#IamthefutureofAI Series: Tulsi Parida

Tulsi Parida is the Global Director — Data Solutions at Visa. In this episode, Tulsi shares what compelled her to join this space, the highlights of her career journey, the types of issues in AI and the different barriers she deals with on a daily basis, and why we need more diversity in this space. Tulsi also has an inspiring message for those of you who come from non-traditional backgrounds but absolutely want to be involved in the change that we want to see in this space.

This interview is part of Women in AI Ethics (WAIE)’s “I am the future of AI” campaign launched with support from Ford Foundation and Omidyar Network to showcase multidisciplinary talent in this space by featuring career journeys and work of women as well as non-binary folks from diverse backgrounds building the future of AI. By raising awareness about the different pathways into AI and making it more accessible, this campaign aspires to inspire participation from historically underrepresented groups for a more equitable and ethical tech future.

You can listen to the podcast or read through their conversation below.

I used to work at an education technology startup in Mumbai, where our goal was to create an English language learning app from Indian languages into English to help students around the country learn how to speak English. And I was really excited about the opportunity to — have this educational opportunity available to students all over the country using technology.

But once I started working and actually seeing what was happening on the ground, it became clear to me that there was a challenge there that I’d seen in other companies as well and in other contacts, which is, we’ve gone out and created a solution without actually understanding the needs of the community.

So we were solving a problem that definitely existed. English was a way to move up in society in India for better or for worse and there were a lot of middle and low-income families who were paying a lot of money to ensure that their kids had that access to that education. They weren’t necessarily getting it through the formal structures in the school system and so this was meant to be an alternative and an add-on.

However, the app that we had built was actually so large that at the time nothing has changed since then, but at the time, a lot of the phones that were being used by these families didn’t have enough storage to even house the app, let alone then use it and do things with it beyond that.

So that was a really glaring error, but something that I think is true with a lot of tech companies is that think tech first and then community second. And so that really probed me to think further about the intersection of technology and society and how can we build technology in a way that really serves the communities in which we operate and how can we start with the right questions to get there.

I started my career as a school teacher through a program called Teach For America in the United States, in New York City. I was based in South Bronx and I taught third graders. So eight-year-olds. And it was to date the hardest job I have done, but the most rewarding and it really got me thinking about issues of equity in different classrooms and why certain classrooms have the resources they need, but others do not.

And wanting to then think about my impact beyond the 30 students in my classroom, I started looking at other ways to remain in the education sector, but having more of a broader impact and slowly they started to learn about education technology and joined a startup in New York. That was an early-stage startup at the time and started quite early on.

So my role was to help teachers and educators use the app in their classrooms, but because I was so new to the company and the company was so young, you kind of had to do a little bit of everything. And so I was helping with product testing. There wasn’t a data scientist on the team at the time and so I defacto became the kind of analytics person tracking the usage of the app.

Every time there was a board meeting, I was the one putting all of that together, just because there wasn’t anybody to do it in the early days. Eventually, you know, we’ve got a robust data science team. And that happened later, but that’s kind of probably how I got into the data side of things by chance at that startup.

And then moved on to work in India at another education technology startup. That was an English language learning app as the Director of Growth and then went to graduate school after that. So I came to the UK to Oxford where I did a dual degree course. So one was MSc in Social Science of the Internet at the Oxford Internet Institute. And the second degree was an MBA at the Oxford Saïd Business School. And that’s when I really started to look at the intersection of technology, society, and business.

When I graduated I was looking for something that would allow me to put into practice some of the things that I learned around ethics, around kind of these broader frameworks and ways of working with technology that we’re industry agnostic. So it didn’t necessarily have to go back into the education sector. And by chance, I found a really interesting job at the Data Science Lab at Visa, looking at AI data policy, which is what I started doing at Visa back in 2020. And then just a few months ago, actually I have now switched teams to a new team looking at data solutions for government clients. So that’s how I’ve gotten to where I’m at today. It’s been kind of a windy journey and not a linear path at all. And a lot of it has been just by saying yes to things and putting myself out there trying things that I didn’t necessarily have expertise in on my own before. And yeah, I wouldn’t change anything.

So I would say I probably have a non-technical background, but I’m working in a pretty technical space. And I think there is a little bit of imposter syndrome that a lot of people face when they say, Hey, I don’t actually know how to code, or I don’t do that every day. How can I work in tech?

But the reality is there are so many roles that you can have in the tech industry and the data AI industry that don’t require you to have a technical background. And in fact, I think sometimes it’s better to have that holistic perspective. Because I do think that when you’re solely working within data science or engineering, you can kind of put your blinders on to what else is going on, focus on the problem at hand, and get that work done, which is important in and of itself but you do need those people who are also thinking more broadly around, Hey, what are the ethical implications of this? Do we have any guard rails around what would happen if something goes wrong? You know, what are some consequences that we might not have thought of as a result of the use of this technology?

