 I'm really glad and I would really want to tell that to you that I'm glad that we get to speak today on a very important topic that is you, a woman in SDM industry. So let me begin with asking you that you have an impressive background spanning my molecular biology, biotech and now focusing on healthcare and AI ethics in specific. What inspired your interest in these fields and what continues to drive your passion for improving healthcare accessibility? First of all, I want to say thank you for this opportunity in your very kind words. It is really truly my pleasure and honor to be here with you today. Going back to my experiences and my educational training and my passion. So it sort of came from a nurturing family from childhood. I was always passionate about science and so was my older sister who used to be and continues to be my role model. So I always gravitated towards science and, you know, in India, the educational structure is such that you are a science, you can move forward in a science field. So of course, you know, biology was something and chemistry that came that became a priority for me. So of course I did my bachelor's in chemistry, but I wanted to move towards biotech because my older sister was doing a PhD in microbiology. So again, getting inspired by her and moved into biotech and then molecular biology and into research in two different kinds of cancers. So science remained a calling, but, you know, as I was doing my postdoc, I was introduced to the world of scholarly communications and scholarly publishing, which as a grad student I didn't even know was a field that existed, you know. I published papers and, you know, book chapters, but I didn't know what it entailed to get it into, get it to the public. So I explored that as a career possibility and started out as a scientific editor for two journals at the American Society for Investigative Pathology and I continue to work there now as director of scientific outreach. So I think my journey has been sort of staying passionate about what I like, but stumbling upon new, you know, challenges and sort of exploring how that shapes my thinking and how that may impact the world. So in 2019, we started a new topic category for one of our journals on AI and computational pathobiology. So from all my training, I didn't know what that meant. So I took it upon myself to start going to AI based conferences with healthcare and pharma tracks. And this is way back in 2019, and it was an amazing world of innovation, but I couldn't help noticing that folks were not focusing on the ethics and regulation of AI in the healthcare domain, which to me was paramount. So essentially, since 2019, I started working with people who were working on AI ethics in different domains, especially the healthcare domain. And so that's my journey into the domain. And as I started exploring more, there were so many disparities. And like you rightly mentioned, it's come to the forefront now, you know, with the strong adoption of chat GPT and large language models like chat GPT, that people are now thinking about all the effects intended and unintended that these AI tools can have on our lives. That really impacts us as humans, the way we perceive the world, and in either bridging some gaps or enhancing disparities in the other cases. I'll stop there. Yes, yes, I think I absolutely agree with what you said. And like as the field of AI grapples with the risks of bias in algorithmic systems, let's say, so some argue for the value of diversity. Including more women creators like how you mentioned, when it comes to coding or it is supposedly and preconceived to be a male dominant area where we have a lot of engineers who are males. And at all stages of the AI life cycle, as you also mentioned in your previous answer that a lot of big names in the AI world are of males. Do you agree? Is that what really matters the most? And how exactly can gender diversity strengthen the development of ethical AI system? You've partially covered this thing in your previous segment, but then I think we could help with emphasizing a little more on that. Right, right. And so let me take a step back and let's just think about women's health, right? So till the time that I was a growing girl child, I was fine and I didn't know the struggles of having menstrual cycle, for example. And that is still different for each and every woman because not everyone experiences endometriosis and that could be very debilitating for a lot of women. And it's not accounted for in terms of, you know, if women are able to work or not, should they be getting some time off, you know, in these specific instances. So that's one example, right? Not all women have children. So not until I actually became pregnant did I realize some of the struggles and it could be different for another person. For example, if you have gestational diabetes, right? So all the procedures surrounding your pregnancy change completely. Like I still cannot attest to what may happen because thankfully I didn't suffer from gestational diabetes like some other of my friends. But that's something that I could never explain to someone who's in the drug delivery or pain management or clinical care study, right? Postpartum depression. It's real. It exists. I remember having conversations with my husband about it and unfortunately, you know, we do glorify a woman being pregnant with, you know, everything positive that comes with it. But there is a taboo about talking about what happens afterwards because essentially they're left on their own with a child to feed and take care of, right? So those are the challenges that are ignored, especially because they're not talked about in the open. Not everyone sees the same exact situation and men are completely oblivious despite the support they provide are oblivious of actually what's happening inside and outside of women's