An Intelligence History of the 1973 Arab-Israeli War
The Central Intelligence Agency has published a series of essays on intelligence and the 1973 Arab-Israeli war, to coincide with a symposium on the subject held last week at the Nixon Presidential Library.
The publication itself (“President Nixon and the Role of Intelligence in the 1973 Arab-Israeli War”) is a welcome addition to the literature. But it also “includes some embarrassing errors,” wrote Amir Oren in the Israeli paper Ha’aretz on February 3 (“CIA report on Yom Kippur War: Israel had nuclear arsenal”).
“For example,” Oren wrote, “in the photograph labeled ‘An Egyptian soldier holding up a portrait of President Sadat,’ the soldier in question and the two soldiers flanking him are clearly Israelis, as evidenced by the ‘IDF’ stamped visibly on their shirts.”
“The editors of the new study also err in attributing two things to lessons from the Six-Day War: the faulty prevailing conception among Israeli Military Intelligence ‘that Israel would have at least 48 hours’ warning before an invasion’ and that Sadat wouldn’t start a war before acquiring fighter planes. Furthermore, it seems they also confused war analyst Maj. Gen. (ret.) Chaim Herzog with one of his sons, Brig. Gen. (ret.) Mike Herzog,” he added.
If these discrepancies are cause for embarrassment, then it is the kind of embarrassment that should be willingly endured. To put it another way, exposing such work to external review and criticism is an unsurpassed way of identifying and correcting errors.
Advancing the U.S. leadership in emerging biotechnology is a strategic imperative, one that will shape regional development within the U.S., economic competitiveness abroad, and our national security for decades to come.
Inconsistent metrics and opaque reporting make future AI power‑demand estimates extremely uncertain, leaving grid planners in the dark and climate targets on the line
Federal and state governments need to ensure that the development of new AI and data center infrastructure does not increase costs for consumers, impact the environment, and exacerbate existing inequalities.
As AI becomes more capable and integrated throughout the United States economy, its growing demand for energy, water, land, and raw materials is driving significant economic and environmental costs, from increased air pollution to higher costs for ratepayers.