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What the Fundraising
258: A New Paradigm: A Preview of the FundraisingAI Global Summit with Woodrow Rosenbaum
00:42:18
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- [00:00]
A
Change is never good. Nothing good ever comes of it. And I think that's how a lot of people feel about change. Like it's never gotta be comfortable. And getting comfortable with that discomfort is just a necessary component of any kind of change, any positive change requires. And this is no different.
- [00:24]
B
Hi, everyone, this is Jen Lau from Fundraising AI and I'm excited to bring you a very special episode about our upcoming global summit on September 15th and 16th. If you're not already registered, we'd love to see you there. You can register anytime for this virtual and free conference at FundraisingAI Summit. In this episode, our very own co founder Mallory Erickson is joined by Woodrow Rosenbaum of Giving Tuesday to explore the primary themes of the summit, such as human centered AI, leadership and governance, cultures of innovation, and even tough questions about the environment, equity and generative AI. Stay tuned to learn more about what's to come and our top session recommendations for each theme as we explore the world of responsible and beneficial AI and fundraising together.
- [01:13]
C
Hi, Woodrow, how are you?
- [01:15]
A
Hi, Mallory. I'm doing well. How are you?
- [01:17]
C
I'm good. I'm excited that we get to have this conversation today because I feel like we blinked and we're already a few weeks away from the Fundraising AI Global Summit. And the agenda. As I was going through and preparing for this conversation today, I was just blown away by the agenda. We have so much good stuff on the horizon September 15th and 16th, but I want to jump right in because you are sort of constantly seeing and hearing the conversations that are happening around AI in our sector in a really intersectional way. And one of the themes that has really been there from the beginning is this tension between people and technology. And there are a lot of different layers to that. But I know in terms of amplify impact and the way we've thought about the summit this year, really keeping people at the center is a big part of how we're thinking about the content. And so I'm curious from your perspective, like, how do you feel like we can keep people and not just productivity, which often seems to be like the dichotomy at the heart of how we're thinking about AI.
- [02:24]
A
That's a really great question and I think a good framing question in part. Part. I guess I'm. I'm encouraged. When we did an AI readiness survey asking people who work in the nonprofit sector around the world about their engagement with the technology, most people were finding ways to work with the tech. And I think that that's encouraging in part because I'm always worried about the nonprofit sector's ability to keep up with technological advance. And we don't have a great track record of that over the past decades. And I think that that's part of the answer is the best way to ensure that we're, that people are at the heart of this tech is that we're using it and we're familiar with it. And that doesn't necessarily mean taking it for granted or not being cognizant of challenges or potential harms. But it is critical that we are engaging with the technology if we're going to be able to use it not just effectively, but also appropriately. I do have some other concerns though, because you, when you mention this question about people versus the productivity, I am concerned that our industry is adopting this technology to do a kind of mediocre job more quickly. And that is not going to serve us. We are, we're not going to realize transformational benefit from this transformational technology if the only thing we do is the same thing we've already been doing much faster. And so it is. Look, it's great if we can use this technology to improve our efficiency and allow the people in our organizations to do the things that only people can do and address some of the drudgery is no different than any industry. Right? Like there's just things that, that we can increase our productivity and get more done. And that's especially useful in an industry like ours that, where everyone is stretched so thin. But I would love to see more expansive thinking about how this technology might transform our organizations, our structures, and the impact that we're having in the world beyond just, oh, this will make my job easier.
- [04:41]
C
Well, you just said something that I think is super interesting and I'd love to dig into for a moment is I had used the word productivity and then you used the word efficiency. And I wonder if there's a real big difference there, right? Like, because productivity is like this feeling that we have that we were productive. We checked this many amount of boxes on our to do list today. But if those boxes are not particularly efficient tasks towards achieving our mission, then it really is just productivity for productivity's sake. And what you're talking about doing these mediocre things faster versus like efficiency of delivering programs and services or being able to like have kind of like a core mission fulfillment component happen better.
