Podcast

Full Episode Transcript:

Hi, and welcome to hello, Human. A podcast to explore ideas and feature humans working in AI and Technology.

John: Preeti Adhikary from Yale University who serves as the Tsai CITY External Partnership Associate and an adviser to the Women in AI Think Tank here in the United States. Join us today on the hello, Human podcast, where we discussed the latest topics in artificial intelligence and how it’s being applied in the real world. I’m John Knisley the host of hello, Human and a longtime consultant focused on helping companies adopt and prosper with emerging technologies. 

A big thanks to FortressIQ for sponsoring the program and be sure to subscribe wherever you listen to podcasts. This episode is part of a series on women in AI that we are very excited about here at Fortress IQ. Elizabeth Mitelman from our marketing team, who’s been driving the program, is participating in this session as well. On this episode we’re going to explore leveraging technology for social impact. When you talk with people about the role of AI on humanity and society, people tend to fall into two camps. You either have this Hollywood dystopian view that the robots are going to destroy the universe and take everyone’s job, or a more utopian view that the technology will make life better and lead to a more prosperous future and let people do more meaningful work. That’s the angle that we are going to explore today. 

Welcome to the program, Preeti. Thank you for joining us on hello, Human and participating in our Women in AI series. I mentioned your association with Yale Tsai CITY. The CITY there stands for Center for Innovative Technology. It’s supported by Joe Tsai of Alibaba fame and owner of the Brooklyn Nets as well, and a major supporter of the Yale lacrosse program, that I know he’s very proud of. You’re also an advisor to the Women in AI group as well. Both those organizations run some very unique programs. Maybe to start you could give our listeners some background on them and how they’re working to leverage technology for the greater social good? 

Preeti: Sure. Thanks, John. Great to be here. In terms of Tsai CITY, it’s the Tsai Center for Innovative Thinking at Yale and it has this big audacious mission. It’s to inspire Yale students to use innovative ways to solve real world problems. They run a long list of programs anywhere from incubations, accelerators, they provide mentorship, funding. They provide a lot of workshops, amazing, amazing things. For me, one of the reasons I actually enrolled in Yale for my Master of Advanced Management Degree, was because of its strong focus on business. They create business leaders for business and society, that’s something I really relate to. 

For Tsai CITY,  a program I helped run. It’s called Innovation from the Inside. What it is, is like a 5–6 week program where we bring a cohort of students, about 75. Not just from Yale, but all over the world. 30 different Global Schools. We bring them together to have this discussion around innovation and what that means. When we typically think about innovation, we always think of startups and how disruptive they are, how agile they are and so on. We don’t really think about bigger companies, corporations as innovative. We’re trying to change all of that mindset. 

Just to give you an example of the one we ran in the fall, it was about Corporate Innovation. Talking about how you can change your mindset, how you can create that support system and bring your vision to life. We had amazing leaders from around the world. Some examples are Jim Snabe from Siemens, we had […] from Time Magazine. They joined to really bring these ideas to life, really add value to students from their life experiences. 

What people think is we can change people’s perspective, change the perspective of these students. When they’re choosing their career path if they’re not really thinking about starting like being an entrepreneur or joining a startup, we still want them to know that there is innovation everywhere in the world. This term we’re starting one which is called Public-Private Partnerships. Again, it focuses on that innovation that we can really infuse in government entities, nonprofits, and whatnot. That’s really, really exciting in terms of having those discussions, and having a lot of ideas spin off as a result of that.

In terms of Women in AI, one of the reasons I got involved was because I’m super, super passionate about two things. AI—that’s one of the reasons I’m here, and two is Women Empowerment. That nonprofit actually fuses it together. Where we believe that women are not represented or do not participate in the AI sector, overall. We’re trying to change that. It’s a volunteer run organization. One of the things we’re doing is, this March actually, we’re launching this, almost like an Incubation Program. Which is called Why Accelerate. Which brings a cohort of about 40 startups, led by women, or started by, founded by women. We’re trying to help them from idea generation all the way to investment.

For me, the ways I’m involved in that particular nonprofit, is as the lead for Speaker Outreach and Investor Relations. I personally think they’re one of the most important aspects. Because there are so many, you guys know this right? There are so many amazing women leaders in AI. When we see these panels for events, so many times they’re just in a float, they’re just nanos, there’s only one woman there. There’s just the woman, it’s just a moderator, or something like that. That needs to change. 

