#161 AI Strategies for Sustained Philanthropic Support with Nathan Chappell, Author of “The Generosity Crisis” and Founder of Fundraising.AI

ai benefits donors new nonprofit philanthropy Dec 31, 2023

Nathan Chappell joins us to explore the transformative potential of AI to broaden opportunities for donors and nonprofits. Nathan and Sybil also address possible downsides for AI involvement in connecting donors to nonprofits.

Episode Highlights:

  • Examining benefits and challenges of AI in philanthropy.
  • Effective methodologies for donors to discover and engage with nonprofit organizations using AI as a potential tool for good.

 

Nathan Chappell Bio:

As a thought leader, public speaker, author, and AI inventor, Nathan is one of the world’s foremost experts on the intersection of Artificial Intelligence and generosity. His recently published award-winning book, The Generosity Crisis: the Case for Radical Connection to Solve Humanity’s Greatest Challenges, has been dubbed “Required reading for our generation of professionals in the nonprofit sector” by NonProfit Pro. 

Nathan is the founder of Fundraising.AI, a 2,000+ member initiative responsible for publishing the world's first Framework for Responsible AI for Fundraising. 

Nathan's fundraising experience spans more than two decades, where he led large-scale fundraising programs and multi-billion campaigns. As Senior Vice President of DonorSearch AI, Nathan currently leads Artificial Intelligence deployments for many of the nation’s top charities. Nathan’s subject matter expertise is featured regularly on podcasts and publications, including Forbes, Fast Company, Future Forward, The Chronicle of Philanthropy, and many nonprofit associations. 

Nathan is an advisor for the AI for Good Foundation, the OpenAI Users Forum, and the Forbes Technology Council. 

He holds a Masters in Nonprofit Administration from University of Notre Dame, an MBA from University of Redlands, a certificate in International Economics from University of Cambridge, a certificate in Artificial Intelligence from MIT, and a certificate in Philanthropic Psychology from the Institute of Sustainable Philanthropy.

Links:

 

If you enjoyed this episode, listen to these as well:

https://www.doyourgood.com/blog/156-Supporting-the-Places-that-Rejuvenate-You-with-Dana-Okano

https://www.doyourgood.com/blog/157-Be-a-Considerate-Thoughtful-Visitor-with-Eric-Co

https://www.doyourgood.com/blog/153-An-Amazing-Twist-on-Donor-Advised-Funds 

 

Crack the Code: Sybil’s Successful Guide to Philanthropy

Become even better at what you do as Sybil teaches you the strategies and tools you’ll need to avoid mistakes and make a career out of philanthropy.

Sybil offers resources including free mini-course videos, templates, checklists, and words of advice summarized in easy to review pdfs.    

 

Check out Sybil’s website with all the latest opportunities to learn from Sybil at https://www.doyourgood.com

Connect with Do Your Good

Would you like to talk with Sybil directly?

Send in your inquiries through her website https://www.doyourgood.com/ or you can email her directly at [email protected].

 

FULL TRANSCRIPT:

Nathan, I am so happy to talk to you today. I've just… I'm so interested in what you have to say. You wrote a book on how AI - artificial intelligence can help us in the donor world and help us be more effective in giving strategies. And I just love that you're connecting AI to philanthropy and doing good in the world. Please, please, please, let's just talk about this. And I would be grateful if you could add your words of wisdom to my listeners. 

Before we go there, though, can you talk to me about your inspiration? What was your life journey like? Why did you decide to end up working in this really interesting space?

Yeah. Thanks so much for having me. It's a pleasure to be here. Someone asked me this question the other day, and it made me think back about how, you know, there's no coincidence in life. Everything happens for a reason. You know, at a younger age, I grew up in a single-parent household, kind of a classic scenario of a single-parent household. I learned my work ethic from my mom, who worked three jobs.

So, my sister and I kind of had to take care of the house and do things like that. But you know, throughout that time, you know, we, as children, wouldn’t say that we were food insecure, but we were… There, you know, we went... I guess we were probably because we were in the food line at the food bank. And at Christmas, we'd be in line, you know, to get presents, you know, as children, which I still distinctly remember. But I was never identified as that at the time. That was just life, I guess. 