Those questions often come from people who are maybe perhaps more generalists or not as technical but thinking more holistically about a problem. And so I think that is something that I try to hold as an advantage rather than a disadvantage. The fact that I’m able to think a little bit more broadly, brings in my experience from say, the education sector to now I’m in financial services and payments.

There might not be synergies that you can think of immediately, but there are a lot of similar challenges that come up across different workplaces and you don’t have to have technical expertise or really focused knowledge in one particular area to still be successful. And I think the key to being successful, if you are more of a generalist is still having that curiosity and saying, you know, I don’t actually know that much about this space, but I’m going to read everything I can.

I’m going to go to all of the industry events and I’m going to sort of, you know, become that expert as much, as possible while also bringing in all of the other experiences that I’ve had before.

I think diversity is really important for business. Full stop. I think we used to be at one point having to convince senior managers and boards and things like that about why it’s important to have a diverse workforce.

I think, for the most part, we’re past that and we’re now heading into a conversation around inclusion and why it’s not just important to have a diverse workforce but to have an inclusive workforce. But I think it’s important for a variety of reasons. I mean, most of us work in companies that have an impact on people outside of the company within which we work, right? So if you work for a global brand, you have an impact on different communities all over the world. And it’s really important to get those perspectives into the room so that you are properly serving the needs of the communities in which you work. And the more voices you have in the room that represent minority groups, you can ensure that the products and solutions that you’re creating within your work are actually inclusive and can be beneficial and useful to more than just the status quo.

That’s the diversity side of things. Why it’s important to have an inclusive work culture so that people are actually empowered to bring those perspectives to the forefront? So if you just have a lot of different types of people in the room, but then the only voice that’s actually heard is the status quo then it doesn’t really matter that your workforce is diverse because it’s not inclusive and it’s not actually giving people a platform and a comfortable work environment and a safe work environment where they feel they can voice their opinions and ask the right questions and probe a little bit further. So I think not just diversity, but inclusive work environments are really important.

And especially when it comes to fields of Data and AI, because the products and solutions that we’re creating in this space have massive impact, right? Because of the innate ability of things to scale. If things go wrong in an AI-related solution that you’ve created, the challenges with that can be potentially catastrophic because the impact is so massive. And so, you know, almost as a risk mitigant it’s really important that the people in the room making those decisions are diverse and that you’ve empowered them to actually ask the right questions and probe further when needed.

So for people who come from non-traditional backgrounds and want to enter Data or AI or the tech industry, my advice would be to start finding communities that you might feel a little bit safer in to start to imagine what those potential future possibilities could look like. So for me, The 100 Women in AI Ethics group, or the various women in tech or queer in tech communities that exist both in-person and online have been an invaluable resource.

Most of the people in these groups are open to talking to anybody, whether they’re new to the industry or if they’ve been there for a while. And having those conversations can really help open up your mind as to what is out there and what those potential futures could look like for you. So I think that’s why I’m attending conferences and, you know, just making those connections can be really powerful.

Once you’re in the workplace, I think there’s an opportunity there to also help other people up. So if you have employee resource groups that are like Women in Tech or Women in Business, or if you have a pride resource group or an ethnic minorities one, having and creating that space for dialogue for others who are perhaps experiencing similar things to you is really helpful. And then from my own experience, I think when I’ve seen an opportunity come up, I’ve pushed myself to stay curious and to ask questions and to say yes to things that come my way that might not necessarily make sense in a linear fashion in terms of I would do this job and then this one, and then this one, I mean, I wouldn’t have gotten to where I am today if I had just stayed on a linear pathway, you know, completely switched industries and jobs and locations. And a lot of that has come from just having a little bit more faith in myself and saying yes to cool opportunities and having that confidence that while I may not have all the answers now and I might never have all of the answers. I know enough to ask the right questions and to be as good of a candidate as anybody else.

#IamthefutureofAI campaign is sponsored by the Ford Foundation and the Omidyar Network. You can watch this and other inspiring career stories on our YouTube channel.

Tulsi Parida is a socio-technologist with a commitment to reducing digital inequality and promoting responsible/inclusive technology. She currently works in Visa’s Government Solutions team, focused on public sector and government data products and solutions.

Prior to working at Visa, she led teams at startups working to bridge digital divides in literacy education both in the US and in India. She has completed an MSc at the Oxford Internet Institute, where she studied the implications of mobile learning technologies in emerging markets through a gender and political economy lens, and an MBA at Saïd Business school, where she focused on responsible business and impact finance/investing.