We’re trying to be really intentional. For me that’s an amazing way to bring these inspiring leaders and motivate our cohort, by having these inspiring women there. Again, in terms of investors as well. If money flows into startups that are started by, that are run by women, then that ecosystem is going to change and there is going to be, hopefully more women being part of this. That’s my hope. 

John: That’s great, Preeti. Thank you for that introduction. We’ll be sure to put the links to the Tsai CITY and Women in AI in the show notes for this episode, so people get easy access to them. Going back to that idea of the different ways to get involved and contribute to this idea of using technology to build a better tomorrow. Like myself, you’ve had a bit of a nonlinear career path that ultimately led you into AI. I think you started in some operational roles and things like that. How did you find your way in AI? What lessons can you share from that journey for other young professionals that are earlier in their career? 

Preeti: Sure. I feel like we probably need an entire day to go through my super nonlinear path, but I’ll just give a gist. My undergrad was in Economics, my MBA was in Finance and Strategy. In terms of the roles, I’ve worked in banking, nonprofits, energy, and whatnot. I’ve worked in Singapore, Canada, Nepal, and the US. It’s been a lot of different things that I’ve explored. In terms of Fusemachines, I joined them in 2016 because they needed somebody to run their operations, to help them expand to different locations. That’s where my global outlook more than anything else came into play. I did that for a bit.

In any company, we’re all trying to sell something, market something, and so on. Marketing almost seemed like a natural progression. Just because I was also leading the social mission of the company. That’s how I migrated into it. I completely loved it. In terms of my advice, one is not to look at things as silos. Think of your career as a set of almost interdependent skills. It’s about transferable skills that you can bring to the table. I mean there is obviously a lot of value in having domain expertise, and spending a lot of years on that. There’s a lot of value you can bring by your creativity, by thinking outside the box, and so on. 

Just to give an example. From my background, I also understand the challenges that different industries face. For example in banking, I do understand how maybe chatbots or OCR’s might be able to expedite a lot of progress in and benefit the people. 

John: All right, Preeti. That’s great. Thank you so much. Obviously you’ve had a nonlinear career path and also a very international global one as well. Which is always interesting and I think helpful, and will become more and more the norm for everybody. I think you sort of illustrated another piece that’s interesting in that background as well. There’s this large misconception about the need to be technical in AI. Obviously, yourself, like me, don’t come from that sort of hard core programming coding background. Can you share how your career path has been able to sort of break that misconception? Would you be able to share any benefits as well as the challenges of being less technical in the industry? 

Preeti: Sure. When people think of AI, they think of people that have studied a lot of years in computer science or math—that they all have PhDs. I mean those are integral things and a lot of people in the AI space have those backgrounds. But I feel like there are tons of roles for intermediaries, like you and me. Where we sit between these technical people and the users, the consumers. There’s so much value that non-technical people bring. Not just in terms of translation of the jargons so to speak, but in terms of the creativity, the connections. Because at the end of it, the people that buy your product or your service, they’re humans, They’re not just buying that feature, they’re buying a solution for the problem they’re facing. They’re not just investing in a company based on the data, they love this, they love the story of the company. 

People like us, we’re the storytellers in a way, we’re the people that are showcasing that human side of even a product, or a service, or anything like that. Even when we talk about publications or PR in general, they’re not just trying to feature another AI company. They’re trying to feature one that’s disrupting the company, that’s impacting business or society, and so on. If you like that’s where our place is, in terms of storytellers, in terms of connectors, in terms of these community builders. 

Because AI has this impact on such a big level. I feel like there is a place for all kinds of degrees, and educational experience, and general backgrounds. For example, there’s so much talk about ethics in AI. A lot of importance for linguists, social scientists, marketers, that bring that diversity, not just in terms of backgrounds, but life experiences and expertise. Because what that means is, the AI we build as a company, as a society is inclusive. In terms of the challenges, I do think that there are certain challenges of not being too technical. Which means that some of the conversations are really deep into the math of an algorithm, or the code behind the algorithms, and so on. 

