As the interest and investment in AI surges again -- most recently, Apple announced it’s hiring another 86 AI engineers to compete with the other software giants -- and Silicon Valley tries to work out how to solve its diversity problems, it’s vital to pattern recognize what female minds bring to tech innovation and to observe that some of our greatest breakthroughs have happened when diverse teams, especially of gender, work together. We've already looked at how important empathic and logical thinking is to developing a nuanced artificial intelligence, and how this can be inspired by collaborations between men and women in the typically male-dominated field of computer science.

To learn about making our systems intelligent and our products capable of understanding our natural language, let’s go on an adventure and celebrate past male and female partnerships (X & Y) that can help us with the biggest problems of today: solving the building of smart, inspired teams, and helping us answer "What can we build and how do we do it?"

We'll start the journey in the 1800s:

• 1830s: world’s first computer = Ada Lovelace + Charles Babbage

• 1941: Wi-fi, Bluetooth + CDMA =   Hedy Lamarr + George Antheil

• 1944: Harvard Mark I computer = Admiral Grace Murray Hopper + Howard Aiken

• 1959: COBOL language = Admiral Grace Murray Hopper + UNIVAC team

• 1969: Apollo 11 moon landing = Margaret Hamilton + NASA team

• 1971: Computer telephony switching = Dr Erna Schneider Hoover + Bell Labs team

• 1972: Smalltalk language (later Squeak) = Adele Goldberg + Alan Kay + Xerox PARC team

• 1974: CLU language = Barbara Liskov + MIT team

• 1985: Spanning Tree Protocol (STP) for the Internet = Radia Perlman + Digital Equipment Corp team

• 1990s: ATMs & distributed transaction processing = Dr. Mandy Chessell + IBM team

• 1995: Affective Computing = Rosalind Picard + MIT team

• 2015: Virtual Reality = Mary Lou Jepsen + Facebook/Oculus team

The Origins of Computing

Like the origins of the Universe and our species, Yin (female) and Yang (male) were involved in the origins and continuing evolution of computing. In the 1820s, Charles Babbage had designed but not built his Difference Engine for calculating polynomial functions. A decade later, in 1834, he thought up the Analytical Engine to do more complex analysis. When Ada Lovelace was introduced to him in 1833, her prodigious mathematical abilities and language skills soon made her one of his collaborators.

In 1842-43, she published an English translation of a French article on the Analytical Engine by Luigi Menabrea, an Italian engineer. Going well beyond literal translation, Ada Lovelace annotated extensive notes of her own, including the world’s first published description of a stepwise sequence of operations which led to Babbage writing this about her:

Forget this world and all its troubles and if possible its multitudinous Charlatans --- everything in short but the Enchantress of Numbers.

It also earned her reputation as the “world’s first computer programmer”.

Furthermore, in a September 1843 letter to Michael Faraday, who discovered electromagnetism and invented the electric motor, Babbage praised her talents like so:

So you will have to write another note so that Enchantress who has thrown her magical spell around the most abstract of Sciences and has grasped it with a force which few masculine intellects (in our country at least) could have exerted over it.

Unfortunately, more recently, Walter Isaacson noted in his 2014 book tour for ‘The Innovators’:

“If it wasn’t for Ada Lovelace, there’s a chance that none of this would even exist,” Mr. Isaacson added as he waved his hand in the air, gesturing as if to encompass all of Silicon Valley and the techies sitting around us.

In her day, she was all but ignored, too.

In 1843, when Ms. Lovelace’s seminal computing notes were presented to Scientific Memoirs, an English scientific journal of the day, the editors pushed back and told her colleague Charles Babbage that he should “manfully” sign his name in lieu of hers.

Interestingly, Ada Lovelace’s notes from 1843 provide clues for why some of the flaws in big data and natural language understanding in AI exist today - namely, the meanings of words created by their context:

Secondly, figures, the symbols of numerical magnitude, are frequently also the symbols of operations, as when they are the indices of powers. Wherever terms have a shifting meaning, independent sets of considerations are liable to become complicated together, and reasonings and results are frequently falsified.

In this, Ada and Walter prove that technical expertise comes from honed talent, not one's gender.

Computing Becomes Reality

In 1944, a century after Charles Babbage and Ada Lovelace, one of the world’s first working computers was invented and installed at Harvard University, the Mark I (originally known as the Automatic Sequence Controlled Calculator), by Professor Howard Aiken. He’d taken the mechanical, punch-card tabulating machine developed by IBM and converted it into an electromechanical system that could perform arithmetic operations, including complex trigonometry and logarithms.  

