Storytelling, Service & AI: Tanya Pinto's Journey

‍

Description

In this episode of The Curiosity Current, hosts Matt and Stephanie sit down with Tanya Pinto, Principal UX Researcher at Microsoft focused on Copilot AI, to explore the evolving relationship between artificial intelligence and human insight. Through the lens of both her corporate work and humanitarian efforts as founder of Baal Dan Charities, Tanya shares valuable perspectives on maintaining empathy in research, leveraging AI tools effectively, and creating space for authentic human connection in an increasingly digital world. Whether you're a researcher navigating AI integration or a leader fostering team growth, this conversation offers practical insights on balancing technological advancement with human-centered approaches.

‍

Tanya Pinto is a Principal UX Researcher at Microsoft, focusing on Copilot AI for the Office Suite, and the founder and president of Baal Dan Charities. With a background in journalism and extensive experience in branding, consumer insights, and UX research, she brings a unique perspective to understanding human behavior and decision-making. Through Baal Dan Charities, Tanya has helped provide food, education, and supplies to over 14,000 children across 14 countries, demonstrating her commitment to humanitarian work. In this episode, she shares valuable insights on AI's role in transforming workplace productivity, inclusive research practices, and the importance of maintaining human-centered approaches in an increasingly AI-driven world. Her expertise in bridging technology and human understanding, combined with her humanitarian work, offers listeners a comprehensive view of how empathy and technology can work together to create meaningful impact.

‍

If you enjoyed this episode, make sure to subscribe, rate, and review it on Apple Podcasts, Spotify, and YouTube Podcasts, instructions on how to do this are here.

‍

Transcript

Tanya Pinto:

I believe you have to keep the human at the center. And the rigor comes from bringing your worldview, your experience, your empathy, looking at things with a critical eye and applying your own analytical skills and not just trusting anything. I mean, you wouldn't go into research and just trust the words of just one respondent, right?

‍

Stephanie Vance:

Hello, fellow insight seekers. Welcome to The Curiosity Current, a podcast that's all about navigating the exciting world of market research. I'm Stephanie Vance.

‍

Matt Mahan:

And I'm Matt Mahan. Join us as we explore the ever-shifting landscape of consumer behavior and what it means for brands like yours.

‍

Stephanie:

Each episode will get swept up in the trends and challenges facing researchers today, riding the current of curiosity towards new discoveries and deeper understanding.

‍

Matt:

Along the way, we'll tap into the brains of industry leaders, decode real-world data, and explore the tech that's shaping the future of research.

‍

Stephanie:

So whether you're a seasoned pro or just getting your feet wet, we're excited to have you on board.

‍

Matt:

So with that, let's jump right in.

‍

Stephanie:

Hi, today we're excited to welcome Tanya Pinto, Principal UX Researcher at Microsoft, focused on Copilot AI for the Office Suite. Tanya is also the founder and president of Baal Dan Charities, which has helped provide food, education, and supplies to over 12,000 children around 14 countries.

‍

Matt:

Tanya's expertise spans branding, consumer insights, and UX research, shaping how AI transforms decision-making. At Microsoft, she's influencing AI-powered market research and user journey mapping.

‍

Stephanie Vance:

Today, we'll dive into how AI is shaping work, the role of inclusive insights, and Tanya's experience founding and operating Baal Dan Charities. Tanya, welcome to The Curiosity Current.

‍

Tanya:

Thank you so much.

‍

Matt:

Well, I'll get us started here. I mean, I alluded to it in the intro. You have this career that has approached what we would refer to as researchers as like social science, as the study of people from so many different angles, insights, UX, and also from this humanitarian space. I had to believe there's something connecting all of that together for you, right? What is it that originally drew you to market research, UX? How has your interest in humanitarian work played into that? Where's all this come from for you?

