Meena Das is the CEO of Namaste Data. A rising thought leader in nonprofit data and artificial intelligence, Meena blends storytelling with human-centric data tactics to promote an inclusive and equitable sector.
In this episode of the RKD Group: Thinkers podcast, Meena sits down to discuss how we can advance data and AI equity in the nonprofit sector. Meena shares how:
- She embraces discomfort and lets go of the need for control
- Nonprofits can center people in data to build inclusive relationships
- We can avoid negatively impacting generosity
- Owning your brilliance can drive lasting change
Show chapters
- 4:42 How she lets go of control
- 11:24 The role data plays in social equity
- 18:07 Negative impacts on generosity
- 25:12 How to own your brilliance
- 28:13 Formative life experiences
- 33:50 How she connects her personal and professional identity
Meet our guest
Transcript
Justin McCord
Welcome to RKD Group: Thinkers podcast. I'm your host, Justin McCord. This is the podcast for nonprofit marketers. It's a show about the people who influence marketing and fundraising. And unlike other shows that talk about the craft of fundraising, we focus on the people, the pioneers, the thinkers, right? And so, on today's episode, we definitely dive deep with someone who is kind of an up-and-coming thinker in the space and who's doing some incredible work. And so, Ronnie, why don't you tell us a little bit about our guest.
Ronnie Richard
Yeah, we're talking to Meena Das today. She's the CEO of Namaste Data, and she's really focused on advancing data and AI equity in the nonprofit sector. And she really goes into what that means in terms of making sure that, as data and models focus on building majorities, people don't get left behind in that.
And so, in our conversation, they're really … you get to see two sides of her personality. It's, you get that analytical data-focused side, but you also hear this, this aspirational, motivational side as she talks about her work as a life coach. And what really stood out to me was, as she takes us through her path in her career and in her life, from her time in India, to moving to the U.S., to working for some, you know, very large companies like Microsoft, and Amazon and Oracle, how that path has shaped her passion for what she does in making sure that people aren't left behind in data.
Justin McCord
You know, Ronnie, you and I, especially over the back half of last year, we talked a lot about, like, the strategy and the way that we go about crafting, curating guests for this. And at one point, you know, we were joking of, you know, that, man, this is like, what we're really about is people on purpose. Like, it's people, and it's about how they are on a mission, how they work on purpose, the things that they do to innovate on purpose.
I'm just struck by Meena's ability to crisply articulate that and believe that and act it out. And I think it's so, so cool that we get to be in this sector at this time when people like Meena are doing the work that they're doing. It's really, it's awesome.
Hey, before we get into the conversation with Meena, we are getting ever so close to our 100th episode of Group: Thinkers. And we don't take for granted one second that our listeners spend time with us. And so, I just want to ask a favor of you, if you have a moment, if you have a thumb or two, to just type a review for us. Give us a review on the area, the platform where you're listening to Group: Thinkers, whether or not that's Spotify or Apple or wherever else someone might YouTube, wherever else someone might be tuning in to the Thinkers podcast. And that helps us bring you more content just like that, just like this. So with that, here is Meena Das on RKD Group: Thinkers.
Justin McCord
Okay, Meena, we were just talking before we hit record about antsy space. And I kinda wanna just continue the conversation that we were having. Like, what does life look like for Meena when you have antsy space that you're working in?
Meena Das
That's such a good question because I have so many times when I feel, like, antsy. And I said, right before we hit the record button, that maybe the three of us here or the two of us here kind of understand this feeling as consultants, the antsy space. Because we talk to a lot of different partners, a lot of different kinds of collaborators, and there's definitely some space where we are just sitting by ourselves, at our desk, looking into our own computers. And it is uncomfortable to be in that antsy space, to not know ‘Where is this?’ Sometimes I'm waiting for some new information. Sometimes I'm waiting for a date. Sometimes I'm waiting for confirmation on the timelines, the scope of a project. And you don't know where this information is coming in.
I think … I have done a lot of self-exploration. I like to do a lot of self-exploration. Justin, I don't know if I ever told you this, but I'm also a certified life coach. So, I designed my own tools to make myself go through, why am I feeling this kind of antsy? I'm that kind of a person who used to―I'm gonna say used to―love having control. I wanted to have control. I have been always that. I'm, you know, A-grade student who wants to have control over the schedule and wants to know what's next. And I think the pandemic really opened me up to go and look deeper into that antsiness that I used to feel. Like, I cannot have control over everything. So how else can I let go other than saying to myself, you know, just be okay.
