Solving problems through greater diversity
Female representation in the field of analytics and data science is not as great as it should be. Both industry and academia have a role to play in reducing this gender disparity.
The shortage of senior female professionals in the IT space has been noted before, but remains a concern in the present, despite much ado having been made of the situation in the past. Kelly Lu, business solutions manager for advanced analytics and AI at SAS indicates that it is definitely a case that there are still not enough young women entering this field, but, she adds, it is a scenario that is slowly improving.
She explains that in her opinion, there are not necessarily any specific barriers she can identify that are impeding women in this space, adding that despite this, there have been numerous instances where she has ended up being the only woman in an otherwise all-male analytics team.
"If you ask me, I think the real problem – the one that is leading to this lack of equal representation in the data science arena – boils down to the fact that analytics, artificial intelligence (AI) and other aspects of this field tend to involve a lot of coding. This is something that fewer women have any interest or experience in, due at least in part to the traditional gender expectations," she says.
"After all, girls are not usually encouraged to play video games or to get into computers, which means they are seldom exposed at an early age to the basics required for a career in data science. We need to encourage more girls to take up computers and coding as a hobby at a young age, as this will then more likely develop into a passion and will thus feature on the radar when the time comes to choose a career."
She points out that a lack of passion for IT-related subjects is one of the reasons fewer students today are taking the STEM (science, technology, engineering and maths) subjects at school, and without these, you are unable to pursue degrees in fields like robotics or computing.
"It's critical to encourage kids to take these subjects all way, even if they're unable to see how such subjects will apply to real life. Believe me, when you get into a career like data science, you will instantly be able to see how maths applies to it."
"What we need are teachers who can demonstrate the real-world applications of subjects like maths. Furthermore, we need the youngsters to understand that something like analytics is not confined to a single field of study. In fact, it is something that can integrate into multiple industry fields, from financial services through to healthcare."
Lu explains that it is equally important to make the youth aware of the new career paths that are opening up in the IT space. For example, she says that when her younger sister was deciding on what to study after school, the only career options she was exposed to were the traditional doctor, lawyer and accountant-type choices.
"Something like data science or AI had never even entered her mind, because she hadn't really been educated about its potential. Thus, I feel it is vital for modern career guidance counsellors to educate students about the broadest possible spectrum of potential career choices."
"The industry also has a role to play here, and should be actively doing more to promote the potential career paths and to provide a clearer understanding of what it does. It's also necessary for the industry to put effort into educating students around things like how coding impacts their everyday life, such as the role it plays in the cellphone that is so important to every single teenager."
As far as attracting more women into the field, Lu suggests that educating them around the real world applications for data science is the best way to draw them to the profession. Women are especially attracted to careers where they can do good, she explains, so for them to learn the role AI is playing in the search for a cure for cancer, in helping to save the rhinos and even in the protection of foster children may well change their minds about the subject.
"More critically, because analytics is a field focused on solving problems and improving things significantly, it is necessary to drive greater diversity into the field, since the more different voices that are involved, the greater the number of new and unique ideas and thoughts you will get. Obviously, excluding an entire gender is something that goes completely against this," she concludes.