In this article, you’ll get to read an interview that took place between Tom Allen, Founder of The AI Journal, and Aishwarya Srinivasan, AI & ML Innovation Leader for Business Development at IBM and Founder of Illuminate AI.
Together, Tom and Aishwarya look at how technologies such as AI, machine learning, and deep learning can help us while highlighting challenges that need to be addressed and how we can overcome them.
Tom: What got your interest in the space of data science and AI
Aishwarya: When I was young, my mother worked as a research officer in a business school. We didnāt have a computer at home so I used to go to her office and spend hours there working on my projects. Since high school, I was curious and intrigued about what my mother was working on. Back then she was using IBM SPSS for pulling data analytics reports together and building statistical models. While being with her, I could also interact with a lot of professors who were doing research using data. Back then data science wasnāt all the buzz, but data and facts have always been used to back insights.
I have always loved problem solving, and at some point in my childhood, I used to feel I should be a detective, as I had a sharp observation of things. Ignited by problem solving was my interest in computer science. I still remember my favorite class used to be coding in PC Logo back in 6th grade. I somehow felt that this is my ikigai, this is something I really enjoy doing and I felt I can do this forever without feeling it was a job. I am glad I still feel the same about this field, and hopefully, it stays with me in the future as well.
While in school, I started doing mini projects with the professors in my mothers office around making regression models around global industrial production and utilization of goods , as that was the area of expertise of the professor my mom used to work with. That was the spark and data science grew on my like fire. I followed my passion in the field through my undergraduate studies and researched data science and cloud computing. I did multiple projects spanning industries with consulting, finance, social media, communications and environmental. I quite naturally transitioned into the field since a young age and have seen how the ādataā field has moved from analytics on excel and SPSS to machine learning.
Tom: Reinforcement learning has played a significant part in your career, what are your views on the current technology and the future potential of reinforcement learning?
Aishwarya: I started researching in the space of Reinforcement learning since summer 2018 when I joined IBM as an intern. I am still continuing to work on it and exploring various applications of it. My first read on RL was from Googleās DeepMind AlphaGo. It was indeed a fascinating work, but I wanted to expand it to real-world use-cases. Coincidently, I met my mentor whose expertise was in finance, and I got intrigued too. I had barely any background in finance, so I started readin more on it. Interestingly, I found a way to solve a complicated trading challenge from a computational prespective using RL. That turned out to be a novel approach and I could apply for a patent. As far as RL being productionalized or being a part of main stream technology in industry, I feel we are still far away. I have had this conversation with multiple clients from various industries and how RL would fit into their use-cases. Yes, the technology has a lot of potential, but to make it have more value than the existing supervised/unsupervised machine learning methodologies, it needs way more work, way more data and catastrophic analysis. So, I am still working on learning more about it and exploring the possibilities.
Tom: What are the challenges women face in the field and how do we overcome them?
Aishwarya: I have been working in the community of Women in Data Science as an ambassador to create awareness on the possibilities. I have heard a lot of negative and discouraging comments myself, when I wanted to pursue my Masters. People would expect women to not be ambitious, or they would tag us as a rebel. If we are assertive, we become arrogant. If we choose a career over anything else, we become selfish. It sometimes hurts me to see the kind of stereotypes people have for women and expect them to be low-key in life. I really want to get my voice out and reach those people who are maybe hesitant to step up or have been conditioned to believe that women cannot be something. I want to bring out the stories of many other women who have established their worth in their fields and reach to the community.
We need to work on this together and break the misconceptions that stay in the field of STEM that women cannot code or they cannot be a leader or they cannot be hustling etc. Well, there are ample of women in this field whose work and success speak for what women can achieve.
I am working on multiple initiatives to organize events and session to talk
Tom: In 2021, you launched Illuminate AI a volunteer mentorship platform, could you elaborate on what inspired you to launch this platform and what it offers?
Aishwarya: My mentors have been my greatest strength in helping me decide which direction to pursue not just in my professional career but also in my personal pursuits. I wanted to provide people with the opportunity to find their mentor in the field of Data Science AI by connecting them with like-minded individuals. Since this domain is new, it is particularly difficult to find mentors who are willing to guide newbies towards their goals whether it may be finding the right university course, preparing for interviews or succeeding in a data science career.
You can find out more about the initiatives Aishwarya is leading by following Aishwarya on LinkedIn and going to the Illuminate AI website to see how you can get involved.
I know Aishwarya. Her technical skills are just a gimmick and her job is marketing. Good try here.