So, antsiness, how I take control of that is really just sitting with it and then opening myself up for the idea of unlearning, that there's going to be some unlearning, there's going to be some letting go, there's going to be some processes, some habits, some comfort area where I would say, I don't know that. Maybe I have done this kind of work, like, five times in the past, and I'm waiting for something. Why don't I go out in the world and talk to somebody or read something, or relearn something in the process that maybe I don't know. So I think that's how antsiness works for me now.
Justin McCord
Yeah, it's so interesting, that realization of controlling, of what you can and can't control. Like, to be able to sit and process that, and in this work that we're all involved in, with folks who are on the front lines solving the biggest problems in the world, there's a lot that we can't control. And so, you know, regularly taking inventory around that and then basing your disease, your decisions on that, I’ve found that to be a helpful practice for me, as well. And I think that I've tried to be more intentional about that practice over the course of maybe the last two, three years versus prior to that. That's so, that's so interesting.
So, with a career in research, analytics, and data, like those are very hard, skill-oriented pieces. Like, how in the world did this organizational, this philosophical approach, how did that blossom for you? Like, you've got such a unique blend of your mindsets and the way that you work with folks around their data and technology. It's so interesting to me.
Meena Das
So first of all, most days I feel in my work that I'm talking about Kale smoothie to a bunch of people who know amazing chicken burgers or beef burgers. Like, I'm talking about something healthy. Like, I'm talking about a mindset shift almost around the word data.
And so, let me go back into my story. I have worked in the space of data for almost 15, 16 years now. I've been in a lot of different companies. I've been in a lot of different industries, in tech, in nonprofit, consulting nonprofits and now doing my own thing. And just being in different spaces, being in different rooms, who asked, handed over different kinds of job description , I started to realize through the pandemic that, regardless of the job description, I’ve been doing the same thing over the years, again and again, just sitting in front of an Excel spreadsheet and trying to convert it into a chart and then sending it into a room, in a closed room mostly, where a bunch of people decide something about another group from those pretty charts.
And I―going back to that wanting more control―I wanted more control around the word ‘data.’ I started to realize and hear more consciously, intentionally around me, that most of the leaders that I had in my jobs, they always said, you know, center your customer, center your leaders, design your charts, send it out. And it didn't feel like I was doing enough to explore, what does it mean when someone who looks like me, who talks like me, has an accent, comes up on the Excel spreadsheet. What does it mean to stay on a tab in your Excel spreadsheet?
Because somebody has to have an accountability for all of those data points, because they are people. Most often in our work, they are people in our data. And it made me really explore, how do I balance who I am with what I do? How do I balance my lived and learned experiences? It was not enough for me. It started to … it just became something like an itch. Why do I not know the answer? Why do we not know the answer that if someone who talks like me shows up on Excel spreadsheet in front of me for my nonprofit clients, whose responsibility is that? What are we exactly talking about? And that made me go into this exploratory phase, almost starting within myself. How do I want to show up in data? What does it mean to live in data? What does it mean to be a data point? Because we own this responsibility. You own this responsibility as the data collector. I own this responsibility as the data point in that part of that data sheet.
And so, my work really became about, how do I enable and empower the sector that I really love, nonprofits, to take more control around the word data? Not in the sense that, here, go acquire this add-on, or go get this other tool. But really understand, how can you build a better relationship with the word data? And by that extension, now we have AI everywhere. So, by that extension, how do you build better relationships with AI? I do not want us to be just passive citizens of data being collected by big corporations. I want us, as a sector, to be people who know how to serve our communities by centering them first in the data and starting to talk about them.
And so ... You know, I don't have perfect answers, but most days, I enjoy just sitting uncomfortably with this challenge.
Ronnie Richard
Meena, I loved when you were speaking at the fundraising AI summit back in October. I remember watching your session and, first of all, I loved how, I guess, you talk about AI and data in a way that's so relatable and just, you know, some people could talk from such a high-level perspective, and it gets really intellectual. And one of the things you were just talking about was this idea of data and social equity, and how we think about data in AI, and making sure that it's not discriminating in any way and it's not―I'm trying to think of the word I'm looking for―but basically, AI will always take the majority. It'll always look at majorities of things, the majorities of whether it's the sex, or the gender, or the race or whatever and it generalizes things. And so, it's something we have to be conscious about, right? So, can you explain a little bit about that and how you're thinking about it?
