And welcome to Tony Martignetti Nonprofit Radio. Big nonprofit ideas for the other 95%. I’m your aptly named host and the pod father of your favorite hebdominal podcast. I’m traveling, so the mic quality and the sound is not quite up to par. I’ll be back in the studio next week. I’m glad you’re with us. I’d bear the pain of Brady stasis if I had to stomach the idea that you missed this week’s show. Here’s our associate producer, Kate, with what’s up. Hey, Tony, introducing. A skeptic’s view on the value of AI in fundraising. Holding Fire is Steven Christopher Nill’s new book, written by this artificial intelligence skeptic. Launching his book on nonprofit radio, he presents his human-centered AI framework, five principles to keep humans at the center, as AI does the work no one fundraiser could do alone. There is fundraising potential. There are fundraising risks. You’ll find Steve’s book at charitychannel.com. On Tony’s take too. Beach days are back. We are sponsored by the Bridge Conference. Tony will be with more than 2400 nonprofit professionals at Bridge, July 29th through the 31st in National Harbor, Maryland. Info and registration at bridge.org. My thanks to Bridge for sponsoring nonprofit radio for several weeks, and yes indeed, I will be at the conference. I’ll be there speaking on July 31st. Here is a skeptic’s view on the value of AI in fundraising. It’s a genuine pleasure to welcome. Steven Christopher Nill to nonprofit radio. Steve founded Charity Channel in 1992 and built it into one of the world’s largest online communities of nonprofit practitioners. Through Charity Channel Press, he has published dozens of books on fundraising and nonprofit governance across 4 decades inside development offices and advising hundreds of nonprofits. He has helped raise billions of dollars, billions. Woo. His engagement with artificial intelligence reaches back to the 1970s. 1970s. Uh, I, I’m skeptical of some of these claims here. He writes weekly to development professionals at charitychannel.com and he’s on LinkedIn. LinkedIn? No, he is, he’s active on LinkedIn. And his brand new, recently, immediately recently published book is Holding Fire, A Skeptic’s Framework for the fundraiser with AI at your side. The author of Holding Fire, Steve Nell. Welcome to Nonprofit Radio. Thank you, Tony. It’s, it’s, it’s gonna be fun to be here, I think. You think you’re not sure. All right. No, I know it will be. Now, that’s two things you’re skeptical about, uh, AI and, uh, your, your presence here. All right. Um, So, congratulations on the brand new book. I have the very first copy of the book, don’t I? I have these bragging rights. Tell, tell folks how that, how that happened. I got the very first print. Well, we were talking about doing this, uh, this interview, and you wanted to have some sort of a, uh, first. And I admitted I’d done another couple of interviews that haven’t aired quite yet, but, um, if I hadn’t sent them the book yet, so in fact, I hadn’t sent myself the book. I had just been um uploaded and I said, look, I’ll send you the very first copy even before my own, so now you’ve got a bragging right. You got the first copy for better or worse, off the press. The first copy is pristine. It’s outstanding. Uh, yeah, so even before your own copy, I got one. So thank you. All right. I like to work with hard copies. Uh, I, I know I’m, I’m a little bit of a stickler that way. I, I much prefer the hard copy over, over digital. So thank you. Thank you. Sure. All right, uh, the skeptic, the skeptic, uh, we’re gonna talk all about the framework that’s coming, but the, the AI skeptic actually goes back to, uh, a history with AI, uh, from, all right, let’s, let’s, uh, validate some of these claims in the, uh, in the bio. Uh, it goes back to the 1970s. Yeah, 1977, I was in an honors physics course at my university. And I wrote a paper that posited a computing device based on quantum superposition. Of particles, in other words, using particle spin capabilities as storage for computers, and I suggested such a computing device could Be far more powerful at breaking encryption and things like that. I got an F on my paper. Um, because I’ve been invited to the course and no one ever asked me if I’d ever learned calculus, and, and that was a requirement for the course, which I didn’t know. And so, uh, I had to, the night before the thing was due, I had to invent a bunch of math just to substantiate a lot of the things in my paper and the professors, there were two looked at it and said, what is this? And you know, F. And I asked one of them afterwards, I said, look, you invited me to this course, um, at least let me defend my paper. And so they let me come back and they were both sitting there and I Put my math up on the board and, and I explained what every symbol meant, which I had literally invented the night before and I said, this is, this is how you calculate this. And by the end, I defended the paper and I got an A. So that was, um, that was the beginning of my interest in computing and from, from a theoretical, you know, point of view, and I’ve been following. Um, advances in computing ever since 1977, which is when I wrote that paper. And uh I didn’t go into theoretical physics or computer science, although I’ve taken a ton of courses in computer science since, um, but I followed it carefully. I went, I went on to be a