- [05:30]
A
Right? Which really is what, when we talk about productivity, that's what we should be really thinking. Not about getting the job done more efficiently, but accomplishing our task, which is not the same thing as Checking a box, like you say. And I don't think there's enough thought into that. There's a lot of constructive conversation about responsible use of that technology. But we need more imagination around to what end?
- [05:58]
C
And almost like the responsible use of our time. Right. Because I think that is one of the big things that we see with AI is. Is the excitement sometimes around the technology for the technology's sake. And then it's like, cool. You found a way to, like, edit videos with weird, like, cats all over them. And that's very cool, I guess. But how does that relate to one of your biggest pain points and challenges as an organization?
- [06:28]
A
Yeah, 100%. It's very easy to be like, thinking, I got to get some AI as opposed to what problem am I trying to solve? What is the right tool for solving that problem? I think, like, with any technology, and arguably particularly this technology, there is a hype cycle. And one of the benefits of that is it gets. I have noticed that it is driving people in organizations to engage with this tech and that hype has some benefits beyond just whatever's fancy and new. It's. If you want. If you want to use this technology, well, you need some good data. And if what. And if the first step in your journey on AI is improving your data environment, well, you. This is great. A lot of organizations should have done that 10 years ago. If this is the. If this inspires some of that to happen, that's great. And also the tools enable that more effectively. I hoping that we start seeing, particularly when we're talking about fundraising, is thinking about more about how does this technology allow me to do things I wasn't able to do before, reach more people more effectively, bring a more genuine experience, learn more about my mission and how it resonates and not so much how do I do better wealth screening, how do I like. It's fine. We need that. Okay. It's not just saying we don't do that stuff, but that's the transformational opportunity is what does it unlock beyond doing what we're doing now better?
- [08:14]
C
And that's almost like. I mean, I think it's sort of like a third category from the question I originally started with, which was like, people at the center versus productivity at the center. And this is sort of like the work at the center, which, when done intentionally and well and more efficiently and without so many pain points, is really going to serve the people and keep people, both beneficiaries, but also the folks inside these organizations at the center of why it's Being used, how it's being used, and the impact that it's ultimately having.
- [08:45]
A
Well said.
- [08:49]
C
Well, there's a lot. I mean, so I feel like we can't talk about the like, people component without talking a little bit about this balance for them between or the experience that a lot of them are having around being overwhelmed. Right. Like you were talking about. There are some benefits and drawbacks to the hype that's happening. One of the drawbacks that I see, and maybe hype is the wrong word to connect it to, but with the energy and amount of content we're seeing around AI is this overwhelm. And I worry sometimes that the more overwhelmed certain people get around, what tools should I be using? How should I be using them? I'm afraid of not using them correctly. You know, the. As that fear grows, we actually fall more into the, like, productivity for productivity's sake because we lose that depth of, like, inquiry and curiosity because we're just overwhelmed and afraid and want to be like, yeah, I'm using, I'm using the latest tech. How do you think about that? Like, interconnection.
- [09:53]
A
So, I mean, I do think, and this may sound a bit like a contradiction initially, like, I think that some of the more obvious benefits of the best established tools and products are productivity tools. And if that's the easy way in to getting comfortable with the technology, that's fine. Right. So it's. I'm not. I think it's okay to have that whatever is the path of least resistance to start building that competency and familiarity. That's okay. I'm just hopeful that that then enables more expansive transformational application. You're not going to be able to tackle everything all at once. I think it is really, again, it's encouraging that most people in the sector are, are starting to find ways to use these tools and there's more and more kind of on ramps available to do that. And I think if you have some basic building blocks, some. Some key policies and frameworks that will help guide how you, what you're. How you conduct that journey for yourself and your organization, then that's sufficient training wheels to then not worry about having to know how it all works all at once.
- [11:06]
C
Yeah. Okay. I love that and I totally agree and I'm glad you said that about the productivity piece because I feel like for some folks, yeah, that might be like, they're like, well, maybe I am doing a bunch of mediocre things, but I need some time to figure that out even. Okay. To get the capacity to do that use the productivity tools that feel the easiest for you to adopt and see real benefit from, and then slowly. But I. But we shouldn't stop there. Right? That's not the best case. No.
