Nonprofits are faced with more challenges to accomplish their missions and the growing pressure to do more, raise more and be more for the causes that improve our world.
We're here to learn with you from some of the best in the industry, bringing the most innovative ideas, inspirational stories, all to create an Impact Uprising.
So welcome to the good community, where Nonprofit Professionals, philanthropist world changers and rabid fans who are striving to bring a little more goodness into the world.
So let's get started. Howdy Becky, what's happening?
You just thought you knew about AI? I mean, we just came off the most incredible week AI week and fundraising here on the podcast. And then who walks into our house? Could it be possibly the two most aforementioned experts on AI y'all buckle up because we got Erik and Justin in the house today. It is our complete and total delight to introduce Erik Arnold and Justin spill hug. They are the force over at Microsoft and the tech for social good. And today we're going to be talking about AI for good and Microsoft is really building just an incredible movement. And this technology for social impact. They've committed more than $5 billion to helping roughly 325,000 nonprofit and humanitarian orgs. They're delivering relevant, affordable and innovative cloud solutions. They're helping us y'all tackle the world's biggest challenges. And we don't want you to be scared in this moment, because Erik and Justin are going to take your hand and they're going to tell you how AI can be a force for good. So I'm gonna back it up and I'm going to introduce Justin first. He is the Vice President and global head at Tech for social impact. And he's bringing 25 years of experience spanning commercial social businesses. And prior to this current role, Justin served as the chief marketing and operations officer for Microsoft Asia Pacific, Jon, like what is our life right now that we're so cool, nice to him. But he was spending over seven years of his career working across developed in emerging Asian markets and just incredible human, we're so excited to hear his story. And Erik Arnold is the Chief Technology Officer for tech for social impact. He joined Microsoft in 2017 as the Chief Technology Officer, and he's leading Microsoft engineering product strategy for nonprofits and the United Nations casual. Prior to Microsoft, Erik served nine years as the CIO over at path we love path path International to nonprofits focused on global health and 15 years over at a privately held Bill Gates startup, which is probably a story in of itself. Y'all AI is here, we are ready to embrace it. We know that it is not only going to help us connect, and work smarter, not harder. And we don't want you to fear it. And we have these two incredible gentlemen who are going to take your hands lead you through it. Erik, Justin, so excited that you're here. Thanks for coming to the We Are For Good podcast. Welcome.
Thank you, Becky. And Jon, it's great to be here. Look forward to this discussion. Oh, we're
even repping like every part of of his clothing is tech for social impact. So get on YouTube and go check it out. And you don't start any of our conversations here without actually getting to know the human. And so we're going to take make you take us back a little bit. And Erik, I'm gonna start with you. We want to know about like, where you grew up? And what who was little Erik and how did he find his way into this Tech for Good sort of movement? Yeah, well,
my most I grew up at a small town in Washington State and how I got engaged in the social impact sectors because I was a beneficiary. What my parents are, my mom was relatively poor. We were on food stamps. And so you know, I was in food bags, I was in kitchens, and pretty early on learned how to give back and what it meant to have local organizations, small organizations in small communities that are providing services for people that need
that was the most succinct, powerful elevator speech about somebody's upbringing. career that is to shaysing you're honoring your mom with this work. Thank you so much. What about you, Justin,
what all comes back to mom's doesn't it? Right? Oh, no, I have a similar story. My mother is a Child Protective Services investigator in Seattle, Washington. My father built a small nonprofit, which is now turned into a not larger nonprofit, which is senior services for Snohomish County. And, you know, as to social workers, they didn't have a ton of money. And so they threw me in the back of the car when they got the page or they threw me in the back of the bus when they needed to do the Meals on Wheels work. And so through sort of osmosis, I learned the value of service. My mom had an incredible run an incredible career. Unfortunately, my father's was cut short by mental illness. And it kind of compelled me to focus on finishing maybe part of part of my family's work that needed to be done and also to express service in in and through my work.
That's incredible legacy building. Jon, before you jump in on the first question, we got to name the moms here, let's give them give us their names guys, Barbara, Barbara, Barbara, and
good women raising my iced coffee to them, right. I mean, thank you both for your vulnerability. I think it's easy to hear Microsoft Tech for Good these billion huge numbers and forget that it's like powered by humans with stories that are so connected into that. So thank you for being vulnerable enough to take us into those places today. So I want to hear about let's set some tone and in tell us about Microsoft tech for social impact. Like what's the scope of your work in Mission?
Yeah, you know, and I'll just say one note, Jon, everybody in tech for social impact has their own story. And that's what makes the team so special. They're all a great group of people with with very mission driven attitude. But when we work at the Tech for social impact business, we really look at the nonprofit and iagto industry. So the UN entities, the development bank's, there's 10 to 12 million of these organizations worldwide. And they, in the United States, as an example, command over $2 trillion and total revenues. It's a big, big sector doing incredibly important work in every one of our communities, from delivering health services to global aid to working on conservation. And they, like every other industry need technology, to accelerate their missions and to have a greater impact and to operate efficiently and effectively. So that's why we created the tech for social impacting was to really treat that industry as a first class industry that needs the same cutting edge technology that every other industry does. And we did that in a unique way, though, we brought together both affordable offers. You mentioned, I think you mentioned $5 billion, will do $3.9 billion of discounts in donations per year. So supporting 325,000 organizations. So affordability is a big part of our strategy. So that the that nonprofits have access, Erik leads technology. So we build specific patterns and solutions for critical processes like fundraising and program delivery, we brought together a capacity building team that would focus on raising and elevating the skills of nonprofits so they could use and apply this technology to mission and we work with partners like Tech Soup. To do that we brought together commercial resources, account management partner resources into one integrated team that is based on a social business construct. And so ultimately, the way we run this business is as a social business where we reinvest a portion of our incremental proceeds back into public goods, initiatives, like digital skilling for excluded communities, like AI for good and many other topics. And that's unique and keeps us oriented, I think, in the same way that nonprofits are and the way that we serve the sector.