And at the same time, I just give my mom so much credit because while we were recipients of so much generosity growing up, I mean from the time our roof caved in in our house and the guys from our church came over and literally like reroofed our house, I learned I learned to, you know, my passion for, like, fixing things started from that. But it led to a family friend of ours almost drowning in a pool, so I led my first fundraiser when I was eight years old—or traumatic brain injury. 

Then, I remember my first real moments of making a big difference with Habitat for Humanity. And I think that he was probably 12 years old and volunteered to help make wheelchair ramps at a senior home with habitat. And it was just something that stuck with me.

And the funny thing is, later in life, you know, I went through … I grew up and went to business school. Never. It never occurred to me that I could work in the philanthropic world. I just thought it was the thing that I was a donor, and I would donate, and I was a board member, and I would, you know, help, you know, volunteer. And I did that.

I started two tech companies in the nineties (94/95 through 97). I ended up serving on a board at a boys and girls club. And this is a classic story for how people get into nonprofits by accident, which is, you know, I showed up to a board meeting, and the director said she was leaving. They asked if, you know, a short straw kind of thing, with someone willing to take over for just a little bit, you know, “man, the farm” or whatever, “man, the house.” And I naively did, and I was going to get my MBA by the time I'd sold my second business. Which I thought would be about a three-week journey, which I, you know, felt, put a band-aid on until we hired someone. I ended up there for seven years.

And it wasn't surprising to go back to your question more directly. It wasn't long until I realized that the culmination of my experiences growing up was why I felt. Where I was at the time working at that boy was also where I needed to be. And it was, I think, my third day going into just kind of again, you know, take care of things, that I walked in, and a child was sleeping on the porch. And you know, this is not even in a great location. But he was sleeping on the porch because he had gone home the night before. And his mom was a drug addict. He was an early high school student. A type one diabetic, but just so smart and with such a tender heart. And he felt the boys and girls club was the only safe place he could go. And my gosh, like I mean, from when I was a kid, I went to the boys and girls club, and it was a safe place that I could go.

So again, when life has a plan for you, I would say to be open to those opportunities, say yes, and go for them. I spent 20 years fundraising, even as a “technologist.” I had an amazing career in the nonprofit world.

That's an amazing story, Nathan, and I love the inspiration you have to give based on that story. In your book you talk about a concern you have. It sounds to me like you're very concerned that giving may decrease, and it has decreased, and that we should be thinking a lot about how, in the new age, people are interacting with doing good in the world. How do we make sure that we support people to continue to give back in a way that works. Let's talk about that a little bit.

Yeah, I think you know … I don't know how many people are aware or unaware of this. I'm always a little surprised; it seemed obvious, but at the end of the day, I mean, there were a few constants that I experienced, you know, raising money for 20 years.

And, you know, one constant was that my goal got larger every year. This unquestionable thirst for more money was present every year, and in any organization I worked in, we did well, but we need to do better next year and raise more money. 

The second was that when we looked at the data, it turned out that we were raising more money from fewer people. And so that was a kind of interesting, you know, dynamic of really learning that, like, we were, we're kind of going against all odds because, like, you know, we have this unquenchable thirst for our money. Still, there was a pulling away from the typical charitable giving donors we had relied on.

So, you know, I had different roles and nonprofits throughout my career. Back in 2012, I was asked to write a paper on anything that I found interesting, and it was through a consulting firm I was working with, and it was just kind of a “train, the trainer” kind of thing.

So we had to present anything we wanted to other consultants, and I chose the topic. I was interested in the disparity of wealth. The Giving Pledge, launched in 2010 by Bill Gates and Warren Buffett, was launched in 2012, so I was kind of watching this go by, and I was gaining a few hypotheses about what would happen. The first hypothesis was, well, this, and as a kind of history buff in the Industrial Revolution, I'm like this could be like the generosity revival. This would be the thing that used to make front-page headlines with Rockefeller and Carnegie about how they were competing against who could give away more. You know, while they were alive, the giving pledge could be that, and it would make giving in vogue like a really exciting time.

But then, it didn't take long for me to have another hypothesis: Well, what happens if the average person pulls away because, you know, I want to contribute to polio, but Bill Gates has already made my contributions… are they still important? And that's not All the reasons why there's a generosity Crisis.