- [11:35]
A
We think about what outcome this technology might have for this sector five years, ten years from now. I hope that our ambition is much bigger than it was easier for us to find donors or we. Our CRM became much more manageable. Right. Like, great, that's fine. But I'd be interested in what it does for our missions and the meaning that we bring to the people who support our missions.
- [12:07]
C
Okay. This actually leads really well into the next thing that I want to ask you about. But I do want to say for folks who are on here and listening, if overwhelm or, you know, discomfort around AI is a topic that feels particularly resonant with you. We have a number of sessions at the summit focused on this. I'm going to drop the titles in the. In the LinkedIn chat so you can see some of the ones that are coming. Make sure you're registered for the summit. But we definitely are going to be digging into this like people first and what that means in terms of how we take care of ourselves as we're using these tools, but also how do we balance that working smarter, not just faster, with AI components that Woodrow is talking about, which I so appreciate. Okay, so what you were just saying really leads into this piece around innovation and culture and how those things sit with a lot of fears of. Around taking risks and what you're talking about, that type of transformation, that thinking bigger, the. You know, what's really possible, if those involve a lot of change, a lot of change in how we think, a lot of change in how we do things. And we have seen, and you and I have talked about this a lot, the resistance to that type of change and the fears around risk taking. So how do you think? I think there's a big conversation here. But to sort of start us off, how do you feel like we can spark innovation in cultures that feel fear, risk?
- [13:45]
A
There's a great line from a play written by a guy named Eugene Strickland. There's one of the characters says, change is never good. Nothing good ever comes of it. And I think that's how a lot of people feel about change. Like, you've never got to be comfortable, and getting comfortable with that discomfort is just a necessary component of any kind of change, any positive change requires. And this is no different. There are also real risks of harm that come with the adoption of this Technology. And there are both ethical and practical considerations that need to be addressed. And this is why. I mean, the FAI framework is, I think, a really good way, like a pragmatic way of guiding people's journey into using this technology. Again, I think it's very encouraging that most people are. I think part of this is people need to interrogate their own feelings about this, because I don't hear a lot. But we do hear from some folks who are saying, you know, the risks are too great. I'm not going to do it. I'm opting out. And I have no issue whatsoever with that as an ethical standpoint somebody might take. But I don't think it's a very practical approach. The fact is, opting out is not going to be easy and might be impossible. And it's very difficult. I mean, it might, in fact, be easier just to have to completely opt out than it would be to dip your toe. I think the real risk is the folks who are not going to. Who are going to engage a little bit and not enough with this tech and aren't going to be situated to address those ethical and practical concerns because they're not engaged enough with the use of the technology. So I do think that if you're going to use it at all, you better use it and you better get into it. And I think that it's also. I was saying, like, I think interrogating your feelings about the technology is important. Are you concerned about any particular ethical issue, or is that a reason for you to not do the uncomfortable thing? Because if it's the former, great. There are resources available to help you navigate that. And if it's the latter, you're just putting yourself in a position to not be able to manage that particular risk, and that's not going to be better.
- [16:13]
C
Who? Yeah, I mean, I think this is, like, at the crux of so much of the. What I'm concerned about with our sector and a lot of the conversations I'm hearing around AI is that we definitely need to be having conversations about the real concerns and valid concerns around the use of AI and how we engage responsibly with these questions. And I'm really proud of the summit this year for having a panel on AI and the environment, like, what nonprofits need to know, talking about, like, will generative AI be a force for good in the social impacts sector? And then, you know, trust and nonprofit mission. I'll drop those in the chat, too, for folks. But I think, like, it's super important that we're Having real critical conversations around those things. And I definitely feel like I see and hear a lot like dismissiveness or shutdown around AI for some of those reasons, when, without even being open to nuanced conversation. And I'm really concerned about all of those folks not being engaged in this conversation because I'm like, the only way we're going to influence better decision making, better policy, better, less harmful impacts, is to all actually be engaged in the conversation of what's happening, not closing our eyes and saying, well, I'm just not going to participate.