body. You know, you can think about similarly menopause, different women undergo, you know, different sets of symptoms and it doesn't last for like an hour or two. It lasts for days and weeks and months and years in certain cases, right? So now think about building any of the products, services, drugs, care regimen, or even I want to say a variety of drugs that you may need in pain management or the management of a particular disease for a particular woman. Nobody can provide or answer the questions adequately other than the women who are actually suffering from these diseases in a particular setting under a given set of interactions. And that could be very different for different women. And now we're just talking about the developed world here. Like they take this to rural settings where they may not even have access to doctors. They may not have access to transportation and the challenges change, right? So when you're building a product as an investor, as an innovator, as someone who really want to bring about a difference. Would you want to take under consideration the needs and, you know, the aspects of care, excuse me, surrounding your end user? Or would you just think this is a problem? This is the solution and this is how I'm going to go about it linearly. So I think in actual life, it's there are many complexities. And I think we can make those challenges, you know, simpler. We can decrease the complexity by taking the input of the users by taking under consideration the viewpoints of those who we want to serve. And that in my case in this, these instances would be women. Yes. Speaking of socioeconomic biases and, you know, geographical biases as well. Being an ethicist yourself, you may sometimes feel like at several structures or at several systems, ethics are literally put at a toss, right? People are potentially just aiming at going from point A to B without having to, like you mentioned earlier as well. The output is what people are more focused on without having to understand really the process that is involved in it. And again, your security, your privacy, all of these things are a little at stake, as we may say. In this scenario, what kind of ethical compliances would you envision in the future? When you're using an app, how much information do you know? You know, an AI-based app, what kind of information is that app collecting on you? Do you consent to it? Do you know how it could be used in the future? Like there's so many data breaches, even, you know, real-to-groceries. And I have been a victim of data breaches where the hackers stole the credit card information from the store. So that's something sort of beyond your controls. But we can all be aware about these incidents. We could all be spokespeople or the stakeholders at these tables where these decisions are being made, right? So let's go back to, you know, large-language models like ChatGBD, which swept the whole world, right? So what guardrails needed to be put into place before the speaking mainstream, right? They made it freely available for folks to use because the more we use these models, the more data we supply, they gain by training their models, improving their performance. So if any one of you remembers, right, when initially we were using ChatGBD, there were a lot more, you know, errors. They were like the output was not as good, but over time it's getting better. But why did that happen? Because we supplied our data sets to these models to train them. What are the big tech gonna do? They're gonna monetize these models. So of course, there are versions of ChatGBD that perform better, which we have to pay to be able to use, right? So think about these nuances, how that may affect us. Especially when we go back to the context of healthcare, because I think I have selected doctors based on the trust, the relationship I had with them. They were doctors I never wanted to see in my life because I did not trust them. But when my physician, whom I trust, uses the AI based tools for the diagnosis of the disease, for the treatment of the disease, for my betterment, they should have that kind of trust in the tools that are augmenting, you know, their abilities for me to trust them and for me to trust the healthcare ecosystem. So I think it goes back to trustworthiness, fairness, you know, when we talked about COVID-19, certain, you know, individuals are at disadvantage, but how do we make these models fair enough to be applicable to everyone's needs? So I can go down a list of, you know, principles, aspects, fundamental guardrails that we need to put forward. But I would like to encourage each one of you to start thinking about things that could become better when you're using AI, if you can think of one or two principles that you can embed in that AI tool, because we are all AI ethicists and AI would touch each one of our lives in ways we can see and in ways we have yet to envision. Like how we just mentioned that conceived as a male dominant field in itself, you've made your place into it and you also started your very own newsletter speaking of the murkiness of the whole system. It really is inspiring as a woman and also I'm sure it will help a lot of aspiring women scientists and researchers to take on AI as a field of study and then probably work toward emphasizing it and making sure that, you know, ethical compliances is enabled throughout the process. With that being said, in your opinion, what role should investments in women play in bringing women at the forefront of research in academia, especially when they're pursuing a field of study that is not generally being taken up by women? And what strengths do you think and women add on in driving progress in that particular field? Thank you, Kirish. No, I think these are some loaded questions and they're very relevant. And, you know, I mean, my mind is going in so many directions is so much I