lawyer and and working in the nonprofit world and fundraising and that kind of stuff, but it’s always been near and dear to my heart, Tony, and Um, so that’s, that’s sort of my background and so I have a foot in, in, in sort of the computing side and the artificial intelligence side, but and also in the fundraising and nonprofit world, uh, which has been my career. So, So you were, well, you did get an A ultimately, uh, you defended your paper. I got an A and I’m, the weird thing was I’m the only one who got an A. All right, but you started with an F, like you were ahead of your time. I got an F. I, I richly deserved the F because my math was, you know. All right, you were vindicated. You got, you got the A. I guess I did, yeah. And we’re gonna have plenty of time to get into the, the, the details of the book and, uh, like I said, your, your framework, of course. Um, you do say that, that AI can, AI can mimic warmth, but you say it in a way that AI can only mimic. Warmth, the warmth of people. And this is something running throughout the book that, that there’s, there, there are processes and, uh, sort of patterns and changes, you know, that AI can see. But there’s a, there, there needs to be, there will always need to be is central to your, your thinking, the human. Uh, the, the human component of fundraising, that, that, that AI, AI has a, uh, has value, but within certain limits, strict limits, very strict limits, you, you posit, and, uh, the humans must, must be involved in the, in the rest. So, I, I like that, you know, AI can only mimic warmth. Yeah. And, and at the same time, elsewhere in the book, you say that AI can amplify our own humanity. So talk us through your, your high-level thinking before we get into some details. Such an important question. I’m so glad you started the, this discussion from. All right, so are you less, are you a little less skeptical now about, uh, about your, about whether you’re gonna enjoy this or not? No, because we can wrap it up right now. If, if you want to wrap it up in 7.5 minutes, we can do that. We can wrap this whole thing up. If you wanna wrap, you know, if you’re still not comfortable, we can wrap. No, Tony, let me just say, so far you’re the, you’re the one interviewer who insisted on reading the book before the interview, so thank you. I’m sure there will be others. I don’t know how you can talk to an author about their book without reading it. I know, I know. Thank you. Your, your integrity is, is shining through. Um, AI can, can mimic, uh, pretty much any, any kind of human, um, behavior, at least in words, because it’s trained on words, you know, the, the, the whole large language model is literally turn it loose on the internet and feed it all this copy, feed it books, and the more information you feed it, the more it can pretend to be human. And it’s so good that Um, there are people that, that, you know, have written hundreds of novels with it. Although the, the novels are, are sloppy, slop, they call it AI slop for a reason. It’s, it’s not terribly great, but it’s, it’s how good it is. It can mimic even writing styles and, and everything else, and it can mimic human warmth. In a, in a development office, the temptation is to use AI to write our donor communications, isn’t it? Because, you know, development people, uh, in any sized office are under a lot of pressure to try to reach out to their donors, and it’s so tempting to have AI write a, write an email or write a letter. I don’t know anyone write letters anymore, write an email, uh, or, or some other electronic communication or, or, or whatever. And And it, it, it’s on the surface can seem pretty good at it, but the thing of it is, is. It’s not the, it’s not the human fundraiser actually writing that communication. It’s, it’s the machine. And I think it dehumanizes the process, and I think donors are are onto this, and I think it’s only a matter of time before we start to see our donor relationships. Erode even as we’re trying to reach more of them at a deeper level through AI. And what what I have seen happening is a temptation to now that now that these um. Software vendors, um, these, uh, systems, the CRM systems that we all know and love in our sector are incorporating AI. The temptation is to sort of turn AI loose into that process because, hey, we could reach so many more donors now. And the problem is. It’s, it puts the AI between us and the donor. It may not seem like it, you know, if we misuse it that way, we are no longer really driving the communications the machine is. And, and to me, Um, and Tony, you know, you’ve been in the sector for decades and you have a wealth of experience in this, as do I. We know that, and I hope it’s OK to say this, I’ve had a peek at your forthcoming book. We know that it’s all about relationships, right? It’s human relationships, and that’s the thing that we’re sacrificing. If, and if we’re not careful, it’s, it’s gonna move us backwards, not forwards. And so that’s the whole reason I wrote the book. I’m a skeptic. I really wish AI wasn’t here. As much as I find it fascinating. I’m alarmed at the speed with which it’s been inserted into the CRM systems that our development officers are using and absolutely every other tool that we’re using without much thought about the impact it’s going to have on our donor relationships, and that’s why I wrote the book. You