- [17:40]
A
Absolutely. And that, I mean, it's a question of how to what degree do we want to be in the driver's seat. And mitigating these risks is going to be best if we have some agency. And that does mean engaging in the discourse and the use of the technology. And some of it's fun, right? Like, we have Matt Price on our team, who's doing a session at FAI this year, leads an AI learning group at GivingTuesday. And we have a Slack channel where people share stuff they've done in ways they've used the tech. And it gives us a really an easy peer learning environment where we can learn from one another and try things out and in an environment where we have guidelines that can help us do that in a way that is safe. And that just does an enormous amount for helping people to get over that discomfort and have a little bit of fun with learning this. And I will say, it's also, this is a technology that for most people, it's a much less of a technical skill. Right. You're not. You don't even need. We're not talking about learning to code. We're right. This technology is actually very approachable.
- [18:49]
C
Yeah, well, I mean, I obviously feel that way because I'm somebody who doesn't know how to make a reel on Instagram, but somehow leads a technology company now. So, I mean, I couldn't agree with that more. And I also feel like, you know, as somebody who's neurodiverse, it makes information more digestible and approachable. I'm able to, like, actually grapple with subject and topics and engage in things like I've never been able to before because I can easily sort of translate them into how my brain processes things. And there's a lot of accessibility there that really hasn't been available with any other tool. And, you know, it's interesting, like the responsible, like that piece about the responsible and ethical components of it, like when I was starting to build practivated I obviously the fundraising AI framework was like a cornerstone to how I wanted to think about building this tool. And a lot of that work was informing how I was thinking about it from the beginning. But if I'm being totally honest, it wasn't until I was like, digging in and building it that then I was able to start to see how it could be unethical or biased or have these other like. Or what would be irresponsible about it. I couldn't have identified all those things without ever starting to build it. And I just think that's true. Like, if we are the. Obviously we're here at fai, like the responsible and beneficial use and the ethics are like, core to how we think about this. But you are never going to get to a place where you feel like you have that completely figured out and then you're ready to jump into the tools. Because it is an ever evolving and iterative process as these tools change. And your orientation and context, even for those conversations, needs to be influenced by being in there.
- [20:42]
A
Yeah, that is the way to get used to it. And there's plenty of ways that you can do that in an environment that's safe for that experimentation. I had a similar experience. So I run LLM models locally on a local machine for a variety of reasons. In part because I wanted to learn a little, a little bit more under the hood. And one of the sort of turning points for me was playing around with the parameters that I don't really fully understand. Very recursive way. I tend to get chatgpt to explain them to me, playing around with them and finding little tweaks to the models that resulted in just pure gibberish, like absolute nonsense coming. Like, not just wrong or hallucinating, just literally incomprehensible gibberish. And I was looking at the wizard of Oz behind the curtain. It was like, wow, this really is just a statistics machine. And it's very impressive what it can do when it's tuned well. But it was, in a way, it was almost kind of a liberating experience to be like, it is really just not that mysterious. And seeing how it broke, what I found very interesting in the extreme, like we've all experienced, it gives you the wrong answer and it sounds confident, that kind of problem. But getting absolute gibberish really helped me to understand, like, really understand why. Why are these things not always super accurate or, or appropriate to the circumstances? It's a prediction model, really. Only that. Just pretty sophisticated prediction model.