want to say. I also want to put in a thank you for putting in the plug for the newsletter. And I wanted to say on that aspect, you know, you have to bring your own tribe as a woman. There are many challenges and they're real. The things that men do or men may like to do. You know, for example, if they're setting themselves up for a promotion, when looking at men, sometimes it's like they have the potential to do that job. So they should be promoted. And looking at women, you have to first do the extra work, prove the work that you can, and then you get promoted for what you have already achieved. So that is a disparity in many cases. So when you think about, you know, what could be done to help women in a professional setting, women and allies who are men, you know, should think about these considerations. I had been in several conversations with several of my mentees who happen to be women and they say, for example, you know, I know in my own instance, when I was pregnant or when I was planning a family, certain opportunities were not presented to me because, you know, it was perceived that, you know, starting a family, I would be taking a step back from my career. Right. Thankfully, I had support systems in place that did not impact my career, but that doesn't happen with every single woman. Right. So give women the time, space, and resources, and the opportunity to make that decision for them. Do not make those decisions for them because that impedes their career development. And please do not do that. I want to go back to your question of, you know, supporting women investors and women in AI in general. So I'm also the program manager for women in AI's accelerate and raise programs. So essentially these are programs where it's put into place by an entity and organization, another not for profit called women in AI, which has many chapters across the world. So there's a global footprint. So we bring in folks who can train women to, you know, generate funds venture capital for their innovative AI products. So essentially we'll provide them with tools and resources and also help them prepare their pitch deck so they can go in the real world to get some funding for, you know, their startups. And it's very surprising and you, thank you for mentioning about the 100 women of the future. And I'm very fortunate and really, really humbled to be in this company because if you look at the other 99 women, they are doing groundbreaking work in the field of innovation. And that's just not limited to AI. It's like virtual reality or augmented reality. So I think everyone, each human has the basic ability to be intuitive. They have the ability to be creative. In addition to that, you know, we tend to be caregivers. So we come women come with a lot of empathy. They come with a lot of energy to support the team. So the reason why you may see a lot more men in leadership is because, you know, sometimes they could be dominating, commanding, dictating, directing, but women try to bring the whole tribe together. So when you're thinking of a woman leader, they will be working in capacities to elevate the entire team, not just highlight their individual contributions, which will let them, you know, get on top. And a very recent example, you know, I was in conversation with three great women leaders and they have the ability to continue in that position for another year or give somebody else a chance to come in. And each one of them to me said that and they provided arguments why the other two should stay and one of them should take a backseat so that we can serve the need of the team, the community and the organization that they were serving. And the only one thing I said to them, think about what a man would have done. Right. So you have to start thinking about your own interests at time to because, you know, so my doctor told me this and I'm now an airplane mom so they essentially tell you to put your mask first so you can support the people around you it could be your children so we have that natural tendency to first help people around us before helping us. But think about this, put your mask on first, because you're not just going to elevate yourself, which I know you don't want to do or both about, but you're going to elevate the whole tribe, you're going to elevate your whole team, you're going to elevate your whole organization. And that's needed. Again, I think we circle back to women inspiring women and women building women with these thoughts coming in place. And I think we are running out of time at the moment and it's been an amazing talk so far. Is there anything I did not ask but you think aspiring women scholars especially and researchers definitely would want answers to just one thing. Because you covered more ground than I would have imagined. But one thing that I'm passionate about and I always say to everyone, dream big, you know, and don't be scared to share your dream with the world. You are what we believe is what we achieve is what you know I heard from someone and I agree to it don't let someone else tell you what you can and cannot do. It has happened in my own life when you know I had passions I had dreams and I talked to some people who said no you've achieved enough or why would you want to transition or why would you want to do this now this is going to take you to a whole different level. They discourage me but be true to yourself, you know, if you think about something you believe in something you can achieve it so go after that don't let yourself or anybody else hold you back because you can achieve what you believe in. Absolutely as you said and on that note I think a very strong closing statement that I would like to get from this is that don't let anybody confine you to the limits that they think is what you are built on or what you can strive with. If you decide on what you want to do the sky is the limit.