Why We Should Conquer Our Misplaced Fears & Embrace AI/ML in the Workplace

There’s plenty of misinformation and fear mongering out there about the current state of machine learning and AI. To that end, we sat down with Bhumi Bhanushali, Machine Learning Engineer at adMarketplace, to clear the air on these misconceptions and gain more insight into the field.

Bhumi shares how AI/ML will impact the future of technology, how machine learning can be applied to any field, and why women shouldn’t be intimidated to start a career in tech.

‍What inspired you to pursue a career in machine learning? What do you love about the field? From your perspective, how is it unique from other specializations in technology?

What I love about machine learning is that it’s a field that touches so many areas. I have worked in the field of machine learning for different applications and you can really apply it to anything - biomedical, agriculture, psychology, anything.

When I was in India I was trying to explore different applications of computer science, and machine learning was one of the courses I took during undergrad. I liked it, but I wasn't sure about it. I tried two or three different courses and I was interested in all of them, but then a lot of my input came from my school. It's known for machine learning.

It's basically psychology. You can think of teaching machine learning as teaching something to a kid, like a language. You would start with basic alphabets, then teach words, then sentences, and then the bigger things. So that is how machine learning also works — it’s bit by bit. 

‍In your opinion, what are some common misconceptions about machine learning and how do you address them when communicating with non-technical stakeholders or the general public?

One big misconception is AI will take all our jobs. It’s not true. There's something that was released recently which was an AI software engineer. It's great, but it just codes and fixes bugs. A software engineer has to keep making the pipeline better and more robust. You can think of AI as a tool like your smartphone. When smartphones and calculators were released people thought we wouldn’t need to learn math, but we still did.

‍With the democratization of machine learning tools, how do you see the role of ML engineers evolving in the coming years and what new skills do you think will be essential for success in this field?

ML engineers kind of do everything, from research to development to testing to production. I think ML is currently evolving in both research and production. Learning how to deploy models and how to optimize production so that the models run faster with good latency is really important.

‍As AI continues to evolve, what emerging trends or technologies within the field of machine learning excite you the most and how do you see them impacting the future of technology? 

I think the more people work on building the products end-to-end, that's something that will be evolving. Right now, there is a person working on one individual task. But if somebody is able to do that individual task, you're not adding that much value. You're just automating one part of the process. So you have to look at the whole process.

‍adMarketplace recently launched ELME, which stands for Event Likelihood and Metrics Estimator. Could you briefly describe how it is used?

ELME is a tool that we use at adMarketplace for pricing media placements. ELME prices the ads from different advertisers on different publishing platforms and, based on a variety of inputs and contextual signals, ELME determines the value to the advertiser for what we call a “moment of intent”.  

‍What advice would you give to young women who are considering a career in technology?

Technology was something created to make our lives better. What helps me is thinking of the end goals: what do you want to work on, what difference do you want to make, and how can you make it. 

Technology is something that enables us to create more feasible creative solutions. At the heart of it, it's always just about making something better. 

Understanding how we can use machine learning and AI tools to assist us in the workplace instead of succumbing to the false narrative that they will one day take our jobs is vital as this technology integrates more into our everyday lives. Bhumi encourages us to see how these tools can be applied to any field and why we should embrace them instead of fearing them. 

Check out more from our Women in Tech series here and discover the importance of using soft skills in tech and stepping into your confidence with Amritha!