When he was joined by Admiral Grace Murray Hopper, she recalled Aiken greeted her with:

Where the hell have you been? Here, compute the coefficients of the arc-tan series by next Thursday.

She dived into coding the Mark I and soon co-produced the 500-page Manual of Operations for the Mark I, which outlined the fundamental operating principles of computing machines. During and after World War II, the Mark machines were vital in helping the US military to calculate the atmospheric drag, wind, gravity, muzzle velocity and more that affected the trajectory of the shells being fired from their battleships.

Following her Harvard assignment, Admiral Hopper joined the Eckert-Mauchly Computer Corporation in 1949 and the team building the UNIVAC. This became the first commercial computer made in the US and was used by the Census Bureau, the US Airforce, ACNielsen and Prudential.

It’s thanks to Admiral Hopper’s work that, in 1952, she invented an operational compiler of which she said:

Nobody believed that. I had a running compiler and nobody would touch it. They told me computers could only do arithmetic.

By 1959 she and her team had invented COBOL, the first user-friendly business computer software program. Admiral Hopper has some words of wisdom for teams today that are finding it difficult to motivate themselves, to “lean in” and to build their vision:

If it's a good idea, go ahead and do it. It's much easier to apologize than it is to get permission.

In this, Grace and Howard show that leadership and invention are equally the domain of men and women - and even more so when working in unison.

The Future for Human and Machine Intelligence

So women have been and are key to how we solve the hardest problems in technology. The sooner everyone from the Apples, Googles and Facebooks to the smallest startups proactively try to source and foster modern-day Ada Lovelaces and Grace Murray Hoppers, the sooner we’ll have more intelligent systems.

Why and how is this the case?

Well, in recent times, it’s become clearer to the predominantly male developers and AI researchers that better forms of emotions and empathy have to be systematically designed and coded into our machines. This week, Mark Zuckerberg shared that Facebook is looking to include a “dislike” button and their reasoning is:

People aren’t looking for an ability to downvote other people’s posts. What they really want is to be able to express empathy. Not every moment is a good moment, right? And if you are sharing something that is sad, whether it’s something in current events like the refugee crisis that touches you or if a family member passed away, then it might not feel comfortable to Like that post.

Notably, Facebook has also been building up its FAIR unit (Facebook Artificial Intelligence Research) and conducted an emotion experiment around its newsfeed in 2012; the results of which were published in 2014.

Separately, in his article on a potential Emotional Internet, facilitated by the proliferation of IoT sensors, Gareth Price, technical director at Ready Set Rocket, observed:

By studying speech patterns, facial expressions, body gestures and physiological reactions to specific stimuli, researchers hope to amass a database of emotions they can train computers to recognize and interact with.

The key challenge here is to establish a standard for what is definitively “happy,” “sad,” “angry” or another state, because right now, many apps and devices that claim to read emotions aren’t drawing from one definitive standard.

Now, since neuroscience from the University of Basel shows that men and women process emotions differently, we need to bear in mind that male definitions of what’s “happy” and a “like” or “sad” and a “dislike” will be different from female definitions, and we’ll need to solve the problem differently from the way it’s been done before.

In this, Gareth and Mark reveal the nuances of empathy across genders, and emphasize the need for an integrated approach to defining emotion. This may explain why and how we’ve programmed narrow intelligence rather than more universal intelligence into our systems. 

When we look at who’s developing emotional AI, we discover the work of two women: Rosalind Picard of MIT who founded the field of affective computing and Dr. Marian Bartlett of Emotient who’s applying machine vision to interpret people’s facial expressions for emotions. It’s also worth taking stock of Fei-Fei Li, Director of Stanford AI Lab’s, views on AI:

We are very, very far from an intelligent system, not only in sensory intelligence, but cognition, reasoning, emotion, compassion, empathy. That whole full spectrum, we’re nowhere near that.

So for all the teams out there from big companies to small startups that are wondering how to make themselves more innovative and, potentially, be at the vanguard of the tech future, start by learning from the successful male and female partnerships from the past. See that the opportunities to solve big hard problems are sizeable. Tractica estimates that the market for AI applications in enterprise will be worth $11.1 billion by 2024. Now, get out there and source your Ada Lovelaces and Admiral Hoppers to build the gamechanging partnerships that have built Silicon Valley in the past.