- [22:16]
C
Yeah, it's super interesting. And I also want to go back to your point before that, around the. As complicated as it could be behind the scenes, there's also just a million accessible ways to engage with it that you don't have to have any technology skills to handle. And one thing I want to make sure I say out loud, because I did a train, an AI training a few months ago, and at some point in the training, I could just tell that everybody in the audience was like. Was, like, stuck. And I didn't really know why, but there was something happening in the room. And I was like, okay, tell me how you really feel about AI. Like, how does it make you feel? And somebody finally raised their hand. They said, I feel like I'm bad at AI. And I was like, what does that mean to you? And everyone was sort of nodding like, yeah, I'm bad at AI too. And I was like, what does that mean to you that you're bad at AI? And the woman was like, well, I put into Canva a description of the image that I want, and it comes back with four arms. And I was like, oh, yeah, for all of us. And I was like, you're not bad at AI. I was like, these tools are developing, and many of them are inconsistent or they're releasing them before they're gonna. I mean, we are seeing in real time how the models are improving their ability to create photos with text on them. Like, a year ago, none of that, you know, existed. And so I want to encourage folks, like, if you try something and it. You break it or it breaks or whatever. The whole piece of generative AI, to me, that's so exciting. That's so different than other technology that really does require mindset shift, though, is that you keep going, you keep talking to it, you keep. You ask it, the next thing you have it change. Like, that just isn't the mode that we've engaged with technology before this, like, building on. And so I feel like people get to a moment where something breaks and they're like, oh, I'm bad at it. I'm bad at it. And I'm gonna apply it universally to all AI. And I just. I'm the one who can't figure this out. Have you seen similar, like, patterns?
- [24:24]
A
And it's frustrating because the other reaction that is also a perfectly reasonable reaction is this thing is garbage. Why got forearms not useful, right? And creating prompts as an example, right? Like, that's a skill. And the best way to learn that skill is, in fact to work with the tool and ask it to do something and understand how it was wrong and refine how you're engaging what your inputs are to get the outputs that you want. And that's true whether you're describing an image or you're trying to get the thing to write some code or extract some information from data or whatever it happens to be. I think that skill is going to develop the technology. You're right. The technology will also get better. We are going to. The best way to develop our skills is going to be by telling it to do something and seeing how it gets it wrong and revising our inputs so that we're. It knows better what we want and we get better at asking for what we need. Where the risk comes in is when you're the. There's uncertainty in the outputs that you get, right? So if you're asking for an image for your organization and the people have forearms, you know it got it wrong. If you're asking it to describe, based on the impact data from the last 50 years of your organization, what the best interventions are to address bacterial infections in a population, it may not be so clear to you whether the output was right or wrong. And that's where the risk comes in. But there's plenty of opportunity for us to learn how to do this prompting better where the risks are lower. And we can do that learning, and then that then equips us to better address and use these tools in situations where the risk of harm actually matters.
- [26:12]
C
Okay, so that actually brings me to a question I wanted to make sure to ask, which is about, like, AI governance. And I'm curious, like in your mind, like, what does kind of good AI governance look like? Thinking about the goal of, you know, protecting trust and charitable giving. But like that example you just gave, right. Has real implications if we don't notice it, don't check it. So how do you think about that?
- [26:37]
A
Well, I mean, again, the fundraising AI framework is a really good place to start. And one of the interesting things also that can be done here is to build a policy. Like using generative AI to build a policy for your organization is also a fairly simple approach and probably a good place to start. I mean, what's interesting and important to note, I think about that FAI framework is there's no technical components of that. Right? There's no specific technical compliance component of that framework, because it's not about that. That doesn't mean that there aren't components that relate to data privacy and security and data ethics, and all of that is really important. The other things to note, though, about this framework that that are part of why it goes beyond kind of a policy is continuous learning, collaboration as core components of a framework. So we think about that framework as actually like not just being a policy. We try, we say we're going to adhere to and then hope we do and delegate to some technical person to ensure that we're complying with that. If we think about this framework instead as everybody who's using these tools for whatever purpose is going to be guided by these principles of collaboration and continuous learning, this is how we're going to make our, ourselves and our sector better and more effective and how governance can actually be a tool for productivity effectiveness. And then beyond that, just try not to do harm and be careful with people's data and have policies around how that's done and make sure that people are provisioned with the tools that they need. I think the way I think about the actual sort of practical implementation that of the technology into organizations, I think organizations will tend to think about prohibitions. It's gotta be more effective and it's going to mitigate risk better if you think about enablement. So what are we trying to enable? Understanding that people are going to use and try lots of things. And what we want is an open dialogue in our organization. We want principles that we follow and data and privacy compliance that is managed carefully. And then also things like, hey, I'm interested in using this tool in this way. Who can help me figure out how I do this according to our framework? Or I'm looking for a solution that will help me do this. As opposed to we are prohibiting the following uses or tools. Right? I mean, there may be some requirement for that. But as the core principle, thinking about governance as enabling an organization to do something responsibly and ethically as opposed to preventing an organization for doing, from doing things unethically or, or irresponsibly.