Meena Das
I like to call it, Ronnie, I like to call it ‘algorithmic behavior,’ like, one of the things when I talk about this―so, giving you an example, let's say a nonprofit acquires a new AI software, a new AI solution that's supposed to segment its donors from the CRM, right? Common thing that we have seen in the industry, right? We do have a lot of solutions that segment the prospects and donors to figure out, okay, here are the five pretty lists, pretty dashboards, that you can access. Hey, fundraisers, you can access this every single day. Morning, you would get these lists of 10, 15 people, go reach out, talk to them, and this is going to make your work easier. This is going to make your work faster. As much as I appreciate this solution as a technology person myself, the place where I want us to be a little bit more intentional, a little bit more conscious is with this ... this algorithmic behavior. What it means is that ...
If you, let's say, Justin, you and Ronnie, you are two fundraisers, and you get this list. What I would want is for you to not focus on those three data points, let's say A, B, and C, which lead to that segmentation and you having those three dashboards. Because once you know what makes my life easier is getting me these three data points that go into that dashboard, and the model does its own thing and gets me this list of 10, 15 people, I can bet that you are going to get into that set of behaviors where you would prioritize collecting good quality data just for those data points A, B, and C. What happens if we miss some important data points like D and E? What happens when we are not prioritizing a data point which should be prioritized?
And when I talk about these things, I don't mean the ownership is just on the technology teams. It is, for sure. They are the developers, the designers of the product. But there has to be a very substantially powerful table, space in the table, voice of the people who are also the end users, the fundraisers.
And that's what I mean by ‘algorithmic behavior’ is when we unknowingly, unmaliciously, if that's a word, start deprioritizing the data points that more talk about our community and mostly focus on those A, B, and C constantly. So that is what I mean when you―and also, thank you so much for being part of the fundraising AI presentation. I should have started with that. Yeah. Thank you for that. And the kind words―but that is what I meant. If we are not conscious, we are always going to prioritize the majority. From a designer point of view, if I'm not conscious, I'm always going to feed in the data from who are the majority population. I'll highlight them in my charts. I'll highlight them in my dashboards. From end-user perspective, they'll start to live with this algorithmic behavior, prioritizing two or three data points. It always leads to good, clean, neat kind of outcomes.
We don't know how to comfortably sit with the outliers, with the data points that don't fit the formula, data points when our formulas feel inadequate, and we don't know what to do with those. So our defaults go to what works always, let's go with that because we have a timeline to follow. So, probably a longer way to say that we just need to be more intentional.
Justin McCord
It's really interesting because in fundraising, this is a massive overgeneralization. There is the mass-market work, and then there's the major-market work. There's appealing to large quantities of individuals, and that tends to be far more skewing towards the mode, and then there's the major gift work, the mid, major and, kind of, legacy gift work that skews towards the individual. And in both cases, I think that we have overcompensated, to your point, and not been able to advance.
And so it's interesting, Meena, what you're sharing. If we're able to add that context back in around data, not solely focus on the variables that appear the most, it can get us closer to authentically connecting with as many people as possible on a scaled level. What do you think the gap is for people of, like, getting from where we are today to getting to that connection with folks? Like, the understanding is a part of it. Is there also, are there technology gaps that people are still trying to overcome beyond the basic understanding? What do you, what do you feel like's missing?
Meena Das
Can I just say can I before answering that question, can I add a point, what we risk here when we get ...
Justin McCord
Meena, this is your time, dude. You can add whatever, like, you can do this whole, this is your show, okay? Add a point, please.
Meena Das
Getting my permission to be as nerdy as I want to be. Thank you. The risk, what we have here with this, everything that we are talking about right now, if we are not intentional, if we're not conscious―and when once we get into that question, what can we do before that?―is that we are going to impact negatively the equations we have for the word generosity. We are going to impact that. We are going to hurt people in the process. We are going to hurt the data that we are going to collect in the process. And we are going to hurt our sector in the process, whose primary job every single day is to build a good relationship with the people outside our sector, bring allies with whom we can share this vision of designing a good planet, a good work, a good world.