In terms of my advice, understanding where you need the help of a technical person. To reach out, and augment your expertise with theirs. For example, just an example. My marketing team, they work really closely with the technical people on our team. Because we need to make sure that the messaging we are sending out, especially if it’s related to a technical audience, we wanted to make sure that it’s hitting the right notes. The language that I understand versus the language that, problems you’re very technical CTO needs to hear, is very different. 

My advice in general is to not have silos even within a company, but really work closely with, so that technical and non-technical people are really integrated. 

Elizabeth: Really great to hear. Thank you so much. Preeti, you shared some meaningful projects you have worked on in various third world countries, including creating a fellowship and working with young students. Would you be able to share a bit more about the combination of social justice and AI within those projects and initiatives? Why did you decide to prioritize these projects within your career?

Preeti: Sure. Thanks, Elizabeth. Fusemachines is basically a for-profit entity, it’s a startup, based in New York City. It has this mission of democratizing Artificial Intelligence. Started by Dr. Sameer Maskey who teaches Machine Learning at Columbia University in New York. Basically, we started this fellowship program that teaches AI to deserving students in underrepresented communities all around the world. We used the Micro Masters Course at Columbia EdX. We use that to actually spread AI education all over the world, from New York City, Nepal, Burkina Faso, Dominican Republic, Kigali, all kinds of places. 

For me, I was really involved in all phases of that particular fellowship. From actually selecting these students to implementation of the program in all these different cities. I have a special connection I feel to this particular program and the students that went through it. Some of the people are still in touch with me. From the cohort in New York, we actually had people that went on to get jobs at IBM, and Facebook, and so on, which is incredible. 

That in itself really speaks for not just their hard work and caliber, but the belief that people need opportunities. People need opportunities, they need support, and they need mentorship to be successful. That’s the basic belief behind the fellowship. The fact that AI is, especially more than any other technology, so to speak, that we know of. It has that impact and if we can provide that, we can package mentorship and the support, maybe even the tools, we can really create an impact all over the world.

For me, one of the reasons I actually loved being a part of that and one of the reasons I actually led that is, because I am originally from Nepal. Being from a developing country like that, I understand the challenges and the benefits. Countries like that, if they have knowledge and they can adopt AI, you can really empower and enable people to do amazing things. 

During my visits back home, I would judge some pitch competitions and I would sometimes coach these people. I would just be amazed at the solutions that the students were proposing to solve problems that they’re facing around them. They’re using the local context and they’re using the expertise that they’re getting, the knowledge that they’re gaining, to solve issues around them. I feel like that’s tech for good or AI for good in that sense, is like the best thing that can happen with this technology. 

Elizabeth: Wow. It’s amazing to hear your involvement in these meaningful projects where you’ve been able to provide support, mentorship, and opportunities to help those from underrepresented communities and even your own community. That’s truly amazing. You should be very proud of your work. When thinking about the use of AI in our daily lives and tasks, we also see the challenges of AI with disparity and access, gender, and of course, underrepresented communities. Would you be able to share how you have conquered and addressed those challenges within your career? 

Preeti: Sure. One is really thinking about the ways you can bring value. Not just in terms of how you don’t really match up in terms of the technical expertise, but what extra factor you can bring. For example, one of the things I did during my time at Fusemachines was actually I started this almost like an interview series on LinkedIn that focused on CTOs. It was part of almost like a really creative way to connect with CTOs. Also happened to be our target audience, and really engaging with them, and so on.

The reason I bring that up is you can, even when you’re not the smartest person in the room or the expert in the room about AI, there’s so much value you can bring in terms of maybe looking at issues and finding new ways of solving them. 

One of the few things that I also enjoyed last year was I worked for an investment bank for a few months. I was the AI lead on that particular team and really helped source deals and look at founders that are building AI companies and so on. The one thing I loved was, you can see how AI is making an impact. Startups in the AI space aren’t just limited to Fintech or something like that, they are AI Startups coming out to Retail, Legal, and Pharma and Education, and Recruiting, and whatnot. There are so many opportunities and people that also have an expertise in a particular domain. For example Retail or something like that. They can also contribute to the AI Economy by building something using their core knowledge. 