- [29:27]
C
Okay, I love everything you're saying here. I appreciate so much. And one of the things you sort of answered my next question, which was about like how leaders can responsibly steward their organizations when it comes to this like super rapidly changing technology. And part of what I'm hearing you say in there is one like, focus on guidance about what you do instead of what you don't do and how you do it. And then also the preparation for this like iterative, dynamic, ever changing process. So maybe some of what's happening and I'd be curious for your feedback here on the leadership level, like, do you think leaders are kind of like waiting for things to like chill out because they're like, oh, there's this big, you know, experience explosion of change. I'm going to get a handle on it. And then once I do, I'll get. I'll level up my team around it. But there's no, like, getting a handle on it because it's growing so fast.
- [30:25]
A
Yeah. I hope people are not waiting for it to all sort out, because you are. You're going to be waiting. I think that it's vital at an organization and a leadership level that we begin finding the places we can adopt the tech and doing it to the level and in the places that we're ready for. If you're waiting, you will always be waiting. It's not going to get any clearer. So find the place where you can start now. Adopt some policies. Most organizations don't have a policy on the use of AI in their organization. Start there. Have a look at the FAI framework. Think about where is the place that your organization can start. And again, I will say, I think it's been really helpful for us having this learning. This internal learning group has been a great way for it to be kind of fun and lowered a lot of barriers to entry into the use of the tech.
- [31:23]
C
Okay, I love that. I'll drop in the chat in a moment. The different topics we have coming up at this summit around this. Okay. I want to end with, like, a. A really kind of positive and hopeful full framing.
- [31:36]
A
You have someone else coming on for that.
- [31:38]
C
So, Woodrow, I'll see you later. No, because, look, we started all of this talking about, like, what does it look like to think bigger, right. To think beyond just this helps me do this one thing faster. Right. And I think one of the things that both you and I care a lot about is that piece, like, how do we inspire imagination around this technology? And with this technology that really could transform the sector in the ways that it needs to be transformed. So I'm curious from your perspective, like, and maybe we should define agentic AI first. But I'm just curious, like, as we've started to see AI AI doing more, I'm not going to actually be more leading than that. What do you think could be possible for nonprofits in the next five years? Like, how should. Should they be thinking about this agentic AI or any form of AI, like, give us some ideas to help break people out of maybe the narrow ways they've seen it presented so far.
- [32:43]
A
So, yeah, I like that question. Because when we talk about agentic AI, so much of the conversation is about, oh, my God, imagine how bad this could get. There are real risks, and giving the technology kind of more agency and autonomy has those risks. I'm, I'm doing the opposite thing, opposite of what you asked. Let's think about what do I imagine? And we're, and I'm thinking not so much about missions, because this is fundraising. AI and there, there's probably a different answer when we talk about mission outcomes in the U.S. in particular, more and more people are being left out of the nonprofit experience. They're not being invited and given an opportunity to leverage their generosity. If I think about what I would like to see in that, in this realm as a result of this technology, and I think I'd like to see that all people are afforded the opportunity to make positive change for themselves, their communities, and the world. And yeah, part of that is going to mean because they're supporting nonprofits and those nonprofits are resilient. But the outcome I'm looking for is for those communities of givers and the people around the world who want to make that change, who are being left out right now by our current practices of fundraising in this industry.
- [34:03]
C
So how do you see? I'm going to build on this a little bit because we have a few more minutes and I intend to take all of yours. So do you see? Because we hear a lot about AI and concerns, obviously valid concerns around bias and equity and things like that, but can I help close equity gaps in giving and nonprofits? That's what I think I'm hearing you say. And, and what does that look like?
