

The Information Quality Act, aka The Data Quality Act, has been in existence for nearly two decades and the Office of Information and Regulatory Affairs (OIRA) has shown excellent leadership on this matter in that it (1) implemented the Act on a government-wide basis and (2) recently issued additional guidance to further the implementation of the Act.

Unfortunately, OIRA’s diminished staff level makes it virtually impossible for it to assume a leadership role in incorporating the Act into the development of a successful AI (Artificial Intelligence) program. What is needed is for one or more organizations with broad crosscutting responsibilities to assume the role of a catalyst to get the program moving prior to the enactment of legislation, including organizations such as the Administrative Conference of the US, the National Science Foundation and the White House Office of Science and Technology Policy.

Background: Information Quality Act aka Data Quality Act

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