On a personal note, I love that there is now a lot of conversation happening around ethics, bias, and privacy. These are huge issues. I love that we’re actually talking about it. We’re talking about how companies should be really intentional in terms of how they collect data, what they collect, how they monetize it. We’re having these conversations about having standards for policies. I love that we talk about surveillance and what that means for the privacy of individuals, groups and so on. I love that there are so many women. I love Kate Crawford, Renée Cummings, Kate Butterfield, leading these conversations. 

For me, there are obviously a few challenges in terms of not enough representation. But how you change that is trying to be part of the conversation. Women in AI, again, like I mentioned earlier are trying to change that as well by showcasing these women leaders, women founders, women investors and so on. 

John: That’s great, Preeti. You’ve had this wealth of experiences in your life and seen a lot of different opportunities from the investment side as well. I love that idea of this can go beyond just Fintech, different industries, and sectors and things like that. From a humanity and society perspective, what do you see as the top opportunities in AI. What gets you excited about the potential for AI to make that change and have that social impact?

Pretti: One thing I love and it’s not really tied to a particular industry is I love that people are thinking of using AI not just in terms of how they can build a good product and really have a lot of profits. But they’re also thinking of using AI for helping humanity. Just as an example with Fusemachines, one of the things we had done earlier a few years ago, the students there, the people on our team actually built a drone that could carry medicines and blood, and drop it off to remote parts of the country. We did some tests and so on. 

There are companies and Africa and so on that are doing something similar. There are companies that are thinking of working on climate change, food systems and so on. For me, instead of a particular company that is doing something, it’s just this whole mindset that we can, especially as entrepreneurs or people, I feel like there are two categories of people. There are either founders that actually start things. And there are these joiners, people like us that want to belong somewhere and do some purpose driven work. 

I love that the focus now is more towards that. You could be earning a lot of money, making profits and so on. But there is that focus now. People want a strong mission. That’s something that attracts talent as well. I love the fact that you’re thinking in that sense in terms of building something that obviously helps people but will actually help the world as well. 

John: Yeah, that’s great. I love that idea of just social mission being embedded into the product. I think overall, a lot of these technologies, I used to do a lot of work on the RPA side of AI and Intelligent Automation. Some people are like, the robots are going to take all the jobs. But we always looked at it as we’re getting rid of menial, low value tasks that are so time consuming for people that were letting them focus on work that is more productive and provides a better outcome and can really drive more valuable work to society and to humanity in general. 

I think you always gotta look at both sides of it. If you want to be successful in leveraging technology to really drive social impact, can you share some best practices to increase the likelihood of success?

Preeti: Sure. There’s obviously a laundry list of things you can do correctly. But I’ll hone in on two. One is managing or even figuring out who the stakeholders are and that’s actually super, super important. These people are people that are directly affecting the decision of building something, implementing something, or they could be users, they could be the government, a lot of different things. Really mapping out your proposal or your project, what that means for all the stakeholders. Not just in terms of how they benefit or how they will be harmful, also in terms of their accountability. 

When we’re trying to deliver a social impact project, what role does the government have or what role does a community there have. Really, with the accountability, figuring out what might be the resources for each particular stakeholder and really leveraging that. One of the big reasons a lot of projects also fail is because there isn’t a lot of buy in from all stakeholders. We see that even in terms of a different product where the decision is made at the top and then it’s rolled out and there isn’t a lot of change management happening. The people that actually probably didn’t have a say in terms of which software is what or something like that, they’re the ones that are trying to use it, they don’t understand it and so on. 

In the same way, with any project, I feel like there has to be that cascading effect in terms of responsibility in terms of guidance and also in terms of that communication flow. Next, it’s related to this, is having the right expectations. How are you measuring success? In so many cases, it’s not super defined. There needs to be a qualitative as well as quantitative analysis done in terms of any project, any pilot. That’s where communication is important. 

For me, those are super, super important. Actually, in terms of due diligence, you really think about the complete picture in terms of stakeholders. But external as well as internal, have everybody aligned in terms of not just getting buy in but in terms of the expectations from it and having that communication. For me, being a martketer especially, I think communication within an organization overall is super important. I feel like there should be over communication especially when you’re thinking about these kinds of things. 

