State Department Reveals 2009 Intelligence Budget Request
The U.S. State Department’s Bureau of Intelligence and Research (INR) is among the most highly regarded members of the U.S. Intelligence Community. Not coincidentally, it is also among the most open and accessible.
In particular, it is one of the only Intelligence Community organizations that regularly publishes its budget (pdf). (The FBI also discloses much of its intelligence spending.)
Thus, the recent 2009 State Department budget justification book projects a 2009 INR budget of $59.8 million for a staff of 313 persons.
This would be unremarkable except for the fact that INR’s budget disclosure policy deviates from the norm of U.S. intelligence classification policy, in which most budget information is automatically classified. Even some intelligence organizations that are smaller and less influential than INR insist on classifying their budgets.
For more than a decade, the Department of Energy Office of Intelligence published its detailed budget each year. But under pressure from CIA (so I was told), DOE began withholding its intelligence budget information in 2004. The last reported figure for DOE intelligence was $39.8 million in FY 2004.
If consistency in classification policy were to prevail throughout the U.S. intelligence community, as the Director of National Intelligence has recommended, then State Department intelligence might be expected to follow DOE intelligence into pointless, unnecessary secrecy.
The energy transition underway in the United States continues to present a unique set of opportunities to put Americans back to work through the deployment of new technologies, infrastructure, energy efficiency, and expansion of the electricity system to meet our carbon goals.
The United States has the only proven and scalable tritium production supply chain, but it is largely reserved for nuclear weapons. Excess tritium production capacity should be leveraged to ensure the success of and U.S. leadership in fusion energy.
Despite an emerging awareness of the importance of state and local government innovation capacity, there is a shortage of plausible strategies to build that capacity.
Innovations in artificial intelligence and robotics will allow us to accelerate the search process using foundation AI models for science research and automate much of the experimentation with robotic, self-driving labs.