just said, uh, you wish AI wasn’t here. You wish I really do this. I really do. It’s, it’s a, I’m in a weird place because I’ve, I’ve been fascinated by the, you know, thinking machines, if you will, my whole adult life, really. Um, and, and maybe it’s because of that that I saw early on. In fact, the outline for my book I wrote at the turn of the century, decades ago now, cause I foresaw this day. I, I just didn’t publish it because AI wasn’t here and no one would buy the book, but I had this outline almost unchanged for the book because it was so clear to me that what was going to happen was AI was going to become so powerful. And so convenient that we were going to replace our own human judgments and efforts with the machine’s judgments and efforts. And while AI holds real promise to let us actually reach out and, and, and. Um Identify opportunities with our donors that we never could before. If we allow it to do too much for us, it’s going to actually hurt those relationships, and we can’t let that happen. You, uh, have a different concept of the, the CRMs, the customer or constituent relationship management, uh, systems. You call them RBSs, relationship building systems. Yes. Well, I don’t think of our supporters and donors as, uh, needing to be managed by us for one thing. So the term itself is just doesn’t fit the nonprofit, uh, world very well. But I think we, we, if the technology needs to help us improve our human relationships with our donors. Grow those relationships and then, but stay out of the way enough that we’re the ones driving it, not the, not the technology. So I do focus in the book a lot on what I call relationship building systems. Because Um, they have raced, raced to put AI. Capabilities into these systems. And so, honestly, I don’t see very much thought into governing those AIs or even trying to train those AIs on Our human values and, and even our fundraising ethics, for example, and Uh, I don’t see a lot of effort being made into having that AI. Uh, suss out opportunities to make a phone call or do a visit with a donor or do the human things. I see the emphasis, maybe by default on, hey, we could write 100 letters now that are all personalized, and we could zip those things out and now you can reach your entire donor base in 10 seconds or 10 minutes or whatever. That’s the wrong approach and that’s what worries me. So little thought seems to have been put into all of this. That it’s going to do more harm than good, and honestly. I don’t think the fundraising profession or the nonprofit world in general has been sufficiently consulted by some of these software vendors before just bootstrapping these AI systems onto them and putting them out there as products. I think there’s been a breakneck race to add AI because, hey, if we don’t, our competitors are going to do it and we’re going to be at a competitive disadvantage. I think that’s the mindset. And so now we in the nonprofit world, folks like you, folks like me who, who actually care about this, have to come along and figure out, OK, how do we prevent the harm while allowing the good to happen because there is a lot of good that can happen with AI if it’s properly used and properly understood. And that’s where I gave a lot of thought and that’s where my outline emerged years ago when I first wrote it. And it, it was, you know, we can actually give AI a set of rules and principles and guardrails. And it could then know when to back off and allow human judgment to take place, human contact with our donors to take place. Also in the, in the very writing of communications, a critical step is rewriting those communications in our own words, things like that. So I wrote up a, as part of the book I released to the, to the world, if you will, through a public license, a uh a specification um that the AI literally reads before every session and knows how to behave and, and that’s, you know, that’s um. That’s a pretty powerful tool. I don’t mind saying so myself. That’s why I released it free to to anyone who wants it. I hope software vendors are listening. Because this, this is the missing ingredient. This is the, to me, this is the moral and ethical opportunity to reorient their AIs as they face the nonprofit world in a way that serves us rather than sort of serving their competitive advantage, if you will. That’s where we want to get into your human-centered AI framework because the, the specification you were just referring to is Is the embodiment of your framework, uh, that puts it in an AI readable format. So let’s, let, let’s now talk about the, the human-centered AI framework that you introduced in the book. Um, you’ve got 5 sort of pillars, uh, pillars to it. Do you wanna, do you wanna tick them off? You want me to tick them off and then we’ll, we’ll go into some detail on each one? Why don’t, why don’t you, why don’t you tick them off and we’ll talk about whatever part you want. OK. Uh, number 1 is the healthy division of labor. 2 is the workflow. 