‍

Tanya:

Well, I think from a very young age, I think I was a journalist at heart. I always thought I would be a journalist or a reporter. I love telling stories. I love asking questions. I love talking to people. My degree, I grew up sort of all over the world. I did my degree at Curtin University in Perth, Australia, and I majored in journalism. And I saw journalism and sort of the art of asking questions and trying to get to the heart of a story is something very core to sort of what I really love doing. And I think that is the trait that has carried me through being in advertising, where you're doing a lot of storytelling and the qualitative side of advertising, which is account planning, finding out what makes people tick, what would make them gravitate towards a brand, persona development. And then the humanitarian sector, obviously, I did a lot of investigation to find out how to help children in need, how best to help them, how to develop models to where the money that U.S. donors give doesn't just go to waste, that it gets to kids, that really need it and developing systems, and then market research and UX research. And I'm loving UX research because I get to talk directly to people and conduct studies where I'm sort of just there one on one and really understanding what their experience is. So I think that's the thread.

‍

Matt:

So great. One of the things we talk about a lot at AYTM, a lot of research agencies talk about is empathy, driving empathy. And I think there's a propensity for it to feel a little bit like a buzzword, but it's so refreshing to hear that perspective. It's so refreshing to have that conversation. And just, I think it helps remind us why I think a lot of us have fallen into market research as a passion. It's just the study of people because people are weird and fascinating and endlessly surprise you. They only generate more questions. So that totally resonates.

‍

Tanya:

Absolutely.

‍

Stephanie:

Tanya, before we get into like the role of AI within the context of research, whether it be UX research or, you know, consumer insights more broadly, because you have worked on Copilot AI, I would be very curious to hear you talk about how AI is just transforming more broadly just the modern workers experience.

‍

Tanya:

Yeah, it's been absolutely amazing. And, you know, I've been at Microsoft almost eight years now, and I think it's the most significant thing that's happened in my career at Microsoft. It's just been absolutely transformative. And it's just incredible what AI can do and what Copilot can do. I mean, I think the world changed a lot when COVID happened. We, you know, I used to go to the campus every day, and now we're hybrid or we're on screens. And one of the most transformative things that I think Copilot enabled was teams meeting summaries, because a lot of us are in back-to-back calls, and then you finish the call, and there's the Copilot meeting summary with the action items. And it removed this cognitive load that I think many people didn't even know they were carrying because of the way work and the pace of meetings and screen time had changed things. And so that's been just a personal delight for me, is just definitely using that. And I think just the opportunity that Copilot has given for, you know, starting from scratch, for, you know, authoring and getting some help and coaching, changing the tone, personalizing something, the things that maybe, you know, are difficult in some ways, the written form. I think there's been a lot that Copilot has done to instill confidence and to make me feel like, oh, you know, I can push this project along. I have the tools that I need.

‍

Stephanie:

For sure. I love it that you mentioned something that reminded me of the sort of the blank page effect, right, and how clutch AI has been and sort of helping us overcome that in a lot of ways.

So now kind of moving more into the consumer insights and research and UX research space. One of the biggest challenges that we see for brands today in executing research is balancing speed and quality, right? Speed and quality. It's always going to be those two big tension points. AI is something that has come in and promised to sort of, you know, bring us that speed, right? While that's happening, how do we ensure that that acceleration doesn't come at the cost of, you know, experimental or research rigor and also deep human understanding of our research participants?

‍

Tanya:

Yeah, I think, you know, AI is a tool, just like Google or searching, you know, doing secondary research. I think these are all tools. These are things that can definitely increase efficiency and speed. But I believe you have to keep the human at the center and there has to, and the rigor comes from, you know, bringing your worldview, your experience, your empathy, looking at things with a critical eye and applying your own analytical skills and not just trusting anything. I mean, you wouldn't go into research and just trust the words of just one respondent, right? Like you would get a number of different data points. I think triangulating different data, I think using mixed methods, I think you've got to sort of check, verify, be curious. I don't think you can just rely 100% on just one thing. And having said that, there's some amazing things that are happening and amazing outputs that are high quality and truly transformative as well.

‍

Matt:

That's such a great point that, you know, this sort of traditional role of the researcher as like, you know, keeper of the knowledge, keeper of the flame is really still there. It's just that there are more tools to consider. Maybe there's more complexity to consider as well. But yet that role, like fundamentally, you know, at least in your view and in ours still very much exists. Maybe it's even more important today, like because of these AI tools.