And so ... we are going to miss out on people. I'm not gonna use the word opportunities. I'm gonna use the word on people. We are going to miss out on people if we are not conscious and not intentional about our data. And when I say, to your question, what can we do? I'm going to say something which is probably going to sound the most basic, but I'm still going to say it. I just want us to, the first step that I want us to do is just being okay with being slow a little. We don't, why are we always in a rush to prove something to somebody when we are in no competition with somebody else? So, why are we always in this very rushy, rushy mode that we have to solve something by tonight? We have ridiculous timelines. We have no space for each other to ask questions. We have no space to be a little antsy, going back to our antsiness. We have no space to own this collective, inclusive space.
I think the first thing that we really need, which I push for when I talk about AI equity in my projects with my clients, is I want you to build inclusive spaces. When we talk about data equity, it is not enough to just think you need diverse and not just racially diverse, but diverse candidates in your data teams. That's not enough. You need to have your tables to be more inclusive.
And that means sometimes going a little slow. That means sometimes creating space for learning. That means sometimes that you are not going to hit your goals, or you might have to review from scratch how you create your goals. And I'm probably hitting some really hard points here right now, but we cannot straight talk about data and AI equity and have the best test of the benefits of these technologies just by saying that let's take a, you know, tech. certification. That's not going to be enough. We need real, inclusive places where people feel belonging enough that they start speaking up their thoughts. That's where the diversity would translate into inclusion. That's what would lead up to actions in the technology we are going to use in our companies. So probably a very high level, very basic response.
Justin McCord
Well, I think it's a response that I needed to hear about, going slow. You know, as I was sharing with you at the outset of the antsiness and my tendency to want to go fast and ‘let's go’ because the energy around going fast is, has, for me, often been more fulfilling versus the energy of going slow. But there's value, like you said, in going slow.
I have a question for you. As you were speaking a moment ago, you said something that I don't want our listeners to miss out on. And it spoke to the opportunity and necessity right now for us to be intentional about the decisions that we're making so that we don't impact the sector and so that we don't ... impact the idea of philanthropy or generosity.
Do you think we already have?
Meena Das
That we have impacted the idea of generosity?
Justin McCord
Yeah, do you think, have we already? Are we needing to now backtrack and reset, or have we already negatively impacted the idea of generosity or philanthropy based off of common practices that are in the sector today?
Meena Das
Yes.
Justin McCord
I kinda wonder if that's true. Yeah.
Meena Das
I do feel that we have the work that is in front of us, that we always talk about in our conversations, we have a lot of work to do before us. That is because we have negatively impacted generosity. We are, as a nonprofit sector, we are working with ridiculous timelines, not enough funds, with goals that―and this is probably just me saying it―with goals that we did not put enough intention and heart into. And I could be wrong, but I'm saying what I truly feel is that we could be doing a better job in setting up our goals and then measuring ourselves against it.
We have created something around us; something needs to change, something needs to break for us to be this very inclusive space. And when I say space, I mean inclusive organizations that go up to inclusive sectors. Because we can't have this conversation of AI, responsible AI, AI equity, data equity, in circles between me and you, one other person of another organization, in small rooms. And then we, when we are in, just in conferences or just in webinars … If this has to be a sector-wide supported idea that helps us in connecting with the equation of philanthropy and generosity, this has to be a conversation sector-wide. This has to be this understanding that something needs to change. We have done things in the past which have been, I'm going to use the word, inequitable in certain senses. We can do better.
I do believe very much that we are well-intentioned people. We have good hearts. We have good capabilities. We just need to remind ourselves and the people next to us that we are capable of doing better. We are capable of doing things differently and then making this a more sector-wide idea. We cannot have, we need … if I have to use, like, in three words, I want us to ‘own our brilliance.’
I want each of us to own our brilliance. And that's going to enable me to look into my power. It's going to enable you to look into your power of how can we make this idea that, how we operate with data? Because my work is with data, so I'm gonna bring back this response to data, how we operate with data. It's going to directly affect and impact the idea of generosity. I cannot compare, just by looking at somebody, their color, their accent, their hair color, eye color, to say how generous they are going to be. I cannot look at a community and say, ‘This is your idea of philanthropy. It doesn't match mine, so no, you are not generous enough.’ I don't want us to be there. I want us to own our brilliance in a way where we can go out into the community and then build allyship which is based on this brilliance.
