This is what speeds up Innovation
How Grace Hopper's Human-First Design Philosophy Accelerates Organizational Innovation
December 7, 1941
The attack on Pearl Harbor launched the US into World War II, but it also revealed a bitter truth: the US Navy was technologically outmatched.
German U-Boats prowled the Atlantic, and the Japanese submarines outclassed their enemies with advanced Type 95 torpedoes and the audacious I-400 class aircraft carrier subs.
By 1944, with over 1,000 Allied sailors dying weekly, America developed the Harvard Mark I to help with attacks and logistics calculations. A room sized calculator that could compute in hours what human-computers needed weeks to complete.
But almost no one knew how to use it effectively. There were no manuals, people needed to use punched paper tape to use it, and most naval officers didn’t have the mathematical expertise to run it.
Winning World War II required making the cutting edge Mark I accessible to people who needed it most.
Learning to speak Machine
In 1944, Grace Hopper arrived at Harvard to work on the Mark I.
The computer had no manual, no organization. It was a behemoth of metal, wires, and clunky relays. 8 feet high and 51 feet long, with 530 miles of internal wiring connecting its relays. Weighing almost five tons and featured 750,000 moving parts.
Her job was to learn the computer and ensure it runs accurately. Her background is in mathematics, but she had to learn other fields to translate their problems into equations and then communicate in a way the machine would understand.
Everyday the Mark I ran calculations, more Allied ships went down. 1,000+ lives depended upon those calculations.
“The whole thing was the war, the end of the war, getting a job done, terrific pressure,” Hopper recalled near the end of her life.
As she worked, she compiled what she learned into the world’s first computer programming manual, a 500-page book that covered how the Mark I worked and how to program it.
The machine was used to calculate ballistics, trajectories, and coordinate operations. It was even used in the Manhattan Project by John von Neumann to determine implosion mechanisms.
Computation helped the Allies win the war, and computers were popular for solving larger scientific and military problems.
The war had been won through computational advantage. The peace would be won by whoever could make the better computer.
The Innovation Bottleneck
More computers were being developed such as ENIAC, but they all had the same problem.
To use them, you had to speak in machine code. Binary digits of ones and zeros. Grace had a PhD in mathematics to run the Mark I, and so did many others who ran computers like Mark I or ENIAC.
“If programming requires mathematical symbols, why would talented people become programmers? They'd become mathematicians instead."
The result was artificial scarcity around innovation participation. Only a tiny community of mathematical specialists could translate business needs into computational solutions.
By the early 1950s, this pattern was clear: every new computer recreated the same accessibility crisis. Grace, now working at Eckert-Mauchly Computer Corporation, saw an opportunity to solve this systematically.
Essays in Math class
Before World War II, Grace taught mathematics at Vassar College.
She began a lecture on Stirling’s approximation and asked her students to write an essay on it.
Her reasoning is that math is just numbers. The numbers don’t talk. You do. No use in learning math if you cannot communicate it with other people.
This is her cornerstone philosophy that she carried throughout her career. From translating fields into equations for the computer & writing a book on how to program a computer.
She had already proven that complex mathematical concepts could be communicated clearly.
Could the same principle apply to machines?
Machines learning Human Language
Since most people aren’t PhDs in mathematics, Grace’s goal was to have a computer understand a command written in English and act on it rather than commands written in binary.
But her colleagues at Eckert-Mauchly were skeptical. 'Computers are mathematical machines,' they argued. 'They can only process numbers, not English.' Grace disagreed.
In 1952, she made the A-0 compiler that translated English into machine code automatically. For the first time, programmers could write commands that resembled human logic rather than mathematical symbols.
Before the Compiler, programmers had to say:
Take the number out of unit A; deliver it to unit B; start operation C.After the Compiler, a programmer could type:
subtract income tax from payThis compiler technology became the foundation for FLOW-MATIC, which led directly to COBOL in 1959.
Modern programming is made possible because of compilers.
Her compiler opened computing to business analysts, scientists, engineers of the time, anyone who could clearly describe their problem could now use a computer. It even helped us reach the moon.
During the Cold War, computational advantage meant national security. By democratizing programming, America multiplied its innovation capacity.
Making the Complex Simple.
Grace never stopped teaching.
She has a famous lecture of how long a nanosecond is. She hands out a piece of wire that is the distance electricity could travel in a nanosecond.
It is 11.7 inches long. She was a genius at making abstract concepts tangible.
“The most important thing I’ve accomplished, other than building the compiler, is training young people,” she would say in her later years. “They come to me, you know, and say, ‘Do you think we can do this?’ I say, “Try it.” And I back ’em up. They need that.” The worst thing people can say, she would add, is “We never did it like that before.”
Her approach to translating complexity to simplicity made modern day computers possible.
Speaking the language, not jargon. Finding ways to transfer knowledge across fields, and focusing on trying new ideas.
The question we face with AI today is similar.
AI is democratizing programming again with vibe-coding, vibe-writing, vibe-designing. Taking sentences and turning them into computer commands.
But this asks a deeper question: where are we still forcing people to learn our systems instead of making our systems learn from people?
Or as Grace would say: Why are we making humans think like machines?
The organizations that thrive will be those that flip the burden. Make the complex simple. Teach systems to speak human. Create the wire demonstrations that make abstract capabilities tangible.
Grace Hopper proved that the most revolutionary technical breakthrough is often the one that makes technology disappear entirely.
References
Primary Sources
Hopper, Grace M. Interview with Angeline Pantages. Charles Babbage Institute, University of Minnesota. 1980.
Hopper, Grace M. "The Education of a Computer." Proceedings of the Association for Computing Machinery Conference, 1952.
U.S. Navy Bureau of Ships. Harvard Mark I Automatic Sequence Controlled Calculator Operations Manual. 1944.
Historical Documentation
Computer History Museum. "Grace Hopper: The Mother of COBOL." Oral History Collection.
Harvard University Archives. Harvard Computation Laboratory Records, 1944-1947.
IBM Corporate Archives. "Automatic Sequence Controlled Calculator (Harvard Mark I) Technical Specifications." 1944.
Military and Naval Sources
U.S. Naval History and Heritage Command. "Battle of the Atlantic: U.S. Naval Operations in World War II."
Aiken, Howard H. "The Automatic Sequence Controlled Calculator." Electrical Engineering, Vol. 65, 1946.
Von Neumann, John. First Draft of a Report on the EDVAC. University of Pennsylvania, 1945.
Technical Publications
Sammet, Jean E. Programming Languages: History and Fundamentals. Prentice-Hall, 1969.
Ceruzzi, Paul E. A History of Modern Computing. MIT Press, 2003.
Wexelblat, Richard L., ed. History of Programming Languages. Academic Press, 1981.
Contemporary Sources
CODASYL Development Committee. COBOL: Initial Specifications for a Common Business Oriented Language. 1960.
Eckert-Mauchly Computer Corporation. Short Code and A-0 Compiler Documentation. 1952.