‍

Tanya:

I think it's actually more important. I think you need that discernment, that wisdom, that lived experience, and then you can put that along with these other tools and bring a more powerful package to the problem or solution to the problems you're encountering.

‍

Matt:

Great point. You did mention at the same time, you know, taking this like trust but verify type of perspective, very wise. At the same time, you've seen things that have been, you know, delightfully surprising in terms of the outputs that AI tools have been able to create. Can you just walk us through like an example of what has really surprised you from the AI space recently?

‍

Tanya:

I think a couple of examples have been Microsoft's a global company and my humanitarian work is global. And I work with a lot of people where English is a second language. And I think that the seamlessness with which AI is enabling, you know, language translation, grammar, ensuring appropriate tone. I mean, I think these are things that are really valuable because if suddenly we had to conduct this podcast, this call, you know, speaking a language that wasn't our primary or native language, it would be really hard. And so that's been just very compelling for me to watch how it's really like brought confidence to people where English is a second language and they're using that. They're, you know, and even if it takes them a few hacks to get around, you know, copying and pasting or figuring out the translation, it's come up over and over again, actually, in the work that I've done, not just for my career, but just even with my charity work. It's just how people are using AI. And I think another example is just the delight that is experienced with creating things. So whether it's creating an image or writing a story or just doing things for fun with AI, like, you know, bring me some recipes for baking or things I haven't thought about for gluten-free baking, you know, all these things.

‍

Tanya:

The synthesis of information, the speed at which and the nuance that you can put in to really personalize the ask. Like, you know, I'm preparing a dinner and two people are gluten-free, like all these things that you can put in and you can kind of get this output that would have been very laborious and kind of taxing. I think that's been really, that's been amazing to experience personally as a user and also just watch, watch how, how it's enabled a lot of people to kind of upskill and have confidence.

‍

Matt:

I love that. I love the perspective of upskilling. And you said it a couple of times, confidence building, which is something I had never really thought about before this conversation. But like we were talking about Copilot earlier, it has like those after meeting summaries have been such an important part of like my day to day that it has taught me sort of the value of like, you know, having a little bit of rigor there while also to your point, taking a very laborious task and taking that completely off my hands. I think that like, you know, there's a lot of conversation around AI, like in general right now about like the original promise was that it's going to do all of the dirty jobs so that we can focus on the art. You know, we can do the things that bring us a lot of enjoyment. And then like recently, you know, like public sentiment, a little bit different, some concern around like, well, is this really what I want to be doing? Is this tool like really, really panning out the way we thought it to you? But I think you just shared some great examples of like how it really is when deployed, you know, with this like this empathetic, intentional, informed type of strategy, it really does become a partner that does all the things that you don't want to do and lets you do the fun things like bake your gluten-free cookies. You know, I mean, I think that's such a great point. Going back to research. Okay. So, you know, we talked about the positive side of things. Are there gaps like- If you're trying to plan a research strategy and you have these tools in your, you know, you have these AI arrows in your quiver, so to speak, but you also have your traditional methods as well. What are the gaps that you look for in your AI tools that indicate to you that, okay, this is where maybe we want to stay away from an AI-powered solution. We want to go back to the traditional human-driven approach.

‍

Tanya:

What I would just say is that I tend not to look at the gaps, but I tend to have the starting point that I can use different things for different purposes. Right? And just like, you know, you open a Word doc to maybe write something long form, but then you prepare a PowerPoint deck when you're in a meeting, you know, for presenting. I think it's just very much looking at all the tools that are available as doing sometimes very specific things. And you have to choose. You get to decide what you use when and where and to what extent. And sometimes, as we've talked about, it's a really helpful jumping off point. Get me started. If you're kind of like staring at that blank page, I don't even know where to go with this. Sometimes it's an amazing polishing tool. We just wrapped up that meeting. We did a five-hour offsite and wow, Teams, you know, Copilot made the meeting notes. That would have taken me a week to write those meetings, right? Like for a very long meeting. So I think you just have to know when to use it and play with it and see what works for your own personal workflow. And also, you know, what serves your clients, your customers to make their experience good with you too.