So, don't know if I'm truly answering your question or not, but we can do better. We are well-intentioned people with good hearts. And yes, we have worked in form of what we need to do.
Justin McCord
You're 100% answering my question. Like, absolutely, yes. That's … and it's something to get fired up about. It's something to get excited about, I think.
Meena Das
I'm sure. I mean, you know, even in my own … so, I'm an entrepreneur. I run my own business, right? Namaste Data. And most days, I feel like if what I talk about―talk, you know, owning your brilliance and data and, you know, how do you build a sustainable relationship?―I want the same behaviors applicable in my own work.
So, you know, I have a very creative process of setting up my own business goals. I have a creative process of going, making myself go through self-retreats. My brain works having, like, five ideas running in my head at the same time. So I need a process to slow down, to work through my antsiness, to work through my energy. But they're all in the direction that's making me centered on my ‘Why?’ every single day. And my ‘Why?’ is every single day, the same thing. What does it mean when a person like me shows up on the Excel spreadsheet? What does it mean when a person I have never known before about their identity, they are showing up on my exoskeleton sheet. I do not want to forget them. I do not want them to feel that they do not belong. I do not want to make them feel that, you know, they do not have a space here. What can I do? And that's why it remains. That's so awesome. I think that ...
Ronnie Richard
You know, that's, that's so well said. And I think there's very much an alignment. And your thinking and our thinking, like, you know, at RKD, we put out a whole theme of ‘Quit Bad Fundraising’ last year, you know, that it was all about this. It was about quitting these, these bad practices that are harming our industry and, you know, pledging to do better.
So I'm curious. You talked about this mindset that you've developed and processes over time. What sort of formative experiences earlier in your career, in your life, got you to this point? And I'm especially curious about you. You moved from Mumbai to New York. What spurred that? You know, what, where did that, you know, talk about living in the, the antsiness of the moment, changing countries. That's a big move. Tell us a little bit about that.
Meena Das
100%. I mean, okay, so I moved from Mumbai to Florida and Florida to Seattle, and I, this is where it got interesting. I picked a place which has lizards and crocodiles, like, and I am dead, dead scared of crocodiles and lizards. Like, I remember going to my part-time jobs, and there would be, like, these tiny lizards, like, jumping near both my feet, and I would curse the city so much, like, why did I pick this place? Of all the places in this very big country.
So, I moved in early 2016 out of India. I grew up in India. My dad was in a bank, used to work in a bank and used to move throughout the country every two years. Back then there was no phone and no Facebook. So pretty much I would lose all my friends if we're going from place to place. But I think I learned through my family this idea of ... losing people in one place and then going to a new place and finding and making your new home. So, I kind of learned this being an immigrant almost because in India every city has, like, a different language, every state has a different language, it's a different culture, so you also, kind of, besides the national language, you also have to learn a little bit of the local language.
So, when I moved to the U.S., besides the lizard, every other athlete was something for me to learn from in the beginning. And then I got a job in Seattle, and I moved. I was still in tech. And I think I remember a lot of those microaggressions. Like, now I'm on it, to be honest, now I have a language for that. Now I have a word for that. I never knew there was a word like microaggression when it used to happen. When somebody would come up, I remember my first day when someone came up and said, ‘Well, hey, you know what? You work in this really big tech company. And I ... I want you to practice enough English so that you speak in a way where our clients and everybody in this big company would respond to you. So can you practice your English with us?’ And I remember being really terrified as the first job in a different country, I got terrified. That was something.
Then about four months into the job―and this is the pivotal moment that really made me everything that I do today, very much like a possible idea―four months into the job, I met an accident in the same company, and I lost my teeth. So, all my front teeth, they are implants. It changed my habits, like food habits, of what I can and cannot eat for the rest of my life. But here's the thing―and I'm pretty comfortable in talking about the high level of my accident because, right after the accident, for six months, I could not speak. For four to six months, I would say, I could not speak. It was tough. And I became part of two systems. I became part of the Washington Labor's Department, you know, where workers comping happens. And I was also, because I had this visa of a temporary worker slash student visa, I was also part of this immigration database.