I mean right now, there's been a 16% decline in the number of people who give, so less than half of Americans give for the first time. In history, less than half of Americans give to charitable organizations in the US, much lower than in other developed nations like Australia, the UK, and Canada. But you know, only 20 years ago, that was 2/3 of Americans. 

So you know this idea that generosity was always here and will always be here. I was challenged, and so a couple of years ago, I think I was challenged throughout my career and raised more money from fewer people.

It didn't take me long to figure out that if we keep on doing this, bad things happen, and at the end of the day, the institutions we rely on as donors are the ones we rely on … Museums or free clinics, or, you know, Cancer Research, or zoos… are all at risk of going away if we continue on this negative trajectory.

Yeah, Nathan and the first sentence of your book is pretty powerful. In the introduction, you say “uninterrupted. Those who engage in traditional philanthropy will cease to exist in 49 years”. That's a pretty powerful statement.

Yeah, yeah. You know, it should give you pause or, you know, make the hair on your neck go up. I mean, not, you know, if you're a nonprofit professional, it's about 10 million of those in the country. Or if you're a donor and you rely on, you know, kind of the staple of, you know, the nonprofits that you care about will always be. There it is it didn't take a lot of Math. Any organization has a negative trajectory that, year over year, is going negative and never going the other way. It ends somewhere. 

So, what we're finding in the US is that giving, which remains extremely vibrant and large, is being made up of half a trillion dollars in the US. There are fewer and fewer people. And with that, there's a complicated question because, on one side, we have to celebrate the amazing generosity of ultra-high-net-worth people and high-net-worth people willing to step in and make contributions. 

But we also have to recognize that there's a society that's becoming less, “Generous” by, opting out of giving to traditional nonprofits. And what does that less generous society look like?

Yeah. So let's talk about this. Let's talk about, well, what does this society look like? But I guess you do sort of talk about some of those scenarios in your book.

So I do want to go there. 

But first, I want to consider your proposal and how I read it… essentially, democratize small D and democratize giving. And how are you feeling hopeful about AI as a solution to bring people who may not be high-net-worth individuals but give them more access to have them not feel so overwhelmed as I do? I'm sure you know people are good in the world, and the decrease in giving is probably not absolutely because people have gotten less good. It's maybe more that they don't have as easy access as you were saying. They feel like, Oh well, the ultra-high net. Worthy folks are taking care of it. In reality, that's not always the case.

So, talk to me more about how AI might open up a whole world of giving for people who want to do good but haven't felt empowered or had access to it. And then let's talk about some examples, too. 

Yeah. No, I think it's a great question, and in the book Generosity Crisis, you know. The decline in charitable participation the number of households that give is a culmination of many different things. 

So, we spend most of the book going into internal and external reasons for that. Some are in our control. Some are internal and external, but this is where my whole world comes together. This is like an interest in generosity and the changing nature of generosity and AI.

So, I was leading a large fundraising team for cancer. On one side of the hospital, we knew that we had patients who were very happy with us, deep admiration, respect, and generally generous feelings toward us, and an abundance of these people. But we didn't know how to capture them. We didn't know how to measure them, and we weren't sure. In an average hospital, only 2% of patients ever make a gift to a hospital. Truly, this is like a needle in a haystack of questions. What's the difference between these 2% and so being a technologist, and that always kind of running through my blood from the entrepreneurial, we set out to create the first algorithm to predict which people were most likely to give. 

We found out in our first kind of AI exploration, which was not easy in 2017. Like, AI is very different than it is now and not very accessible. So a lot of you know, a lot of statistics, a lot of math in science, and Computer code. But we found out first that our experiment showed us that wealth was a very poor indicator of whether or not people were generous. 

And so, to your point. And we even say this in the book: maybe there is no generosity crisis; maybe nonprofits haven't remained relevant. Because if we look at it, fund me. People, you know, fund me. I process one transaction per second, 24/7. People are very generous. They want to see an impact, and the nonprofit has become a barrier to their generosity because they have become so transactional. People don't feel like their gifts matter or are needed, or they're not thanked, or, you know, they're doing something else, or they're just buying responsibly, if you ask Elon Musk. And Musk directly. All of his companies are philanthropic. So, a person who buys responsibly at Patagonia gets the same dopamine and serotonin as someone who makes a gift. The choices for making a difference are there, so I want to answer that part of your question.

