Ada Lovelace found poetry in computer algorithms

By MEGHANA RAVI | October 17, 2019

Ada Lovelace was the world’s first computer programmer. She, working alongside Charles Babbage, made the critical leap from math to machine — calculation to algorithm. This jump was only possible because of the complex intersections in her past that merged art and logic together. 

Ada was born in 1815 to Lady Anne Isabella (Anabella) and Lord Byron (yes, that Lord Byron). Their marriage was problematic to say the least. Just a few weeks after Ada’s birth, her mother legally separated from Byron, taking her daughter with her. Having had an extensive education herself, Anabella ensured Ada had the very best tutors. One of her many teachers was Mary Somerville, the first woman to be accepted into the Royal Astronomical Society. 

Unusually for a woman of the times, Ada was taught science and mathematics. Her mother worried that Byron’s madness had passed on to Ada, and she believed the strict rigor and logic of science and math would stave away any impulsivity or moodiness on Ada’s part. 

Ada took to mathematics like a duck to water. She was fascinated by machines and started exploring the possibility for human flight among other things in her early teens. When she was 17, it was Somerville who introduced her to her soon-to-be lifelong friend and mentor, Charles Babbage. He was impressed by her mathematical prowess and she was fascinated by his inventions.

Ada was eventually asked to translate a French article on the Analytical Engine by Italian engineer Luigi Menabrea into English. Ada’s understanding of the machinery outstripped the original author. Her translation notes ended up three times longer than the original paper itself. In it, she conceptualized a new expansion of the Analytical Engine to calculate the Bernoulli numbers. This was considered by many to be the first complex computer program. In the process of writing this program, Ada used looping and conditional branching, ubiquitous concepts in modern computer programming. Additionally, she proposed that the Analytical machine would be able to crunch more than just numbers. She hypothesized it would be capable of symbolic logic, maybe one day even composing music.

Yet, what’s really special about Ada was her creative way of perceiving science and mathematics. She elevated the language of her personal mundane into poetry. 

Biographer Dr. Betty Toole described Ada’s logical abilities as both unique and beautiful. Despite her mother’s best attempts, Ada merged poetry into her mathematical work. In a letter to her mother, she called this merging “poetical science.” 

Ada saw intricate connections between her work, the world and art. She saw the equations and math she was doing as a type of language — a tool to express and understand creation. Ada extrapolates on this idea in the Menabrea translation notes. She explained her understanding of math as art by highlighting its deep significance to the human race through its unique ability to communicate concepts observed in the natural world. She was in pursuit of the intrinsic beauty of her work. This opening of the third eye, so to speak — this foundational perception of the artistry of algorithms — was achieved by her looking at it as though it was poetry.

Here at Hopkins, I have personally noticed a clear split between STEM and the humanities. I have friends who are humanity majors that wouldn’t touch an equation with a 10-foot pole. I have met STEM majors who have spasms at the word “essay.” They both say very similar things: that they’re not good at it, that they just don’t like it, that they were through with it after high school, so on and so forth. 

While I have observed that there are more STEM majors open to pursuing a humanities major “for fun” or “for a break,” this rarely extends the other way. This is in part because scientific terminology and methodology can be complex and excluding. Yet, complicated theoretical frameworks and higher education are not always needed to see your work through a new lens. 

Ada is very much the kind of expert I strive to be; someone who pursues not only truth, but nuance. Someone who can express advanced scientific knowledge with the grace and fluidity of prose and poetry. She is a shining example of how striving to connect dissonant fields, ideas and theories generates new ideas. She never formally studied poetry but because of her application of it to her work, she made a leap that wouldn’t see fruition for a century. She theorized that machines could work in a sophisticated language of symbols — that they themselves could, in a way, do poetry.

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