John: I think that also goes back to some of your earlier points around these advantages to coming to it from a nontechnical background. Sometimes I’ve been involved in situations where the engineers and the machine learning folks will sit there, they could argue for weeks over algorithm changes that increase model accuracy by 0.2%, 0.3%. As the nontechnical business guy, you’re like, hang on, yes those changes are important. But if we can get this to market faster, those advantages of a portion of a percent almost get lost in the noise. We can come in with this perspective of here’s the mission we’re trying to get to and let’s try to get there as quickly as possible without sacrificing the technology element of it.

Preeti: There’s always this element of balance between speed versus quality or how complete it is. But there’s always that balance you need to have. It’s not a one time decision in any case. It’s sort of this dance between the stakeholders that needs to happen all the time in a way. 

Elizabeth: Thank you Preeti for that great advice, especially about measuring success and the various ways to do so. On the theme for our special series, you’ve involved yourself in various women in AI initiatives. How do you encourage other women to be part of the ecosystem and create more visibility within the space?

Preeti: Sure. One of the things is having a learner’s mindset. Basically meaning that you understand that you’re a work in progress and that you don’t have all the answers. I think one of the things women especially face, and this happens irrespective of our age or the phase of our career, is having an impostor’s syndrome. Where we’re questioning ourselves whether we’re technical or nontechnical and so on. 

One of the biggest ways to tackle that is to challenge it every day. For me, it’s about learning from people you aspire to be like. You’re working harder and smarter than anybody else in the networking, voluntary, mentoring. One big thing I think is amazing is also asking questions. If you’re a non-technical person in the room and you’re surrounded by technical people, which can happen, instead of feeling like oh my God, my questions are the dumbest in the world, you’re benefiting yourself and the organization by being brave enough to ask those questions and you improve yourself in that way. 

With women in AI as well, that’s what we’re trying to do. It’s a group of volunteers. I forget the exact count, but everybody is volunteering their time and all incredible women. They’re, again, at different levels of their career and so on. One of the things to change the narrative is to take action. The action can be as small as asking a question or it can be as big as being part of something that is disrupting the status quo. 

My advice is basically figure out what you can do, how you can change, how you can be a part of the conversation. 

Elizabeth: You highlighted the idea of being curious and asking questions, which I think is really great advice especially for someone with a nontechnical background. For the next generation of women in AI and tech leaders, what advice can you share?

Preeti: There’s a lot. Number one is don’t discount the AI industry because you have a particular skill set or you don’t. Especially if you’re non technical, there are tons of roles, tons of companies doing amazing stuff and you can find your place within this ecosystem. Number one is not to dismiss AI as something that’s just a man for a math and computer science expert. 

Two, again, just being open to learning. Having that learner’s mindset overall, I think is super, super important. Trying to improve yourself whether that means by seeking out mentors, by trying to volunteer, or trying to learn new skill sets. It’s about that constant drive in a way. I think that’s the best way. And in terms of being a woman in the industry, there are obviously situations where you’re the only woman in the room. But I recently was listening to some leaders talking about this and they said that in the end, it’s the fact that you, at the table, means that you have that merit as well. It’s also a lot about being confident in what you bring to the table and showcasing that to the world instead of any perceived weaknesses you might have. 

John: That’s great insight and a great point to end on. To recap today’s conversation with Preeti Adhikary from Yale University and at Tsai CITY and the Women in AI Think tank, leveraging technology for social impact sounds so obvious but there’s a lot of people who focus on the potential dark side of technology’s impact on humanity and society. In the fast paced world of technology, there are many ways to leverage AI and technology for social good. It’s critical to address the misconceptions and challenges to be successful. Learning how to use those challenges as a motivator can create strong passion for corporate social responsibility and social justice initiatives.

At the end of the day, visibility and awareness of these issues and how to address this is how we can use technology and AI for the greater good. This episode has been part of our special series on Women in AI. A big thanks to Elizabeth Mitelman for organizing this series and joining the session today. That’s a wrap on today’s show. Thank you Preeti for joining us and FortressIQ for sponsoring. I’m John Knisley and this has been hello, Human. 

Preeti: Thank you guys.

If you enjoyed this session, subscribe and check out our series at fortressiq.com/podcast. Thanks for joining us today on hello, Human.