Datacast Episode 71: Trusted AI with Saishruthi Swaminathan
By: James Le
Tags: IBM, Data Science, Open Source, Ethical Ai, Public Speaking

Listen to the show on (1) Spotify, (2) Apple Podcasts, (3) Google Podcasts, (4) TuneIn, (5) RadioPublic, and (6) Stitcher.

Key Takeaways

Here are highlights from my conversation with Saishruthi:

On Growing Up in Rural India

I was born in a rural town in the south of India. My dad worked in the Indian posted service, while my mom managed the house and the office. We used to live in a 400-square feet house. Until high school, I literally had no Internet connection at home. I used to visit the local library to read books and newspapers. I used to pay 30 Indian rupees for 15 minutes of Internet connection, just to get a feel of using the computer.

The experience with less technology and more nature actually grew me into the person I am today. My parents made sure that I only heard things that elevated my thoughts and made me a better person. They gave me the freedom while providing a shell around me so that I did not experience too much social pressure. When I moved to the city for university, I could mold myself as a better person.

On Enjoying Programming

After university, I landed a job as a system engineer at Tata Consulting Services. On my first day at the job, I got spec and asked to debug 10,000 lines of production COBOL code. My hands were literally trembling. I didn’t even understand how to get started.

The next day, I was sitting next to my tech lead. He was typing intensely at his keyboard, and I actually wanted to get the same sound. I was so addicted to it that I wanted to get the same sound (even today). Thus, I started enjoying programming. That was the moment that turned my fear into something I enjoyed. I started typing and learning fast, making me more comfortable with programming. I was at Tata for 2 years. At the end of my tenure there, I was the top programmer of my unit, which handled 10 high-priority codebases with over 15,000 lines of COBOL code.

On Getting Into Data Science

I encountered data science during an internship in Seattle. I love that I was able to make data speak to me in which I understand the language. My interest in programming and my passion for innovation intersects. From there on, I was fortunate to take courses like data mining, statistical ML, neural networks, and probability under the finest professors in San Jose State. I also participated in various research projects and other small projects, from smart city to material strength prediction. In the 1.5 years of my Master’s, the amount of data science learning I had gone exponentially. I used to sleep 2 to 3 hours per day. That’s because I enjoyed learning, so I didn’t feel tired at all.

On Public Speaking

Your language or fluency does not matter. Instead, try to:

Be authentic. For all of my talks, I have never reused old content. I always create a specific talk for a specific audience in a way that they can grasp. Even if one person attends my talk, I still present it. I started with as little as a 10-people audience, and recently I delivered an Ethical AI talk to a crowd of 8.5K people. Know your audience and prepare accordingly. It’s a privilege to stand before them and get their time/attention. It’s my responsibility as a speaker to make good use of their time. Present in a simple way. I always break down high-level concepts to simpler levels by connecting them to day-to-day examples. Accept criticism. I’ve been in situations where people stopped me in the middle of my presentations and gave critical opinions. Sometimes it was hard, but I learned to listen to them over time.

On IBM’s CODAIT