In the age of AI, once we learned that you know, it wasn't surprising that wealth and philanthropy are not directly correlated. It's a slow, low correlation. But how well you're connected to an organization, how well you know them, and what data represents your connection to the organization. Essentially, in real-time, the same way Amazon assesses what you're going to buy or predicts what You're going to. You know the next day, the next day, and the next day based on what you did today.

We got good at it. We figured out that when we removed wealth from the occasion from the algorithm, and we just started measuring the connections of people, that connection was the biggest, and it still is the biggest predictor of whether or not you're going to make a gift. 

With a shrinking pool of donors in the US and other countries. It's increasingly important for us to look at what AI can do in a much less biased way by looking at 1000 data points instead of just a few. You know, data points to essentially assess, you know, the level of connection that someone has to an organization and do that in real-time. 

Back in 2017, this was, like, really difficult and expensive. Like algorithms were expensive, storing data was expensive. Fast forward to today, you know, six years later. We're talking a fraction of the cost, much fewer barriers. Organizations that need both precision and personalization have access to that easily at their disposal.

And so it's, I think, a really exciting time as we thought about what we hoped to write about in our book but couldn't find a substitute. It's like, what is the one thing that teaches the virtues of giving, or the one thing that you know, reverses that generosity crisis and we conclude that AI is the only scalable solution to reversing the generosity crisis because it's a tool that allows nonprofits to compete to create a level of precision and personalization that every donor expects. When they wake up, they turn off their Google alarm clock and put on their Nikes. Or their Patagonia jacket.

Can you give me some stories? Some examples: you were about to go there when I interrupted you and wanted you to focus on this line of conversation. But please give me some stories. Examples of where this could work well and some of the challenges, and then I want to do some friendly pushback.

Yeah, go for it. I love the pushback. Otherwise, it's just too easy. If we look at the private sector and how they have used AI to mine interest, as the AI world calls it, you know that we're in the attention economy.   

So every organization points an AI algorithm at your head to essentially, you know, toward this race to the bottom of the brainstem. What they're looking for at this point is intimacy. They're looking for How much you care about them. Are you going to wait in line? You know, for the new pair of Nike, or are you? Are you going to buy them 12 months later? You know, at the end of the day, what we call in our book the competition for connection has done. It's done a lot of things. It's distracted us as individuals; our attention span is now 4 seconds less than it was just 20 years ago; we had an attention span of eight seconds, which is lower than a goldfish.

And so the reality is that nonprofits have not been able to… I think the mindset has been that nonprofits compete with nonprofits for a finite set of dollars. And the reality is that they're not competing for dollars; they're competing for attention. They're competing for connections.

And so at the end of the day, when we've seen this go well, it's first a mindset shift. This is not a fundraising issue. The generosity crisis is not a fundraising issue. It's an organizational issue. It's us. I think I have. I'm a donor, and I'm a board member, and I'm, you know, I run a tech company, but, and you know, I spent 20 years running a non-profit. The pendulum has swung so far to be transactional that people have effectively opted out. They're just like, you know what? I'm not an ATM. I'm a person.

And by the way, Patagonia knows I'm a person, and, you know, Starbucks knows I'm a person. You know, they send me, you know, coupons two weeks before my birthday because they know it's coming up. They want to celebrate with me. The nonprofit sector has not done that, which works well. It's not because they buy a new tool or an algorithm. 70% of AI transformations have nothing to do with data or models. It involves people within the organization who use tools to become more efficient.

But at the end of the day, I would say nonprofits that do this more successfully point the finger. AI at things that instill and develop trust, and that's truly the only way I see this working is when technology, whether it's or not, helps foster trust. It can be a good force for good; it should not be used if it diminishes trust.

Yeah, and give me an example of where you are with the cancer research and the institution and being able to think through. Are there any other ones you'd like to emphasize either mistakes like opportunities lost or not, and I've heard your Ted talk. So, I know a few of them. But please let me know. Tell my audience some of your examples because they impacted me when I listened to them.

Yeah, no, it's so it's really fun because, you know, we're in the space, also carving new territory. So, every day is a new day, and we're learning new things. And you know, in our first five years, we've learned a lot of things the hard way.

