The population of Syria is 17,951,639, according to the CIA World Factbook.
That figure (oddly identified as a “July 2014” estimate) is wrong, according to everyone else.
The discrepancy was noted yesterday in the intelligence newsletter Nightwatch.
“NightWatch consulted six separate sources for the total population of Syria. They agreed that it is between 22 and 23 million people, not 17.9 million as indicated in the CIA World Factbook. There are about 7 million Syrians under voting age of 18 and more than 15 million registered voters,” the newsletter said.
“NightWatch relies on the CIA World Factbook as a standard reference for unclassified factual, baseline information, as does the Intelligence Community. On three occasions since 2006, NightWatch has found errors in the Factbook,” the newsletter added. “This was the third occasion.”
A Congressional Research Service report last month also cites a total Syrian population of “more than 22 million.”
Errors, of course, are to be expected– even, and especially, in intelligence publications. One great virtue of the CIA World Factbook is that it is a public document. This makes it possible for readers to identify such errors, to draw attention to them, and to promote their correction.
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.