- [34:31]
A
So, yes, I think it can also. Let's understand, it's ironic when we talk about the bias and the inequity that we are concerned about being amplified by these tools. Where is that bias coming from? That bias is coming from the fact that it's trained on us. We're being crappy at that. And yes, there is the potential to accelerate that, to amplify it, to mask it with this technology, that's a problem. But that, that inequity, the fact that more and more people are being left out of the nonprofit experience, that are more and more people are not being engaged and invited to be part of solving these problems and being, and addressing the, these causes, that's us. We did that without any technological help. So this is what I'm talking about when I say, like I'm concerned that we are going to use this technology in this environment to just improve efficiency. Well, right now we're fewer people being asked, fewer people giving. Every year more and More concentration of the fundraising dollars into fewer and fewer hands. So if we're more efficient at doing that, we don't like that out. Why would we want to increase our efficiency there? So what's the flip side of that? The flip side of that is it is hard to engage in a. In a really personal way with many, many different people at scale. That's the kind of thing that this technology has. At least there's the promise that this technology can help us overcome that. And part of what. But. But at the end of the day, it's not going to do that unless we value that. And right now, we're not valuing the contributions of all people. And that's not a technological problem. That's a problem of culture.
- [36:26]
C
Do you think that this tool has the ability for us to deflect responsibility on some of these core problems? Like how do we help people ensure that we're looking in the right place to solve that problem?
- [36:44]
A
I think partly it's about. I mean, the discourse is critical because what we're talking about here is changing perspectives, practice and cultural outlook. And we needed that before anybody had ever heard of a large language model. So this is good that it is kind of motivating, catalyzing this conversation. And I think that being in discourse as an industry is, is part of the way that we'll do that. There's plenty of people who are presenting on these topics, and thousands of people will come together at the summit to engage with these con in these conversations. And then, fine, you're going to go back to your organization and you're going to be like, oh, I'm going to manage my calendar better and I'm going to practice this, learning about creating better images. And that's a practical next step to getting you into using the technology need is a perspective change on what we hope this will deliver. And I would implore fundraisers to think about, what do we not like about our current situation.
- [37:45]
C
Yeah, I love leaving on that note, because I also think that behind my creation of practivated was just so much frustration with a problem, was like me trying to solve a problem honestly for the last, like five years and continually trying different ways. And then finally getting to this moment where I was like, maybe this technology could help me solve this, because I haven't been able to in all these other ways. And I just hit my year anniversary of when I went on upwork and asked like a what if question, like, would it be possible to create something like this? Like, I had no idea. And I really do want to encourage nonprofit leaders to like and this goes back to everything we've talked about in this conversation. Like that moment of, you know, those moments of reflection around, like what's really causing you the biggest challenges? Like what are your biggest pain points and what are your like, big what if questions? Like what are the problems that you want to solve in your day to day experience in your organization's way of building community? Like, what are the real problems to solve? Not just that your calendar is unmanageable. I still have not solved that and I use AI all the time. Okay. So like I think that curiosity piece and I know Nathan talks about this a lot. You talk about, I talk about it a lot. Like that I hope people come to the summit with particular questions that they have that they want to dive into with particular things that are already top of mind that they want to learn. But more than anything, I hope they come with a tremendous amount of curiosity and a lot of like, what ifs? What do you hope most for folks who are coming? Like, what do you want them to bring with them to those two days and to get the most out of their experience there?
- [39:31]
A
And it's going to be there. I mean the challenge with this summit is going to be choosing amongst the many, many things that and the streams are make it really helpful and I think for people to think about where they fit into that, that puzzle. But there is just so much good content from so many people who are really thinking about this in advance and imaginative ways. It's going to be great.
- [39:53]
C
Yeah. And just so everybody knows you'll get everything on recording and so you don't have to worry if you pick something and or feel like you're missing something else. Everything will be recorded. You'll have access to it. After I just dropped link again inside the live. Woodrow, thank you so much for joining me today and talking through all these very timely topics. I can't wait to see you soon and to learn alongside you September 15th and 16th. And same to everybody else tuning in here. We're going to see you very soon.
- [40:25]
A
Thanks, Mallory. It's always great to chat with you.