Tell me about your tryst with AI and programming 

I fell in love with programming the first time I drew a line on GW Basic. I started making products at the age of 15, the first being my own Minesweeper as a Java Applet. I pursued coding for 20 different applications for startups, including a fitness app to track body movements using a Kinect and an app for India's first digital microscope Cilika. Coding applications, made me realise the importance of designing end-to-end customer experiences. This led me to a deep dive into Human Centered Design, better known as “Design Thinking” for over 3 years. I have extensively researched, prototyped and tested products and services for mid to large sized companies. During this time, I also tried my hand at founding an edtech startup. Currently I am heading the product team of Augnito, which is India’s first voice-based artificial intelligence for healthcare professionals. My primary focus is to build “Systems of Scale” for design & development that would allow for rapid expansion in the India, UK and UAE markets.

Why do you think voice is the future of conversational AI? 

Language is ergonomic and natural, it's what elevates us from other beings. To be able to teach AI shared intelligence is what voice provides and this is very exciting for me. Augnito is building one of the most accurate voice AI platforms for healthcare today. My team and I spend most of our time into decoding the various situations and environments within which conversations take place, and build context for the machine. Just a conversation between a doctor and patient contains multiple nuances, accents, dialects, enunciations, acroynms that need to be understood closely. Another exciting feature we're building is enabling the machine to understand the primary voices of doctors and their patients, over background noise and other multi-party conversations in the background. This is especially useful in low-resource settings that lack the privacy and luxury of private hospitals and clinics. 

What challenges do women face in the field of tech? Is the perception of the field being male-dominated finally changing?

The way I see it, the biggest challenge women face in technology is not our gender but the fact that we're a minority. This is a systemic issue that traces its roots back to classrooms. Girls pursuing STEM are still a fraction compared to boys. Unless this funnel gets balanced, the output is going to be skewed in favour of men and we will be in a perpetual cycle of under-representation that spills into the tech we're building. We can keep advising girls to be bold and daring, and girls these days are very enterprising because the numbers are almost always against them so they have to work doubly hard to be heard and seen. But without more of our kind to collaborate with, integrate with and learn from, the numbers will dwindle further. While the representation is definitely better than a decade or so ago, more needs to be done. 

What limits women from advancing careers in tech? 

It begins with first acknowledging that inclusion is the bigger challenge. While organisations are doing better at projecting and enforcing gender neutrality, this doesn't necessarily translate into inclusivity. Taking a step back on account of childbirth, child care or elder care should not be seen as a disadvantage. Instead, workplaces must factor these milestones and life events for women, not use them deprive these women of hard-earned opportunities. Otherwise, we're falling back into another perpetual cycle of under-representation, and this time at a mid to senior level. 

Are startups becoming more inclusive? 

Yes they are. The onus of inclusivity falls squarely on founders. Diversity within leadership is critical as this ethos reflects across the board, and embodies the culture of the organisation. Especially in the business of AI, we need to look at building gender-neutral intelligence so that kind of thinking has to emerge from everyone you work with. 

What ails AI today? 

Gender biases have taken societies centuries to overcome, and yet we see lacunae in developing societies. With the advent and rapid proliferation of AI, these biases are making their way into technologies as well and this according to me is one of the biggest challenges AI practitioners have to work on removing. Unless these biases are addressed in the primordial stages, it will be very hard to reign in later.