‍

Stephanie:

Yeah, it makes a lot of sense. I kind of want to go back to something that you both have hit on here to talk about, you know, AI as a tool. And it's, Matt, to use your words, right? It's doing our dirty work for us. And in some cases, that is true. It's not the dirty work. It's the executional work, right? Yeah. Do you have any advice, Tanya, for like how researchers, UX researchers should be redeploying their time, right? So when we think about it's going to take up the laborious stuff that maybe didn't, you know, tap into your, you know, your experience and your top skills. What, how should we be deploying that time? Where should we focus on making sure that what we're producing is the best that it can be?

‍

Tanya:

I think when it comes to the art and science of research, I think we all have sort of the phases in which we plan work. And a colleague of mine, Wes Hancher, like he came up with, you know, a UX sort of workflow of the stages that you go through from exploring the problem, to planning the research, to preparing for it and what goes into that, to recruitment, to conducting and executing the research and then reporting the insights. So that's sort of a workflow that has definite stages. And I think a good practice is to look at each stage of work and think about how you can leverage AI or choose not to. I actually would also like to say that, that AI is not only for the admin work or the dirty work, right? That you don't want to do.

It's a very powerful thing. It can synthesize, like there's big data. There's all these things that AI can do. I don't think we've even tapped the power, you know, the full extent of the power of it. But I think that it just, if I was just, you know, about to start a research study, as you plan and you look at each phase, it would be a good practice to think about how and where you could use some of the AI tools that are out there, whether, you know, whether it's a niche tool or it's something that's, you know, like that team's meeting that I keep going back to. But I think there's ways to do it and to do it intentionally is what I would like to say.

‍

Stephanie:

Yeah. So Tanya, there's also been a lot of conversation around AI democratization, right? It's democratizing insights and making it sort of within the realm and reachable for non-researchers, people like brand managers and product managers and other people who are research adjacent but did not sit in that field very directly. Overall, do you see this as like a net positive or do you see like worries about insights being misinterpreted by teams that don't have that sort of formal interpretation training somewhere in between pros and cons? Like what's your perspective on that?

‍

Tanya:

I think it's a wonderful thing if we can all get smarter and we can all learn. And I think there's definitely a different level of conversation when you come into the room where somebody has studied up on things and they have a higher order of questions to ask because they've done their research or they've used, you know, or they said, hey, I think these are the insights or I've used this tool and what do you think? So I think, again, it upskills, it up levels the conversation on both sides. I think it forces us as researchers to hone our craft and be really precise and really know, you know, really understand how we can land impact with our insights. And I think it's also actually a good relationship building tool because if, if let's say, you know, somebody is seeing something else and they've, they've, they've come to that through whether they're using their own analytical tools or AI or whatever, and, and you see something different, it makes for a great conversation, right? It makes for how do we solve this together and what are we missing? And we can all have blind spots. And I think, you know, there are things where, you know, if I've sat on hours and hours of research and I'm trying to build a story and I'm like, oh, I think the inside is this. And somebody fresh looks at that and says, oh, you know, did you realize that they were actually saying that? And it's like, oh, wow. Like you need, you know, I love multiple perspectives. I think it goes back to my roots in journalism. You never just get one source, right? So I think, I think the more sources we have, the stronger it makes us all. I think we all rise when we have more access to the tools and information and data. And I would want that democratization to continue. I've seen the power of that. I think it's, it's amazing. And I think that the AI will enable, enable, you know, people who maybe were actually also stuck in certain roles to also bring more to what they have to do, because maybe now they're not stuck just making those meeting notes. So they're able to free up time to be more creative and bring a different dimension to their work.

‍

Stephanie:

For sure. How can leaders, whether they're research leaders or product leaders, but how do they empower their teams to take this sort of cross-functional approach to, we're all bringing some expertise, we're all leveraging tools, automation, AI, to bring together that sort of holistic decision-making that you're talking about?