3 is the virtuous data cycle, 4 is the scale shift, and 5 is ethical vigilance, which governs all the others. Putting the donor’s interests first. So, let’s, let’s talk some, uh, let’s, let’s talk about the, the healthy division of labor. What, what do you mean by this? Well, The tendency is, is for nonprofits to Uh, pull back on their human resources, their development staff, and, and try to leverage AI to do much more of their work. Indeed, I, I was a little amazed that there’s, there’s this 11 college I was reading about in the Chronicle of Philanthropy, don’t ask me to name it, I can’t even remember now, but Where the, the college, uh, essentially dropped most of its development team in order to end is using AI in its place. Um And that is probably the most extreme example of what worries me the most about AI, and that is using AI to essentially take the place of the human development officer, and that’s a huge, huge mistake, um. So the, the division of labor is, look, AI can, can the, the, the most important thing it can do for us is it can look at our donor base. Because we can give it access to the donor base. That’s what these online systems have done. And we can have it suss out. Uh, lapsed donors that are showing signals of wanting to re-engage. Uh, we can have it, uh, talk about somebody who has given a fairly small amount for say 3 years and has never received adequate recognition beyond, you know, the acknowledgment letter or something like that. Um, we can have it look at a donor’s capacity, if there’s any kind of well screening built into the, into the system, it, it can, it can look at that. Um, And a myriad of other things and then it can actually give us a briefing, say, um, I like to call it the Monday morning, you know, briefing where it says this week, um, these are the donors you need to focus on and here’s why, and here are, here’s where they fit in our development process. Here are the opportunities and here are the very communications I think you should send and AI can do all of that for us. That is amazing. I mean, Tony, we’re talking about something that, yeah, it winds up in these online systems, but when I was writing this book, I took a simple program um called Obsidian. It’s a note-taking app and it’s, it, it works with plain text files, OK. And I, I dropped a bunch of, of, of fictitious donors into it and I turned my AI on it and that little simple app that’s free, by the way, became more powerful than, than, um, say the Blackbot system or the DonorPerfect system before AI came along. And It did because AI can read unstructured information. So if you just have a like a a a file on a given donor and you throw a bunch of information in and maybe not even that well structured. AI doesn’t care. It can, it can understand what it’s reading and it can then pull things out of that, that we humans just don’t have time to pull out. And, and some of it I think is our capacity too, the, the way it can see trends and, and changes and shifts that are subtle. That, but, but valuable to, to recognize. Yeah. All you really have to do is show the AI how, how your fundraising processes are structured, and that’s where, you know, my framework comes in. It provides a structure so it knows how to assess a given record against that and it can even go outside that record. It, it can know, for example, Um, it can know a lot of information about, say, say, special events that your organization has held and, and, and grab that information and how it might, knowing the donor went to that event is, is important and it can take that into account. As a matter of fact, it is far better at that kind of thing than any human I know, unless the, you know, even a human who does nothing but that 24/7 couldn’t possibly hold a candle to what AI can do. Yeah, that, that’s the, that, that’s the capacity I, that’s the capacity that’s the division. It’s not just bandwidth and time, it’s, it’s, it’s capacity to see trends that, that, it’s just, there are too many data points for us to, to recognize what What the AI can, can recognize patterns that it can find. All right, let’s, all right, so that, that’s a healthy, that’s not just the, you know, you don’t just call it the, like, the right division of labor. It’s the healthy division of labor. Uh, the first, the first part of your, your, do you do that part and then, but we need to make, we need to be the ones that That communication that results in those in that. Human decision making needs to be ours. So that’s the other side of the division of labor, you know, the AI is amazing, but we have to stay in the process, otherwise, it’s not a healthy division at all. That’s the point. It’s time for a break. We are sponsored by the Bridge Conference produced by AFP DC and DMAW July 29th through the 31st at the Gaylord National Resort and Convention Center in National Harbor, Maryland. More than 2400 professionals will gather at bridge. Tony will be with them. The question is, will you? Thought leaders from nonprofits, associations, foundations, hospitals, higher ed, faith-based, and emission-driven causes across the country come to Bridge, to discover new ideas, solve real challenges, and connect with smart people shaping the future of our industry. From 125+ educational sessions and hands-on pre-conference workshops to Bridge tech, the faith and fundraising forum, and inspiring keynote speakers, Bridge offers something for every mission and every role. The conversations happening at Bridge will shape strategies, careers, and organizations long after the conference ends. Don’t hear about it afterward. Be in the room. Register at bridge.org. It’s time for Tony’s take 2. Thank you, Kate. The beach days are back. Summer is here. And I am enjoying as much time as I