Significant gender bias, discrimination and stereotypes still exist within social norms; about 90% of people (both men and women) hold some bias against women. In the era of the Fourth Industrial Revolution, a particular area to focus on is in science and information technology where the challenges posed by the digital divide as well as the under-representation of women in STEM (science, technology, engineering and mathematics) continue. In modern society, the significance of AI and data science is making its way as a critical driver of economic growth, however, if the algorithms that underpin AI are not developed and applied in a gender-responsive way, they are likely to reinforce existing gender stereotypes and discriminatory social norms. “Artificial Intelligence is only as good as the data we feed it – so it is our responsibility to make sure it is socially inclusive”.
With AI and Machine Learning now deeply embedded in our lives– from virtual assistants, social media, and the way we search online– its impacts are transformative and far-reaching and will continue to impact key decisions such as employment propositions, advances and even criminal condemning.
Women have an important role to play in Artificial Intelligence, data science and machine learning. While the gender balance in the AI field has been poor, women in AI do exist and many of them are already championing change and doing extraordinary things to help address and close the tech gender gap. Some notable women include:
Dr Catherine Breslin – Machine learning consultant, Cobalt Speech
Dr Catherine has recently transitioned from her role in Machine Learning for Amazon Alexa to her new role as a consultant at Cobalt Speech, a company that advises businesses and provides high performing custom voice and language technology for them.
Interestingly, Catherine didn’t even know she was interested in computing when she was studying engineering, only after enjoying a module in computer science in her first year of study, did she switch to a joint major. She wanted to understand how computers could learn to do the things that humans found easy – in particular speech and language.
Her role at Cobalt is varied with no day being the same – projects involving analysing, call-centre audio, voice interfaces to control factory machines, and tools to assess the pronunciations of foreign language learners.
Lisa Bouari – Executive Director, OutThought AI Assistants)
Lisa Bouari, cofounder and executive director of OutThought, is one of three Australians to make IBM’s annual Women Leaders in AI awards. OutThought was born out of seeing a need in the market for making virtual assistant technologies harnessing AI, targeting small and medium sized organisations.
OutThought created a virtual health coach that leverages IBM Watson Assistant to track users’ physical activity goals and provide personalized recommendations on health and lifestyle. Users of the virtual health coach increased their weekly physical activity by two hours, improved the quality of their diets and achieved a reduction in waist circumference and weight loss.
Why AI needs more women
Machines themselves aren’t prejudiced, however, the people creating them can be – and some examples have revealed a gender problem lurking deep within AI. Alarmingly, according to the World Economic Forum’s (WEF) Global Gender Gap Report 2018 only 22% of AI Professions globally are female, which means the remaining 78% are male. The report also indicates that men and women with the same skills are places in different roles. Women are more likely to be employed as data analysts and researchers whereas men are likely to be placed in roles that hold greater seniority, such as software engineer, head of engineering, head of IT as well as business owner and CEO. As a result of this women are not engaged in the creation of AI and innovative technologies.
The problem is in the algorithm that creates this gender bias. To redress the balance, women must be involved in creating algorithms, designing systems and monitoring them. We need more diverse teams, specifically more women to make use of it. Diversity is essential, women working in the field should be well supported and more women should be encouraged to take up careers in STEM related fields. Increased women participation will improve fairness in decision-making, particularly where humans don’t have the best track record due to conscious and unconscious biases.
As AI is increasingly being used to influence the products we buy and the music and films we enjoy, to protect our money, controversially, to make hiring decisions and process criminal behaviour, more vigilance is needed to ensure fair outcomes.
Let’s not also forget that the first ever robot citizen was a woman (Sophia)
It is a collaborative process. AI isn’t developed from the top down; businesses must empower teams to communicate any concerns as legislation is catching up. Automated systems and algorithms will become accountable as well as tech companies so that we are empowered to overcome bias, continuously review and manage any risks of bias from existing and future AI programs.