Anyway, despite being part of two very significantly important databases, I was never reimbursed for any of my surgeries. And you can imagine the surgeries in the States for dental is insanely expensive. And it took me a lot of conversations with a lot of people on phones to convince them that I need to be paid for that money because I don't earn that much money. And I tried to talk to lawyers and things like that.
Long story short, that made me realize that being part of strong databases in one of the strongest countries in the world is not enough to give me powers to show up for myself. It still made me vulnerable. It still made me feel that I have no powers, I have no voice, and I need to be constantly begging in front of people to be seen.
And I refused, after I was better, I refused to accept that as part of my identity. I really wanted to own my brilliance. And I use that word more often now. I really wanted to own my brilliance, and I left my job. And I started to figure out who I am in that process. One of the things that I figured out was I speak English very well. I have two master's degrees. I have a lot of certifications from India, Europe and all over the world. And I wanted to own my privilege, my identity, my growing up, my childhood, all the things that I am; who I am. I wanted to own those things. And so that moment really became the reason for me to show up for immigrants and refugee rights and advocacy work.
So after that job, I started … a lot of my volunteering work over the weekends became just about this, just talking to immigrants in refugee communities to tell them they don't have to alter their identities, stories, backgrounds to fit into a mold, to fit into an equation. Stand out. There is no fitting in versus standing out. Just outright stand out. Own who you are. You're going to shine because there's some beauty in it. So that was my pivotal moment.
Justin McCord
You could have given me a million guesses, and that's not the route that I would have guessed. And I am so thankful to get to hear your story, Meena, and in that, much more context and see how all of those pieces have helped shape you. And it's no wonder that you stepped on screen at the Fundraising AI Global Virtual Summit and just absolutely slayed it. It's because your story is incredible, and it's unique and it's beautiful, but it's also very relatable, right? For so many individuals. And so, thank you for sharing it and sharing it with us.
I will tell you, I had a pet lizard in college. I did, I did. He was like, maybe, four-and-a-half, five inches long. His name was Archimedes. And I used to take him with me to class on certain days. I did, I did. So ...
Meena Das
No.
Ronnie Richard
Just, like, in your pocket or what?
Justin McCord
Yeah, yeah, he would, like, stay, like, I would, yeah, or like, wearing a hoodie, like in the, yeah, yeah. Archimedes is a good dude, he's a good dude.
Meena, it's, Ronnie and I love having these conversations, not just to understand, like, who someone is, and what's formed them and what helps shape their mindset, but we get the benefit of also, as we hear them, kind of drawing connections from who someone is to the work that they're doing.
And would you share a little bit about the resources that you have on your website and the workshops that you have for our listeners so that they can connect with you and start to take a first step, or the next step forward, in their journey around data equity and data good.
Meena Das
Absolutely, I would, and thank you for offering me that chance to talk about my work. So, before I get into talking about what my resources and workshops are, I want to offer two guiding values. Where are they coming from? Why do they exist about the things I'm going to talk about?
So, two things: Every collaboration, whether somebody is going to take a workshop with me, or they would be part of my newsletter list or they would become my client or not, every collaborator, I try to center their energy. I try to center meeting them, you know, where they are, trying to tell them through my resources, through the spaces I'm building that I am not coming to you as somebody who has spent years doing this, as a very happily nerdy person who loved living in her rabbit holes. I still do. That's not the entire point. The point is that I bring and build these resources from this place of what I like to call, ‘Strength-Based Experiential Co-learning,’ which means that what I'm talking about is nothing absolutely new or shocking.
Like I, for example, talk a lot about data collection. All of us have designed surveys. Have we not? Have we not collected data once in a while in our life by now in this sector? We have. So, nothing that I talk about is new. So when I say strength-based experiential co-learning, what I really mean is, I want you to be able to do that, to look into your work experience. I want you to look into your own identity and bring those strengths that you feel you have into these conversations that I am offering, into these resources that I am offering.
So don't take this as this is the once and for all; I'll use this, and everything is gonna change, kind of, change, kind of, philosophy. The other guiding value behind these resources is that I am a co-learner in this conversation. So I, you know, I build these resources, you know―I know I didn't ask this question, but I'll add that. So every newsletter, I don't know, Justin and Ronnie, you know, I have two newsletters, “Data Uncollected” and “Dear Human.” Every newsletter edition that I write―and I write a lot, I write about 2,000 words every week throughout the year―and I have this very strong philosophy that I am not going to write until I have spent two hours in learning something every Wednesday, every single Wednesday. So, my learning is very strongly tied to the products that I create.