‍

Tanya:

I mean, I think some of the best leaders and managers I've worked for have always created a space for learning. They've always had a very intentional space that they give, you, their employee to say, you know, take X amount of time and learn something, go do that training course, or we're going to have, you know, no meeting Fridays, and that will give you space for focus time. So you can try that tool out, or you can do a little experiment. And I think when leaders do that, and don't make learning something that you have to do in your own time or after hours, and you're just struggling to keep up with everything that's out there, you know, it can change, it can change the trajectory of your whole career. And I think I've been really blessed to have a lot of wonderful leaders that have enabled growth. You know, at Microsoft, we talk a lot about growth mindset, and that notion of like, you know, I'm not an expert yet. But when you can have growth mindset, but creating space for learning, and development and training is actually, I think something the best thing a leader can do, especially in this environment where things are changing so fast. AI, I mean, the pace of technology and all these tools, everything is, it's literally changing week by week. So we need space to grow and to learn.

‍

Stephanie:

We really do. That's such a great, great call out.

‍

Matt:

So, Tanya, I want to make a quick 90 degree turn and just make sure we carve out some time for you to talk about your charity work, because it's obviously something that's been really important to you, really important to your career, but also just interpersonally. So we'd love to hear more about that.

‍

Tanya:

Yeah, so I started my charity, Baal Dan, which means to give to children or donation to children in Hindi. I started almost 20 years ago. My grandfather was an orphan. And because, you know, somebody took him and his brother and put him in school, actually, he ended up being very successful in his lifetime. He won the equivalent of an Oscar. He won a Filmfare Award in India for being a documentary filmmaker. So in my own family, you know, the cycle of poverty was broken in one generation because an orphan child got to go to school. And I think that enabling children and catching them really early in life and making sure that they have, you know, Maslow's hierarchy of needs, food, shelter, protection, education, clean water, nutrition. And it really stabilizes a child such that even if they're born in places with extreme poverty or, you know, really terrible circumstances, that those foundational years, if you can help them then, it really mitigates a lot of problems down the line. And so I had this passion for orphans, for helping children. I went and took a sabbatical from my job at the time in advertising and worked at Mother Teresa's Orphanage in Calcutta, India, and the home for the dying. It totally changed my life. And when I came back, started a 501(c)(3) and my friends and colleagues in the advertising world started, you know, donating money. And I sort of joke that I am the world's worst fundraiser. I did not know what I was doing. I didn't know anything about running a nonprofit. I've sort of held a full-time job along the way and done this on the side. But my model has never changed, which is I do a lot of research. I try to find the grassroots organizations that are working in very difficult context and helping children that are sort of missed by the larger safety nets. And a lot of these small organizations, grassroots organizations, are run by amazing women who just decided to do something in their community and say, I'm going to take in these street children or I'm going to start a program for after-school care or do something. And I raise money to help them. And because I have a full-time job and because everybody involved in the charity is a working professional, nearly 100% of every dollar that we raise goes directly to help children. And we help children with food. Every day we probably feed over 1,000 children living in orphanages and in the care of special centers. We've done everything from build wells, built lots of toilets and latrines because I'm a huge believer in good sanitation and hygiene. And we've done amazing things when there's been times of crisis. So right now, you know, and over the last year or so, the market research community has gotten together and helped raise money that have enabled us to help more than 1,200 children in Ethiopia suffering from severe malnutrition. Children who would have otherwise probably died after they'd had a critical intervention at a health clinic because conflict, climate change, and environmental factors have caused them to not have adequate food access. And so we're helping these children directly. And because I spent five years sort of consulting and doing a lot of consulting in the humanitarian space, I have some amazing contacts in that world that enable me to try to get to these organizations that you probably would never have heard of. But they're on the ground. They're helping quietly, humbly, and they're really helping children in a very impactful way.

‍

Matt:

Such incredible work. I don't even have a follow-up. If someone wants to learn more about Baal Dan, what's the best way for them to learn more about the mission and perhaps contribute?