can. Out on the beach in the sand under an umbrella. Like almost meditating. Just looking out at the ocean and uh enjoying that, enjoying that. I hope That you will take time for yourself, your family. Yourself too, though, especially. Uh, this summer sometime to get away, relax, rejuvenate, refresh, just change of scenery. I hope you’ve got something planned for your summer that is uh. As special to you as the beach is for me. Just some encouragement, encouragement for your summer getaway. That’s Tony’s take 2. Kate My family and I, we’re going to the camper this weekend, and we’ll be there for almost 2 weeks. Outstanding, outstanding. You love those, you love those getaways, right? Yup, it’s nice and quiet. I mean, cause there’s no like highway around us, as if like we’re at home, there’s a big highway. It’s practically in the back of our backyard, but in the camper’s nice and quiet, you can’t hear anything, wildlife. Nice. Very nice, the sounds of nature. We’ve got Beauco butt loads more time. Here’s the rest of a skeptic’s view on the value of AI in fundraising. Well, folks are gonna have to read the book, uh, for, uh, explaining all five of these. We’re just gonna, we’re gonna hit just a couple of highlights for the, from the five pillars. Um, I’d, I’d like to talk about the, uh, the virtuous data cycle. How AI gets more insightful through, uh, through iteration, through, through the, the data that humans are adding, that virtuous data cycle. Yeah, you know, that in, in a certain sense, um, Uh, we already have something like that, you know, we have usually in a more developed development office, there’s somebody who runs the, the database, you know, the online systems, and they feed things to the other development officers. And all that. And, and in a, in a well-run office, information that, that crops up about a donor that’s appropriate for, you know, to be entered will, will, will be entered. Um, But the reality is in the real world, um, records are, are, are, are really rarely that, you know, that complete. And, but now with AI available, we have a huge incentive to constantly be updating each donor record. If we have a conversation with someone with a donor in the parking lot, or we run into them in a restaurant and there’s a quick conversation or, uh, you know, you name it, we now, we now need to enter that information into, into the system so that the AI becomes aware of it and can take that all, take all that into. You know, into consideration, so. Um The the more, the more that we learn about the donor, the more human interaction we can have that’s meaningful, the more information that we learn about that donor that goes back into the system, so we get this cycle going. And the system just gets smarter and smarter and we’re able to serve that donor better and better as a result. Right, right. That’s the, uh, the virtuous data cycle. And I want to talk about your, uh, fifth pillar of the human-centered AI framework, the ethical vigilance, because it, it, it, it centers the donor. And, and governs all the other parts of the framework, but putting the donor’s interests first. When I was Writing the book, I built a system, an AI aware system with donor records, um, and it became the, um, Uh, portfolios, it’s the, the author forget. It’s the practice portfolio. I’ve got, I, throughout the book, I’ve gotten to know these folks, uh, Doctor, Doctor Sarah Huang and, uh, Robert Okafor and, uh, the Whitfields, who, who lapsed for a few years, but they’re still engaged. The Whitfields are still engaging, but, but they haven’t made a gift. And, uh, Maria Chen. The, uh, oh, and who’s the doc, oh, Doctor, right, Doctor Sarah Huang. She, she, she sees hungry hungry kids in her, in her practice, in her medical practice, and she gives to, uh, uh, nutrition education. So you, you get to know these folks, but they’re all part of this, the sandbox that we can all play in. In the practice portfolio, but I don’t wanna, I don’t wanna come off the ethical, the ethical vigilance pillar of your, of your framework. Yeah. Well, so as I was, as I was building that system for my own experimentation with AI and all that, uh, and I was dumping more and more hypothetical information about these donors, and these are the same donors that are mentioned in the book, so you get to, you get to see them again in the Uh, practice portfolio, which is an online system that you can access for free now. Um, and, and then I began to, to experiment by asking the, the AI to give me a Monday morning, uh, review of, of my donor base and to make recommendations on donor contacts and things like that. And I found that it was so good at it that it would make recommendations on information that Um, I felt as a human was. It was definitely in the in the system, so I could get why the AI was looking at it. It was too good at making suggestions that would cause the donor to, to, to act. In other words, I was, I was becoming increasingly uncomfortable with some of the decisions the AI was trying to make. Because I thought it was crossing a line, and, and at first I couldn’t quite figure out why I was feeling so uncomfortable, but the more I worked with it. The more I realized that as a human. I had a a sense, I don’t know, call it, call it my decades of experience working in development offices. I don’t know what it was, but I had a clear sense. of propriety. And