So, with those two values, I have the workshops and the freebies on my website. Most of them are around $100,000 data equity and AI. All of them, whether somebody who's listening goes to take the workshops or the pre-beats, they have the same intention: that you can go then and talk to your team members around the word ‘data’ and how do you collect that data, and how can you center your community when you are looking at that data? What kind of actions make it ethical, equitable?
Because none of these conversations should start or end with, this is a great tool, go get a subscription to that. This is a great add-on, go get a subscription to that. The real conversations should always center around, ‘Okay, why do we need what we need? How is it going to support us? And how is it going to support our vibe?’ Which is again, building relationships with people and humans―how is it enabling that?
So all my resources, whether the workshops, whether the freebies, they have the same intention. They have a lot of questions. I like to position my role as, I'm going to be the one asking questions, you are going to be the one exploring those answers. So most of them offer a lot of questions. Generally speaking, most of the products are divided into two categories. One is data equity. So, you know, how can you be thinking about data collection, visualization?
The other kind of product falls into this artificial intelligence lens. So, the questions the leaders should be asking―or I have a workshop called “Towards Human-Centric AI”―is what does it really mean? I think the fundraising AI conference had a little bit of a taste of that. I'm starting a new cohort around this called AI Advancement Lab, which basically means, how can you take this idea of responsible AI and make it practical?
The idea of responsible AI cannot be limited just to conferences and webinars and special places, just like the conversations of DEI cannot be limited to conferences. It has to be part of the DNA of every work that we do, same as responsible AI. So AI Advancement Lab is a coaching program for making our sector move from this very task-oriented AI mindset to a sector-wide AI mindset. How do we go from making responsible AI practical for the entire sector? But yeah, those are pretty much the products.
Justin McCord
And both signing up for the newsletters and checking out the freebies and the workshops, you can find all of that at namasteydata.org. yes? By the way, where did Namaste Data, where did that come from? How did that land for you?
Meena Das
Well, so, you know, remember I asked a question to myself: How do I align my personal and professional, or my lived and learned, experiences? How do I align that? And so, I wanted a name which reflects both my personal and my professional identity. Namaste is my culture. This is how we read. This is how I have greeted so many people throughout my life, and data, I've spent so many hours and days and weekends just, you know, working on data. So they're both, kind of, my life. So I combined those two, and it became Namaste Data.
Justin McCord
Awesome. Meena, I struggle to think of someone that is more purposeful, intentional and thoughtful about their work than you. And we're so thankful that you would spend some of your time with us today talking about how you got to this place, and why you got to this place and the important work that you're doing. Thank you for that.
Meena Das
Thank you so much for having me and asking some good questions of me. Can I offer something that I'm recently practicing as part of my self-life coaching experiment? Yeah. Okay. So, I have now, I don't know if the listeners, all of them, can see or not, but I have a bookcase behind me, and on the top shelf, I have three glass jars with three post-it notes and three pens under on each glass jar.
Justin McCord
Please. Yes.
Meena Das
Now, the first jar is called Proud of Me jar. The second jar is Gratitude jar, and the third jar is Community jar. So, anybody who's listening, I want them to own their brilliance. And that happens when we start looking inwards, when we start bringing more evidence from that, yes, you are capable of owning that brilliance. So Proud of Me jar, for example, is for all those little moments when I feel like, okay, I did something good, whether I said a yes, which was a wave outside my comfort zone or a no, even if I was in my comfort zone, I go up and write down a little post-it note and leave it into that job . What I'm building there is not just reminding my body that, yeah, you are capable of being proud of yourself, but collecting evidence for it. So yeah, I want to offer that for people to own their brilliance.
Justin McCord
Their brilliance, that's awesome. Thank you for that. And yes, folks will be able to both see this and listen to it. And, Ronnie, I can already hear some folks like Max Bunch is gonna have a Proud of Me jar the next time that we see him, some of our very, very faithful listeners. So, I mean, thank you again for spending time with us. We can't wait to hear more of your work down the road.
Ronnie Richard
Absolutely.
Meena Das
Thank you, Justin. Thanks, Ronnie, for having me here.
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