In January, the Department of Defense ordered the Special Inspector General for Afghanistan Reconstruction (SIGAR) not to publish certain data on areas of Afghanistan that were held by insurgents.
“This development is troubling for a number of reasons, not least of which is that this is the first time SIGAR has been specifically instructed not to release information marked ‘unclassified’ to the American taxpayer,” the SIGAR said in its January 2018 report to Congress.
But the Department of Defense soon reversed course, saying it was an error to withhold that information.
Last week, the SIGAR published an addendum to its January report that provided the previously suppressed data. In addition, a detailed control map and the underlying data for each of Afghanistan’s 407 districts were declassified and published. See Addendum to SIGAR’s January 2018 Quarterly Report to the United States Congress, February 26, 2018.
The basic thrust of the new data is that Afghan government control of the country is at its lowest reported level since December 2015, while insurgency control is at its highest.
“The percentage of districts under insurgent control or influence has doubled since 2015,” the SIGAR addendum said.
The current lack of public trust in AI risks inhibiting innovation and adoption of AI systems, meaning new methods will not be discovered and new benefits won’t be felt. A failure to uphold high standards in the technology we deploy will also place our nation at a strategic disadvantage compared to our competitors.
Using the NIST as an example, the Radiation Physics Building (still without the funding to complete its renovation) is crucial to national security and the medical community. If it were to go down (or away), every medical device in the United States that uses radiation would be decertified within 6 months, creating a significant single point of failure that cannot be quickly mitigated.
The federal government can support more proactive, efficient, and cost-effective resiliency planning by certifying predictive models to validate and publicly indicate their quality.
We need a new agency that specializes in uncovering funding opportunities that were overlooked elsewhere. Judging from the history of scientific breakthroughs, the benefits could be quite substantial.