when, you know, when you, when you work with donors, sometimes you’re in such a position that you know, you can get them to make a gift, and it’s not overreaching or anything. It’s not like you’re forced, but, you know, something inside of you is telling you, maybe this isn’t the time to push. Maybe I shouldn’t be using this piece of information that I got in a, in a, in a conversation. To frame my ask, you know, it’s, it’s, it’s a human assessment. And I, so I thought, well, how in the world am I going to write about this as, where is a bright line? And there, there really isn’t a bright line. So, I, I asked a question, um, would, if the donor was aware of my thought processes and what went into this solicitation or this communication. Would the donor feel like I was handling them, you know, like trying to get a result, um. Uh, transactional, uh, or not, right? Um, or would they feel that I was honoring them. And so I came up with this handled or honored. Uh, test. And um, You know, it, and it’s, it’s been expressed by others, uh, and I’m not the first to sort of come up with this idea, um. Uh Uh, Professor, uh, James that had similar, similar ideas, uh, expressed differently in some of his books, but it was one that, um, I needed to put in there. That’s Professor Russell, yeah, excuse me, yeah. That’s OK. Russell James at Texas Tech University. Yeah, Russell James. Yeah. So, you know, he, um, He’s endorsed my book, I’m happy to say as well. So, after reading it, and so we had a, a, a brief chat about, you know, that similar perspective. But, you know, AI is terrible at making that judgment. It’s just, and that was what worried me the most, and I felt that the human needs to know, uh, when to make that decision. So you need to train AI when to pause and ask the human fund development officer to make a call. And so when I wrote up this online specification, I actually include the signals that the AI would understand to stop and say, hey, you need to make a judgment here, not me. And so if you have your AI read this online specification before a session, it’s going to understand when to, when to pause and, and call out, uh, uh, you know, your. Duty to make a decision. So that’s a guardrail, and that guardrail has not been existing in the, uh, so far in our sector and the AI systems that have been bolted onto these, these, um, These systems, and it, and it’s high time that we, we do that because otherwise, AI is fighting us and it’s even becoming, it’s even fighting the very notion of ethics in our profession of putting the donor first. And we can’t let that happen. We as a profession have to respond and take control of. This or the software vendors are going to do it for us and you know, I know that they’re, they’re, I’m not here to. To, to critique them, I think that they have different goals and objectives than we do. And so we need to assert ourselves, and this is one way of doing it. Yeah, and you, you give folks that, that specification. We can, we, we, I release it to the public. It’s under a public license. Anyone can use it, even the vendors can use it. I don’t, I’ll never be paid for it. That’s not the point. Um, and they can modify it, uh, if they want to. Anybody can modify it and do what they want with it. So it’s, it’s released to the public and free of charge. Let’s talk a little more about the practice portfolio that, uh, sort of accompanies the book. It’s a, it’s a sandbox, like you said, of Fictitious donors representing different people, different stages of giving, different stages of engagement. Um, and as I was saying, you, you get to know these folks throughout the book, um, There’s also the guy, uh, David, who’s, whose family was fed by the, by the food pantry and his son is now volunteering there. Uh, so just, just say a little more about the, the practice portfolio because it, it can be fun to do the exercises, uh, uh, and see the people, see the records as you’re reading the book. Sure. So, um, you can, you can get a free account, um, with, uh, on, um, Uh, uh, with a website called Notion, and Notion is basically a, a note-taking, um, system, but it’s far more than that. And then apply the portfolio to, to your free notion account, and that’s free. And then if you want, you can for a few bucks a month, you can have the AI from Notion activated. And so what I’ve done is I’ve put the very donors discussed in the book, these are fictitious donors into the system which I call a practice portfolio. And the reason I offer it to readers or frankly anybody who wants to do it. I want them to experience what it’s like to work with an AI that’s operating within the framework, and I want them to see actual fictitious, but actual donor records. That are um tracking the very behavior that I write about in the book. So the book is very tightly coupled with the the practice portfolio and I wanted to give readers a place where they can go experiment with with AI, um, with donor information and query the AI and see how it responds and and what it has to say about. Um, donors and, and all of the stuff that I talk about in the book, but I wanted a safe place for them to do it. I didn’t want them to have to go to, you know, their own organization’s Blackbot account or Donor Perfect account or whatever. I want to be able to work in a safe place where they can’t do any harm, and where they’re not working