U.S. military spending on the war in Iraq has nearly matched the cost of the war in Vietnam, according to a new Congressional Research Service analysis (pdf) of the financial costs of wars throughout U.S. history. And total post-9/11 U.S. military spending has exceeded the cost of Vietnam by a considerable margin.
The ongoing war in Iraq has incurred an estimated $648 billion to date, and total post-9/11 military spending including the Iraq War, Afghanistan and other terrorism-related military expenditures has reached $859 billion, the CRS reported.
The Vietnam War (1965-1975) cost an estimated $686 billion in 2008 dollars, the CRS said.
The total cost of the American Revolution (1775-1783) was $101 million, or about $1.8 billion in 2008 dollars.
The cost of World War II (1941-1945) was about $4.1 trillion in 2008 dollars, and consumed a massive 35.8% of gross domestic product. The Iraq war represents 1% of GDP today.
These estimates include various caveats and limitations spelled out by CRS.
“All estimates are of the costs of military operations only and do not include costs of veterans benefits, interest paid for borrowing money to finance wars, or assistance to allies,” the CRS report indicated.
“Comparisons of costs of wars over a 230 year period… are inherently problematic,” the new report cautioned. See “Costs of Major U.S. Wars,” Congressional Research Service, July 24, 2008.
Commercial artificial intelligence tools have recently emerged that are able to produce police reports. If the resulting reports are inaccurate, incomplete or biased, or if the process leaks confidential information, this could undermine the criminal justice system and harm citizens.
Too often, affected patients, clinicians, and regulators cannot see how the system works, why a decision was made, or whether meaningful human oversight occurred.
Existing tools from other domains, such as existing robust public engagement processes in drug development, when applied to AI deployment can help strengthen public trust in these systems and enhance perceptions of their legitimacy and the decisions they produce.
With thoughtful policy action, it is still possible to build systems that are fair, transparent, and accountable, and to earn the public trust that will ultimately determine AI’s future. We hope policymakers are ready to act.