So, you know, we built the first algorithm called Gratitude Prediction in machine learning, and we patented it. And then, as soon as we patented it, we realized it was a really bad idea. If trust is the currency of the nonprofit sector, how do you trust something you can't see? By nature, something patented is something you won't share with anyone.

And so, you're because you're protecting your intellectual property. And so, in the private sector, all these algorithms that Twitter and, you know, Instagram use are essentially, you know, mining your connection, but they'll never show you how they work. 

So, one of the biggest lessons that we learned, you know, through this epiphany was that we have to hold ourselves in the nonprofit sector to a higher level of responsibility and that anything we develop should be open, transparent, and explainable. And you can interrogate it.

And so, this is why I spend half of my waking time now focused on responsible AI for fundraising. And so yeah, at an international level. And so, this is now more of my passion project of like and hope. I hope my legacy will be bringing out responsible AI practices for the nonprofit sector so that we don't make giving more transactional and we don't remove humans. But when we see this working well, we see it, you know, like in the cancer hospital, we see it mining information of essentially people that are raising their hands like I like you. And I want to know more information versus people pulling away from you, and, like, you know what I'm good at; I don't need to talk. 

What that does for nonprofit organizations is that it removes that notion that most nonprofits have fallen for, which is that more is better. Like, let's just acquire more donors at any cost. Last year, I received 8.7 pounds of direct mail. I collected it all year, which annoyed my wife, but I collected it. And I am doing it again this year. And I'll measure 8.7 pounds of mail from only five organizations this year versus last year.

So, my giving is very narrow at the end of the day. I have my favorite like most people do 1-2 or three charities. Maybe a couple extra, but the way you know the data has been bought and sold has, you know, commoditized giving to this trivial way of thinking, and it's just turned off a lot of people, but when? You can get away from those lessons more and say, look, I don't want just more donors; I want better donors. I want people that is going to go the distance with us, when we find this to be true, and most people our donors know they have a stronger affinity for some organizations than others, which we call radical connection in our book. And because of that competition for connection, we must redefine what connection means. It's not just an affiliation, association, or preference. 

It's not like I like Patagonia. I go out of my way for Patagonia. And so if I'm traveling somewhere, I was just in Hong Kong. Tokyo, like I took a $40 Uber ride to Patagonia, not even to buy something, but just to see and support it. And, of course, I bought something. But you smile when you think about or tell your friends about the radical connection between yourself and organizations. And if any friend were asked, like, what are Nathan's, you know, top priorities, they would say the farming project in Patagonia, in Notre Dame, like they would know, like, those are the things that I hold. 

And I hold dear to my values. The cool thing about AI is that we can mine and understand. What are those? Organizations you have that radical connection with because the data show that you're leaning in, filling out surveys, and attending a play more often than others. You're driving a further distance to go to that play on certain days of the week. 

And so, you're what the what's called digital exhaust, the digital footprint you leave signifies, like, how much do you care about this organization? How well do you know them and that's It's really healthy and really exciting.

OK, so now for the friendly pushback. All right, you are a professional at supporting donors by helping them give money to nonprofits they care about. I'm like, that's. I'm essentially like a program officer contracted by folks who want to be effective givers. Right. OK.

So, the friendly pushback is that I sort of joke with my husband because he also does the same job I do; he runs and's the executive director of a private family foundation. We sort of have a Running joke. We go… Oh my gosh… Web-based research: so often we have folks come to us and say, we did a bunch of web-based research on X issue, and if you do that and you don't have expertise in the issue, and you don't know the players, what's going on, who's getting along with who, what's the visionary leadership in a certain organization. Usually, if you're really in on the whole thing, you know, oh, that, ED… They're wonderful, but they're going to retire in a year, and they're going to go through a transition. So we have to think about that. 

There are so many things that aren't available on the internet. Those are required to know to be an effective philanthropist, so my question for you is, how will AI be able to account for those things? Like if I told you that my interest was in the X issue. And I just did some web research on that issue. I know that, and I've done it. I've sort of experimented with it myself. I know I only get 1/3 of the effective groups and won't get the whole story. So, how do we address that question with AI? I'm sure I thought about it.

Yeah, I think it's a multifaceted question in the sense that, you know, we can look at it from both directions. So we can look at it from the nonprofit perspective and see how they're looking for donors with that interest, and the reality is that it has to start with first-party data.