‍

Tanya:

Yeah, find us online. We have a website, you know, baaldan.com. You can also add me on LinkedIn. I do a lot of posts about, you know, where the money goes. We have a Facebook page, Instagram page. And like I said, I think it's really been amazing to see how the research community in the last couple of years have come together to support Baal Dan. I think as researchers, you know, we want evidence. We want to know that what we're doing is working and I am no different. And so if I'm going to, you know, donate my money or I'm going to figure out like, okay, I want to help these kids. I want to know it's really making an impact. And that's really been what I've tried to do since I started this organization. And Baal Dan is not a big charity. Probably haven't heard of it maybe until this call and that's okay. But what I know is that we are making an impact. We're making a difference. And if you're going to give money, whether it's $20 or $2,000, it will actually make a difference to children who really need the help. And hopefully we'll go on to have, you know, good, stable, bright futures because they were invested in early in life.

‍

Stephanie:

And such a great example of growth mindset and action, just like we were talking about earlier. You were like, I didn't know anything about doing this, but I did it, right?

‍

Tanya:

And I'm still learning and I still don't know. And I have a lot of wonderful people advising me and guiding me and experts I tap into. And I do as much research now as I did where I'm talking to people at bigger NGOs saying, should I do this? Should I enter this territory? What's the best thing to do? Should we not do this? So yeah, I'm still learning and it's a mission. It's a calling for me and hopefully something I'll never stop doing.

‍

Stephanie:

I love that. Well, to bring us back to the wonderful world of consumer insights and research, looking to the future, this is a question that we kind of like to ask everybody who comes onto the pod. What's one under the radar AI trend that you think people maybe aren't paying enough attention to yet, but should be? And this may be another one that you can't answer.

‍

Tanya:

I don't know if it's a trend, but it's a behavior that I've just seen anecdotally. So not even in my work life, but just anecdotally is that AI as a coach. So AI being used to kind of help with skilling or, you know, reframe something and that back and forth where it's really enabling, you know, a problem to be solved. And I think that's something that's very interesting. So I don't know what to call that trend, but it's, I think it's, you know, as a teacher, as a coach, it's providing some sort of a learning and skilling that I think is very valuable. And I think people will do more with that. And I myself was just interested, just like, oh, if I wanted to learn another language, I wonder if, you know, there is an AI language learning app or something. Like, I wonder if there's going to be different ways of learning that come through because of this ability, this technology.

‍

Stephanie:

Yeah, absolutely. That's a great one.

‍

Matt:

Definitely see that. I mean, as people's trust familiarity, you know, they start to kind of like almost develop a relationship with their, you know, favorite AI Tool, chatbots, whatever it is that they're using. I could absolutely see that becoming the case. You know, you start to go, maybe not like we were talking about earlier, not just there for the dirty work, but also, you know, as a thought partner where it is maybe today for bouncing ideas off of, and it sounds like what you're saying in the future, maybe it even kind of goes beyond like the singular transaction and is able to help you again, upskill another theme that's kind of come out of today. I love that. Okay. So if you're a market research, a user experience research leader, and you are trying to make sure that your team, that your organization is staying up to date on all things, AI is doing the right things to make sure, you know, that AI is being utilized effectively and efficiently. What's the mindset change that needs to happen to do that? So maybe not specific to the tools or the planning, but what needs to happen kind of like internally in order to make best use of all of the AI tools that are available?

‍

Tanya:

I think on a personal level, it's having excitement and curiosity and understanding that you might have to change your habits or change the way you do things, you know, to enter a prompt or to go to something else instead of starting in one place. Maybe you start from a different place or source. So I think it's being open to habit change and being curious about that. And I think as we've talked about from an organizational or leadership level, it's carving out space and time very intentionally for your team to learn and to experiment. And I think that there is a lot, I want to stress this Word of experimentation or pilot testing. I think, you know, take baby steps and try something and make it okay for that. Sometimes it doesn't work.

Sometimes you might not get a good output and that needs to be safe and okay. And don't throw the whole thing away because you didn't get one, you know, one good experience because the technology is developing. It's being iterated on. It's going to be different a year from now. But I think having that mindset of, you know, I'm going to keep trying this. I'm going to carve out time to try this. And I'm going to make my organization have a culture of safety around trying new tools, trying new things, maybe failing, failing fast. You know, I think these are all things that are important and not putting so much pressure. Because there are a lot of, you know, I've encountered it. Like there are people who are still afraid of sometimes AI. There are people who don't have a comfort with doing that. And I think you've got to bring a lot of people along at their own pace.