with real donor data. And so I built this system for that purpose, and It’s, it’s a great way to really experiment. It’s like if, if the book was a cookbook, this is an actual kitchen where you can go try out some of the recipes of the book in a safe way, uh, either for free or for very little, you know, if you want the AI notion charges a little bit of money for the AI, but otherwise, it’s completely free. And that’s the, again, that’s the practice portfolio, the practice portfolio. Yes. Um, one of your chapters, you, you know, you, you, you have several chapters devoted to different Um, different. Needs in, in fundraising, uh, the annual fund, major gifts, uh, stewardship, recovering lapsed donors. Let’s talk about your annual fund chapter, how AI can work to support your annual fund, and, and you see the annual fund as a, as a campaign. Yeah, well, you know, um, the annual, relationship building campaign even. Yeah, I mean, we, we, we tend to look at the annual fund as sort of a massive letter writing campaign once a year or something like that, maybe a phone call campaign, whatever, but not so much as a, you know, like an actual holistic campaign such as say a capital campaign might be. And there’s a good reason for that. Up until now, there were only so many resources in a, in a development office that can be devoted to something like this. And so we tend to take our donors and segment them, you know, our, our, we have our top tier and we have a lower tier and a lower tier from that. And so we can only give our attention to the top tier of donors, and that’s pretty much it. And everyone else gets segmented and they get. You know, uh, mass communications based on their segment and where they happen to fall on the, on the donor pyramid or donor life cycle. And, and that, that, that by itself was, was a massive step forward and only really kind of happened when computing came into its own and the internet came along. But now with AI we have the ability to treat all of our donors um with some degree of, of focus and and attention because AI is able to To, to let us see each donor more as an individual than somebody who happens to fall in a given tier on a on a donor pyramid. So my thought was. The, the annual fund can, can be transformed into something much more akin to a campaign and not just sort of it, it, it, you know, once a year thing, but an ongoing, uh, never-ending sort of campaign that, um, treats each individual, not where they fall on a, on a given tier, but where they are in their journey with our organization. And everyone is at a different place, and even the smallest donors, uh, have a place in the sun under this system because they will not be, um, lost in the pile, if you will, because the AI can, can look at them as individuals and spot opportunities and and tell us, look, you have an opportunity here to, to interface with this donor as a human, and perhaps Deepen the relationship with that donor and they’re no longer just In some segmented tier of, of a donor pyramid that gets a a a a mass email, they are now viewed as individuals. So it starts to look much more, I don’t know, campaign-like or personalized, if you will, than it it ever could be in the past because AI lets us do that. You’re, you know, as I said early on, you’re, you’re concerned about the human element of fundraising. You know, as a, as, I said, you, instead of CRMs, you call it an RBS, you know, a relationship building system. Your, your annual fund, you position as a relationship building campaign. So while you’re, Talking throughout the book about the, the, the value of AI in, in seeing the things that we’ve, we’ve been talking about and, and assisting sort of side by side with the fundraiser. you know, it’s consistent that you, you, you want the, the human element, uh, uh, never, never to be sacrificed, the human element of fundraising. No. We have to maintain You know, the human element. And with, with the AI understanding that properly, it will actually be our ally, and it will know when to pull back and when to have you make the critical calls. And even I mean, they never sending out a communication that it writes by itself, you, you, you, you own that communication, you revise it, uh, you, you, you don’t, you don’t just let the AI run amok in that either. And that’s, that’s critical too. So the human has to be present at every step. But never before have we been able to sort of break down the walls and look at even the smallest donors. Um, as individuals, rather than sort of falling in a segment of our, of our, of our donor pyramid or however you want to take a look at, you know, however you want to think about it, the donor cycle, if you will. So, we, we have this wonderful opportunity, as long as we constrain the AI to, to, to let us be the humans. Um, and not fight us on that, because that’s what it, it wants to take over so much of what we’re doing, that if we let it, then, then we, we will hurt philanthropy because the donors will understand that there’s now a distance between us and them, and they might not be able to put their finger on why, but they’ll feel it nevertheless, and they’ll, they’ll pull back. And that’s the opposite of what we want. And that will have been our fault because we allowed it. Yeah, it will have been, yeah. Exactly right. Let, let’s make the, uh, the final chapter we talk