Over the centuries, women in STEM have had an incredible journey of contribution and innovation. STEM-inspired fields like Aerospace, National security, Biochemistry, Data Science and Artificial Intelligence(AI), etc, use cutting-edge technologies that need a broader and unbiased perspective. Concerning the increasing gender gap in STEM-related fields, there is a drive to encourage and promote women to take up STEM courses. Let’s find out how data science and AI advancements are helping bridge the gender gap in technology.
Gender Diversity Crisis – Where are the Women in STEM?
Research indicates women are a small minority in STEM-related fields with just 30% who enrolled in STEM subjects in higher education.
“What is STEM” remains a mystery to many girls, as they face a lack of encouragement, guidance, and awareness towards these disciplines. Social bias and stereotyping also lead the girls to bail out on these subjects. This small proportion of women employed in STEM-related jobs faces a further decline in the number- Unequal employment, career opportunities, work-life balance challenges, and the absence of role models are some of the triggering factors that force women to quit early.
Need for Women in Data Science and AI: Ways to Empower Women
Our knowledge in the STEM-related domain, specifically in Data Science, Analytics, Robotics, and AI have led to great innovations that help us solve global issues and make life-changing decisions. However, future technology will not be free of bias if women’s point of view is excluded.
Here are a few points why we need women in STEM-related careers:
- Skills gap:
Statistics show there is a low talent pool of skilled professionals in these technologies. With women contributing to half the population, it makes sense to hire more females to fill these job roles.
2. Diversity drives innovation:
Shweta Bhatt, a Data Scientist and a mentor at Springboard, expressing her views on women in Data Science says – “Diversity will help your teams to progress and have different and alternative points of view while solving the problems, and will reduce bias. Future technology will not be able to meet the needs of a diverse population if it is being shaped by a small section of society with a singular worldview.”
3. Higher empathy and cooperation:
Shweta says “women’s perspective and insights add additional value to the business.” Monisha, another leading Instagram Data Scientist suggests – “Women have a lot of empathy, which is important for the end-users, and to collaborate with cross-functional teams to arrive at a mutual decision.”
4. More visionary:
Women often see the bigger picture of the problem at hand and bring a different perspective to the table. This elevates creativity, productivity and generates more revenue.
5. Convincing communicators:
Monisha says: “Evangelising your findings and advocating your work is the key, and women tend to be good at that as compared to males.” Fortunately, women are taking front seats in medicine, research, IT jobs, Defence, Science, and similar domains. They are equally potential, analytical, statistical problem solvers. We have women entrepreneurs with excellent business knowledge and experience. What’s more, there are enough and more women who excel in math and also love to code. Women have already demonstrated their abilities in these domains and will continue to do so.
“AI is an expression of its creator”. It comes as no surprise that having just one male’s point of view on building AI algorithms has some evident epic failures such as the ones given below:
- An Amazon recruitment system rejected female applicants as it was based on biased data such as names, hobbies, and verbs used by men.
- Common AI systems like Amazon’s Alexa and Apple’s Siri, have been found to show gender biases.
- Computer vision systems for gender recognition reported higher error rates for recognizing women.
- AI bias has crept into our healthcare deep learning algorithms that are based on past patterns and put certain races at risk due to inaccurate historical data. As was the case in a recent algorithm that was fed heavily man-oriented medical records that failed to predict heart attacks in women.
AI-driven intelligence is, after all, fed by humans and is based on historically biased-data that gets amplified when we input such data into our machines. Thus, the need to increase the women workforce is the only way to equate the men to women ratio. We must develop a positive attitude towards the girl’s abilities, and they must be given the same opportunities and resources. We must discourage stereotyping and promote gender equality. While our textbooks only mention inventions and contributions by male minds, on the contrary, the journey and life experiences of women role models must also be taught. This will impact women’s decisions in taking STEM courses, and in-turn will cultivate confidence.
The future of AI lies in humans and machines working hand-in-hand overcoming each other’s shortcomings. This technological revolution is gradually creating new job roles to narrow down gender disparities.
For instance, if we feed the right set of instructions to algorithms and model the accurate data, AI-driven decisions and predictions will be free of human-like-errors such as favouritism and gender bias. AI apps like Pipeline are now being used by organizations to attain a balance of both genders to boost their businesses. Top institutions and organizations are driving initiatives to educate and employ more women in STEM and fund female entrepreneurs.
Women-friendly flexible policies and strategies, like a child and elderly care, paid leave, and work-life balance, are being incorporated that encourage women to pursue long and healthy STEM careers. Many Organisations such as @IndianGirlsCode, and The WISE campaign for gender balance in STEM, and The rising 2020 event provide a platform for women from various STEM-careers to learn, exchange ideas, career interests and achievements. This motivates and empowers women to join the bandwidth and make a difference.
Springboard’s data science career track program is structured keeping in mind everything you may need in your career transition. We’ve made all our courses 1:1 mentoring-led and project-driven to give aspiring data science professionals the perfect combination of theory, practice, and guidance needed to shine in their careers. If you’re contemplating a data science career, explore Springboard today! The hands-on project curriculum offers a better grasp of STEM careers for a brighter, unbiased future.