So, say I'm a nonprofit, and this is a common question. It's like, help me find more people who look like my donors. Well, what data do you have on your donors? But the reality is if you have a lot of data on your donors, you can build an AI profile of an ideal candidate. But if all you have is that you're giving transactions, no matter how often people give, you'll never get there.

So, you know, the secret sauce in all of AI ... AI is essentially, you know, a tool that can't do anything without data. And at the end of the day, you see a lot of big corporations using things like surveys. Let's not just take it for granted that I want to scrape the Internet to learn about people. But let's put out a survey. 

To find out, like, how people think about us, and even the fact that the most important data point in any survey is whether you filled out the survey; essentially, even if it was constructive or negative feedback, You and it almost always statistically, you'll end up being a better donor because you cared enough to do it. When you peel back that onion, how you answer questions in the survey yields, you know, how much do you care about that organization?

So, most nonprofits are behind in managing and collecting data. Scraping the Internet will not do it to your point. It can help enrich it, but you must start with your first-party data. You know, to get a better sense. Conversely, that's a priority #1, and nonprofits are behind. They're behind, even looking at AI and determining if they will use it. Or they're not going to use it, and that's fairly tragic. I mean, that's going to create a huge digital divide.

Yeah. And Nathan, I see it firsthand, someone who works for donors. Nonprofits do struggle. I love that you said bank transactions; that's one of my lessons for nonprofits. I'm like, don't treat the donor like a bank transaction. 

Yes. But then, like the donors I work with, some have websites describing what they fund because some are private family foundations. The challenge I see there is that a nonprofit will read the website of one of my Plans. They'll come to me, and then I say, we think our thing is connected to your overall goal, but they won't. They actually won't be anywhere connected to it. And that's another thing I think about, like the information and the connection. 

OK, so you're about to flip it onto how donors how do donors find nonprofits effectively.

Yeah, and this is the area that I think you know most of my work has been in machine learning and deep learning, which are all about precision and personalization. But, you know, the advent of generative AI. It is transformative from this perspective specifically, so you know, and we're, and I'll be very clear, like where we're at in generative AI is not where we will be. This technology is exponential, and when we have a .05 upgrade, not even a full upgrade to the next, as you know, we went from ChatGPT 3.5 or GPT 3.5 to Chacha BT, which is 4.0. That wasn't like a little thing; it was like a monumental; built upon that, GPT 5 will be built on a billion dollars in computing power.

So one is, I think, the ability when we get better at removing hallucinations. We get better at providing trust layers so that they're providing more accurate information. I feel transformed by how we curate and source things off the Internet, like doing a Google search, and I know this to be true for me and most of my friends who use generative AI a lot. It already feels archaic to me; why would I want 77,000 rows of things that I could click on, most of which are clickbait, and then have to read the page to see if only one sentence is applicable? Very quickly, that will feel archaic, and within about two years, people will not be doing searches in the same. Right.

Their ability to train on new and relevant data from the Internet I used something the other day with the new GPT that sources from the Internet. It was a very long query about worldwide trends in giving, and it showed me every report it was reading in real time. And these are reports that I've read in the past. Like giving the USA and the worldwide philanthropy study from Citibank, and I mean Sure, like 100 pages. You know the document, and I wanted a concise, poignant synopsis, all within 30 seconds. 

So, it showed me and sourced the sources I sought from a donor perspective. Doing a Google search that sucks like that's like that will feel so archaic to your point. It will source a third because many nonprofits have bad search engine optimization, so their websites won't even pull up. But they might be doing amazing work in that space, but they're not web programmers. They didn't build their nonprofit. 

Be seen by the world because they're focused on supporting their mission. Large language models like CHPT, Clod, or Bard will transform our ability to understand the world in a different, better way. Also, it will be overwhelming because of our ability to source all the information in the world instantly. It's a bit overwhelming also, so we must all be very conscious of what we let in and don't know from that perspective. But I do think, from a donor perspective, it will source and find incredible organizations that you would have completely missed otherwise.

I appreciate this conversation because it also means If we in the philanthropic space care about these wonderful nonprofits, and what you're saying is, you know, charity and giving are sort of going lower. Let's get ahead of the curve here and support all the nonprofits we care about to be prepared so that when AI continues to evolve positively for us, it will pick up on our nonprofit and the good work. We're doing so, so there's got to be some key things that, as we're creating our websites and other things, and as we're supporting groups doing that, maybe there are some key markers, some key things that we want to be sure that they put in their website.