about, uh, the, the, uh, the stewardship, stewardship. You talk about seven touches, um, and how, The, the AI tools can help with uh personalization and and consistency. Well, it’s, it’s, it’s, it’s been accepted for quite some time in fund development in our, in our sector that, um, donors need to receive communications, um, from us and, uh, and, um, and you write about it in your your forthcoming book, I, I, I must say in, in a, in a very compelling way. Um, even a, even a modest communication can keep a donor loyal to your organization and result in, in that, in that gift. Um, But far too many donors are, are forgotten. Maybe they’re so small that they just get a, you know, a thank you letter and, you know, but maybe they’re giving 3 or 4 years like that, but nobody notices, you know, they’re, they’re just, those signals are being missed. Well, that falls under stewardship. Those signals should not be missed. And now with AI looking at our donor base and understanding how the fund development works in our office. Will, will alert us. Perhaps in that Monday morning review that I talk about in the book, that that donor has, has Been engaging with us in ways that we have not noticed up until now, and we should be responding in a different way. And here’s how we could be responding. And the whole 7 touches thing, and it’s rather arbitrary, you know, 7 touches. I, I didn’t want to reinvent that wheel. That’s, that’s sort of an accepted thing out there, and you could say, well, 7 touches, 2 touches, whatever. I went with 7 because that wasn’t the point. The point was, we should be engaging with those donors and not letting them slip between the cracks. We humans should be engaging, and not just engaging one way, but several ways. Um. Uh, phone calls, emails, in-person visits if we can, or inviting them to an event that maybe they wouldn’t have been invited to, or, you know, the, the communications need to take place. And now the AI can track that for us beautifully. And it could even suggest to us how to communicate and Uh, it will even tell us what we can say in some of those communications, and that’s fine, provided we own those communications and we work them so that they make sense to us as humans. So, it’s a boon to, um, stewardship, um, and we should let the AI help us there because it’s brilliant at that. It, it is just brilliant at that. The book is uh holding fire. A skeptic’s framework for the fundraiser with AI at your side. You’ll want to look for Steven Christopher Nill, not just Steve Nill, but Stephen Christopher Nill is the author. You’ll find the book at Charity Channel. Dot com. That’s the best place to get it. Steve, thank you for a, a, a, a thoughtful book, uh, a, a, a human-centered book, uh, a, a book that celebrates the humanity of fundraising. But also points to the. The value of the, uh, the AI tools, uh, at, at our side. Well, leave us with some parting thoughts about that, that human AI, uh, potential. You know, I, I, as I was researching and writing the book, I, I kept coming back to the metaphor of fire. You know, AI is so. Uh, transformative and not just in, in our sector, but in so many other spheres. That It feels like We have, we have discovered fire all over again. It’s that powerful, maybe even more powerful. And so Fire has a potential. Um, to. To warm us, to be a good positive influence for us, but misused. Used without care, without a framework, if you will, without the structure, without the understanding of, can, can burn us. And in our context, it can burn and destroy our relationships with donors who support our organizations and underpin all of philanthropy. And so, you know, I don’t want to be sort of melodramatic about it, but I, I really think. AI is the new fire. And so the book, it’s called Holding Fire, because that’s what we’re doing. If you look at the cover, it’s a pair of hands holding fire, but if you look closely, it’s kind of a digital fire. So that’s the metaphor and, and that’s why I called it what I did, but I, I think it really encapsulates. Both the promise and, and the risk, uh, that AI poses for us, uh, in the nonprofit world and particularly in the fund development arena. Steve Nill, Stephen Christopher Nill. Thanks so much. My pleasure. Next week, confessions of nonprofit social media managers and convert your member website into a thriving community. I know we had said last week that that was gonna be this week, but Steve Neill’s book got released. I want to have the bragging rights to be. But one of the first. We, we might even be the first. It depends if somebody puts their podcast out before this one. But, uh, good chance we’re the very first podcast he talks about his book on. So, that’s important, bragging rights, very important. If you missed any part of this week’s show, I beseech you, find it at Tony Martignetti.com. We are sponsored by the Bridge Conference. Tony will be with more than 2400 nonprofit professionals at Bridge, July 29th through the 31st in National Harbor, Maryland. Info and registration at bridge.org. Our creative producer is Claire Meyerhoff. I’m your associate producer Kate Martinetti. This show’s social media is by Susan Chavez. Mark Silverman is our web guy, and this music is by Scott Stein. Thank you for that affirmation, Scotty. Be with us next week for nonprofit Radio. Big nonprofit ideas for the other 95%. Go out and be great.