‍

Matt:

Such great advice. Such a great point.

‍

Stephanie:

For sure. And I think part of that safety is not just about, you know, safety to fail, but also safety to know that this is not about taking your job. This is about enhancing.

‍

Tanya:

Oh, absolutely. Absolutely. We're still very much needed. I really believe that. And I think there's, like I said, it's like research, right? Like I think there's an art and science to research. You don't just, there's the human element, there's the curiosity about people and it's all, you know, and it's even in a conversation like this, it's the non-verbal cues. It's not just reading the transcript that might have been produced from the meeting. It's like what happened with our energy, our body language, our tone, you know, there's so many things that we're still very much needed for.

‍

Matt:

Fundamentals are still very much in place. Yeah.

‍

Tanya:

Absolutely. Yeah.

‍

Matt:

Well, I love it. Well, again, our conversation today was with Tanya Pinto, Principal UX Researcher at Microsoft. Tanya, thank you so much for your time. This was a great conversation. We're so glad you were able to join us today.

‍

Tanya:

Thank you so much, Matt and Stephanie. Thank you so much to the team. It's been a pleasure talking to you all.

‍

Matt:

Likewise. All right.

‍

Stephanie:

So, hey, Matt and I are going to try out a new segment this week that we're excited about called The Undercurrent. And we are both just going to each week bring to you something, whether it's an article, a theory, something we're reading, that's really just sparking a lot of interest and joy for us as consumer insights folks. So, Matt, kick us off.

‍

Matt:

Absolutely. No pressure. So something that's bringing me that sparking joy, so to speak, in my day-to-day lately is this idea that I was exposed to by a family member, actually. And it's a concept called complexity theory, which I'm sure I'm certainly not the only one in the industry that has come across it. But it is really at its core, this notion that when you are attempting to solve a problem, as many of us in the insights industry are doing, whether we're doing it for our organizations in which we sit, or we're doing it for clients on the agency side, or maybe we are trying to do it internally, like to drive organizational change, transformation, something like that. It's this notion that it's a valuable exercise to reflect. On how knowable and how controllable the various inputs and outputs in that problem are to you as the problem solver. So in other words, like you take the way a consumer insights expert would typically approach a question. They're going to want to design an experiment. That scientific method is at the core of everything. And I don't mean to say that this is a counterpoint. This is not me being contrarian to the scientific method. I think that fight I'm going to, I'm probably going to lose, but it's saying you're going to want to solve a problem by designing an experiment, coming up with the hypothesis, deciding the best way to test the variables and to capture the data. And at the end of the day, you are going to determine whether that hypothesis is accepted or rejected. And you might, you know, iterate on the experiment itself. It's this very sort of classical way of problem solving that works really well. Under certain circumstances. So complexity theory says that works well when things are knowable. And in other words, when the system you're trying to affect, when the system you're trying to understand is simple. The problem is a lot of the things we try to do. And so the reason this has been on my mind a lot lately is, you know, there has just been such a focus on all of this like large scale societal change going on with like AI and, you know, politically and just everyone feels like things are really, really chaotic. So that's one of the reasons this has been really resonating with me lately. But the crux of it is once you get to the point where, you know, you can stop yourself from immediately going down that classical scientific method approach. You stop, you pause, you look at the challenges laid out in front of you, and you acknowledge that things are not necessarily completely knowable or controllable. And what that does in turn is it encourages you to take a position of really championing true understanding and discussion. And, you know, an empathetic interchange between you and all the various people that are involved. The reason I think that this has really kind of stuck with me over the last couple of weeks and as it pertains specifically to market research is so many of us fall into research. We fall into research, as we say, out of this love for understanding people. We say empathy all the time. Sometimes it can be overused in a business context to the point where it feels like a buzzword. But to us in the insights industry, it's very, very meaningful because whether we know it or not, it is the thing that has maybe compelled us to actually pursue this as a profession. And so I really, I think that there's some interplay there. That's one of the reasons this whole idea of complexity theory has really struck with me because it has kind of challenged my notion that like, okay, yeah, the science is great. That has its place, but acknowledge that the problem you're trying to solve first might be such an unknowable, uncontrollable thing that you need to approach it for a place of empathy and understanding, which is more difficult and nebulous and, you know, maybe somewhat uncomfortable for those of us sort of trained in like the classical Western way, but it's core to us as people. And like, whether we know it or not, we're good at doing that. We're good at actually reaching out and having conversations if it's something we've prioritized. So that's kind of where my head's been at over the last couple of weeks. I know that's a lot to throw at you, but. How does that strike you? Am I crazy?