So, when AI searches, they'll pick up on those pieces. I know that; in the past, it was like keywords. There are different things there, but you know. I feel like this is a conversation for both donors and nonprofits because usually, when a donor funds, at least I notice when my client funds a nonprofit, they want that nonprofit to succeed. They didn't have enough money, of course, but they wanted to collaborate with many other donors to fund the whole thing they wanted.

So, talk to me a little about that. Like, what are some key things we should be thinking about? When we support nonprofits and their websites or identities online now, maybe it won't be websites in the future, but talk to me about that.

Oh my gosh, there's so much to unpack there. I mean, you know, and of course, this is where I think I was just on the phone with someone earlier. Today, she does a lot of consulting with small and midsized nonprofits, and I asked how many are using AI at this point, and she's, like, less than 5%, and that's been pretty consistent with my assessments as well. 

The reality is that the things you just mentioned are things that large language models do very well, like drawing, which is a pretty good concept; you can draw on a napkin; a website you like to create, and chat GBT. You will write the code in HTML, giving you a website.

So to think about, if you have a website, if I'm a nonprofit, And I want to optimize my website for, you know, utilization. In this discovery, all I have to do is say, here’s my URL; give me your code for optimizing my website for, the modern day, and it will do that extremely well, you know.

I love that. Thank you for saying that.

So that part is just … I think people grossly underestimate the level of complexity that you can throw at the GPT model and be able to task it. You know that. So that's pretty impressive.

Yeah, it's really important. And I can just talk to you forever about all this stuff. It's been a while. We've already talked for a long time, so sadly, we must conclude today. But please, let's follow. Can you summarize some of the most important things you want my listeners to consider? Before we go, also tell everybody about the book you just wrote and that you're talking about with.

Yeah. Yeah, thank you. And it's been such an amazing journey. I mean, we wrote about the generosity crisis probably out of frustration. I don't think we ever intended ourselves to; never writing a book was not a bucket list thing for me, but I was concerned about our sector and where it's going, and, you know, I also have such reverence for it. This idea creates a sacred space between donors and nonprofits: You know, neither you nor I could do this alone, but we together can achieve things that neither of us could do by ourselves.

And that's truly where the magic happens, right? It's the intersection, you know, between the donor and the mission. I think, you know, after writing the book, it's been in the Amazon Top 20 in the clamped category since it came out a year ago, which is just nuts. I mean, so it's actually, even though it's a stark reality for the first 100 pages. 

And I always recommend it come with a warning, like, have a box of cookies with you or something while you read it. Look, because the first 100 pages are a bit stark. What do we have to lose if we don't do anything?

That's important because how do you make a change if you don't know what's at stake? The second half of the book, which is a book of hope, is about this idea of radical connection. It's about, you know, leaning in, you know, from a donor perspective. It's putting on a blinder a bit to the distractions and the plethora of opportunities you have. Your attention is being Bold and recognizing that your ability to have a radical connection is finite like it's not this: we can't connect with every organization and every person. We'd love to. We have to be extremely deliberate. First is recognizing that our ability to connect is finite, and that's good. We can only have one best friend. We might only have one favorite charity, but we can't have 300 favorite charities.

And so, at the end of the day, a call to Less is more approachable. Do go deeper with organizations that you care about. Be conscious of that connection, and then, like you know, peel back that onion. You know about that organization. And that's, for me, a freeing. It's me, me as a donor, that's freeing because it removes that guilt of feeling like I had to respond to 8.7 pounds of mail. Like, it's OK, my ability to connect is finite, and I'd rather go deeper with my top three than feel like I'm spreading the wealth to the 300.

Thanks so much for that, and if anyone wants to check out everything you have to offer in the discussion around your book, people can go to the generositycrisis.com website, and we'll have the link to that in the show notes as well. Nathan, again, it's been delightful. There's lots to think about here, and I'm just going to keep thinking about all of them. Things because it's. It's so important to ask the question of AI: how do we infuse AI into generosity, giving back to the world, and supporting great people doing good work? So just, I thank you for all you're doing and what you're thinking about today.

Thank you so much. It's truly been a pleasure.