From the 90s and onward, movies that depicted robots taking over the world were all the rave. The likes of The Matrix trilogy and I, Robot gave us a glimpse of a world where technology superseded human intelligence and became a threat to human society
Initially, some might have scoffed at the idea, labeling such movies as works of fiction or fantasy, however, we cannot deny that we live in a technologized world in which Artificial Intelligence (AI) and Machine Learning (ML) are no longer abstract concepts in the minds of tech geniuses.
Machine Learning is a branch of AI and computer science whereby, through the use of data and algorithms, computer systems imitate learning the way that humans learn, getting more accurate with continued use.
To illustrate, think about speech recognition software like Siri that learns the sound of your voice and responds to questions based on your unique preferences.
Also, consider chatbots that pop up on some sites that provide information based on how you respond to questions. These are some relatable use cases of Machine Learning.
While many organizations value the knowledge of data science today as they build intelligent systems based on Machine Learning, they need to recognize the importance of hiring diversely in this space.
As it obtains in other technology sectors, there is a scarcity of women in machine learning. According to one report, 13.5% of the field is made up of women. This low figure is expected considering that only 24.4% of women currently make up the computer science workforce globally.
The AI Now Institute warned that the AI industry needs to acknowledge the gravity of its diversity problem and admitted that existing methods have failed to contend with the uneven distribution of power.
One argument for this is that without gender diversity, the fear that AI systems may perpetuate existing forms of structural inequality and cause harm to underrepresented groups is all too real.
Since diversity is a key quality of humans, Machine Learning needs input from people of diverse backgrounds. Simply put, if machines are programmed by biased people, they’ll learn biased responses.
To reduce the problem of gender bias, more women should be onboarded into the industry.
Women in Machine Learning
Are there women in the field of machine learning? Yes, indeed! There is a growing number of phenomenal women making meaningful headway in the space.
We’ve compiled a very short list of African women at home and in the diaspora, showcasing their achievements with the hope that more young women will be inspired to join the rank.
Joy Buolamwini
Joy is the founder of the Algorithmic Justice League, a digital advocacy organization, that aims to create a world using more equitable and accountable technology. Dubbed the Poet of Code, she blends art and research to illuminate the social implications of artificial intelligence.
Being a technologist through and through, she holds two masters’ degrees from Oxford University and MIT; and a bachelor’s degree in Computer Science from the Georgia Institute of Technology.
Joy’s interest in unmasking biases in technology drove her to explore the racial, skin type, and gender disparities embedded in commercially available facial recognition technologies produced by companies like Microsoft, IBM, and Amazon. Her research led to her publishing two groundbreaking, peer-reviewed studies.
The Ghanaian-American computer scientist and activist has been featured on TEDx talks and has her articles publicized in TIME Magazine and New York Times. She serves on the Global Tech Panel convened by the vice president of the European Commission to advise world leaders and technology executives on ways to reduce the harms of A.I.
Joy has been named Bloomberg 50, Tech Review 35 under 35, Forbes Top 50 Women in Tech (youngest), and Forbes 30 under 30.
Inioluwa Deborah Raji
Inioluwa identifies as a student, self-starter, social entrepreneur, and volunteer who is vested in making constructive contributions to society. She is the founder of Project Include, a non-profit initiative to increase access to Engineering Education in low-income and immigrant communities.
Inioluwa is a graduate of Engineering Science and Robotics Engineering Option from the University of Toronto. As a research fellow at Algorithmic Justice League, she worked closely with Joy Buolamwini on the groundbreaking thesis that revealed the inherent racial and gender bias in facial recognition services.
For her contributions, the young Nigerian-Canadian made the Forbes 30 under 30 list in 2020 and she’s also the recipient of twelve other honors. Currently, Inioluwa is Mozilla Fellow.
Tejumade Afonja
Tejumade is the Co-founder of AI Saturdays Lagos, an artificial intelligence community in Lagos, Nigeria, that offers free classes on Data Science, Machine Learning, and Deep Learning.
A first-class graduate of Mechanical Engineering at Ladoke Akintola University, Nigeria, Tejumade is an experienced software developer, frontend developer, and AI software engineer. Her desire to understand how machines think ignited her passion for Robotics and Machine Learning.
Having discovered the potentials of Artificial Intelligence, she is set on a mission to help democratize AI knowledge in Nigeria of AI through her AI Saturdays Classes. In addition to being a co-founder, she’s both a mentor and volunteer at various organizations where she uses her skills to train others.
Tejumade is currently running a Master’s degree program in Computer Science at Saarland University. She’s the recipient of several accolades, including the 2018 Top Innovator at Intel Software Innovator Program. In 2020, she was honored as a Google Generation Scholar.
Are you a woman in tech seeking an opportunity to get featured, shoot us a mail women[at]techbuild.africa
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