‍

Stephanie:

I like that. Does it become like a different way of a different means of knowing or is it like complimentary? Is it like we need to do that work first before we can put the experimental work within the proper context?

‍

Matt:

I would say it's more of a complimentary approach, but really it's almost like there's a lot of interplay between this concept and like mindfulness because it's first saying like, don't jump ahead to the solutioning and the challenge and all of that. It's almost like grounding yourself in the present and really just absorbing as much information, as much of the nuance that you can. I would look at that as complimenting, you know, all of these skills that we have amassed as researchers, which are still very valid. You know, there's, like I said, I'm not here to dispute the scientific method, but that's how I'm looking at it. And we'll see if it sticks with me. I'll have to keep you updated on where this philosophical exploration goes.

‍

Stephanie:

Yeah, I definitely do. I love it.

‍

Matt:

What about you? What are you nerding out about?

‍

Stephanie:

Sure. I have a timely topic this week. So last week, I went to Quirks L.A., and had a terrific time got to do a speaking session, show off some some AYTM, you know, some new new developments. And then on my way home, so I want to stress had a great time. On my way home, I was in the airport as one is and doing that thing where you walk through the bookstore and I'm a sucker for an airport bookstore book. And so I picked up this guy called Sapiens, which is by Yuval Noah Harari. This book is about 10 years old, but it was just re-released, I think, in 2024, like a 10-year edition. Started reading it on the way home and it is like the perfect compliment to something like Quirks because Quirks is so much about the business of market research, which I love. But to be able to immerse myself back in this very popular science book about what makes humans humans has been such a bomb for my soul, right? Because this really is what got me into market research is that, like you said, that deep desire to just understand people and how they work. And so it's been really fun.

‍

Matt:

Just like getting back in touch with your humanity. Maybe that's The Undercurrent of this week, right? What? Okay. So I'm curious. I have to ask you, what makes us human?

‍

Stephanie:

Well, Matt. There's such a succinct answer to that. Just kidding. But a few things that I thought were really interesting and that I think we know informally, inherently, intuitively, is that what is fire, which I loved that they just called out, right? Like taming fire, big time human skill. But the bigger one, and it's related to language, so it's not language, but it's that what language gives us is the ability to have shared imagined realities. And when I read that, my mind was just like, oh my God, of course, because really what that translates to is culture, right? Because by imagined realities, it means not concrete things, not grass, not animals, not all the tangible things that we see and can feel. But even money, I like to use that example, is a shared imagined reality, right? That's not real, and that's a very human experience. It's unique to us, and it's allowed us to, is a huge part of what's allowed us to become what we are today.

‍

Matt:

That's so interesting. Yeah. I've never really thought about it that way, but yeah. Like, like currency is a, is a construct for sure. I mean, there, there's like, there's a physical component to it, but.

‍

Stephanie:

A symbolic construct. Yeah.

‍

Matt:

Yeah. That's, and you have to, to be on the same plane as another of your species for that to actually have a true existence. That's really interesting.

But also fire, also fire. You need to be able to set things on fire.

‍

Stephanie:

Fire too. You got to have fire. I mean.

‍

Matt:

Yeah. That's fair. I love it. Well, you'll have to keep us updated on where your exploration of human reality takes you.

‍

Stephanie:

Same with complexity theory.

All right. We'll see you guys in two weeks.

‍