Wow. I mean, just some casual numbers there. And I really think you're right, Jon, it's easy to gloss over the numbers. But when you think about 3.9 million billion dollars being invested in a nonprofit, and I think about the systemic issues that that would, that would hit and without the tech, and let me tell you, we've seen some scary tech in our world. And there are still nonprofits out there who are on shoestring budgets, working off a database of Excel. And it's just so gracious. And we really appreciate that all that you're doing. And I just think the AI conversation is just booming. And if you're tired of hearing these conversations on the podcast, well, sorry, not sorry, because this wave is upon us. And it's something that we feel very passionately about embracing, because we don't want to be left behind. And we want to be completely in tune to where's the world going? How do we connect with people who are who are really passionate about our mission? So I want you to talk just a little bit about some tone setting around this topic, because AI is one of the most widely discussed topics in technology today. It's embedded in almost everything we do. It's in our workflows. It's embedded in data, whether you like it or not, it is here. So if you can just talk to us about where are you at right now. Give us some stats and what opportunity exists in particular for nonprofits today. And if you're feeling generous, like throwing some stuff that we're not doing that we should be doing.
Yeah, I think we're gonna get through that in the discussion. Now. What's funny is 25 years ago, when I started my career at Microsoft, it was on an AI project. It was on machine learning to optimize certain things we were doing in our supply chain. So AI has been around for a long, long time. And we've been using it and it's been incrementally improving. But what's been breathtaking and surprising, I think for for many of us has been the speed at which foundational models or language models or what is known as GPT has really come to the fore and, and the very unique problems that it's able to solve. You know, just in in a matter of days, when we launched Bing chat, we saw over 400,000 Nonprofit Users working with Bing chat to do everything from, you know, drafting initial donor proposals to analyzing grants. And so it is actually getting a lot of adoption and there is a lot of speed, but we've got to kind of gone through his hype cycle, right, where where AI was first going to save the world. And then it was gonna destroy the world.
We all have whiplash, yes.
I think people are now kind of in the in the stage of like, well, how do we use it usefully? And so as we go through this conversation, I think we're gonna highlight some of the ways that we think AI can really make an impact in fundraising and donor engagement in delivering missions. But it's here, right? And it's powerful. There's a lot of capability.
Yeah, but Becky, you're exactly right. Like, you can't stop the tide. Right? You're all not just Microsoft. But many technology companies are really taking advantage of these large language models in this moment that we have. And we talk about, you know, that I think it's the sun also rising, the Hemingway quote around, you know, how did you go bankrupt gradually, then suddenly, that's how we're experiencing AI. Right, we spent years where, where AI was really the purview of, you know, really well funded projects with data scientists and big data, solving big problems. You saw these Lighthouse projects, you know, here and there. And then GPT came along last November, and it's everywhere. You know, it's really democratized the access to AI in productivity tools we use every day, you know, guarantee you, if you're a nonprofit thinking about using AI, you're already using an AI, you're you're smart, we're using big chat enterprise are experimenting with it in other places.
I mean, let's double click, I love all this tone setting that we're doing. Let's double click into like, what is the impact specifically on fundraising and donor engagement? And then program effectiveness that y'all are seeing? Yeah,
I mean, I think first of all, just with fundraising over the last five to 10 years, we've seen some real shifts in our fundraising is happening like, like, we've all kind of know, the some of the generational shifts that are happening. And then with COVID, lockdown that really forced, you know, different ways of giving. And it's challenging for nonprofit organizations for fundraisers to adjust rapidly to some of these. And so I think, you know, it's opened up opportunities to create new data partnerships, it's opened up opportunities to use AI with existing fundraising data to do things like thinking about more personalized engagement, thinking about better campaign management, thinking about how to apply getting trend data together with the data that you have in your own systems, whether that's in an Excel database, or whether it's in a CRM system. And so I think the the practical application of AI that we're seeing right now, I'm actually seeing more activity in the fundraising space more rapidly than I'm seeing in the program delivery space. It's happening in both areas. But I think everyone is recognizing, first of all, every nonprofit fundraisers and so it's kind of a natural place for all of us to go. But it's been really interesting to see some of the partnership conversations that have come up where, as Microsoft, a huge believer in having open standards, interoperability and making sure that we're playing our role as a platform technology company that can help lineups innovation, in many, many different ways. And so what I think a lot about is how we're taking some of these patterns that we're seeing some of those opportunities for data partnerships and translating that that into technology and solutions that we and our partners can take forward. And in very specific fundraising scenarios. When I
maybe I just add one additional on the program side, Jon, given that you asked that question, you know, there we're seeing kind of 1000 flowers bloom and I'll give you one example of a pretty compelling use case. So we're working with the International Criminal Court, not necessarily a small amount of profit, they are the largest court in the land that prosecutes war crimes, right humanitarian war crimes when a when a state can't or won't do it. And so they're they're operating in Ukraine, they're operating in many, many different places. And it turns out, war crimes are documented. There's a lot of documents, photos, social feeds, videos, that need to be analyzed, they need to be associated to create a chain of evidence and match a person to a place to a thing to help build up cases. And we're deploying Azure Cognitive Services in partnership with the International Criminal Court to do just that. And it's shrinking the time for investigations dramatically what that result that sin is prosecution. Right. And what that results in is justice faster. For those that have been, you know, been victims of war crimes.
I mean, that was probably the most perfect example. And I mean, war is very heavy on all of our hearts right now. We're all thinking about it. And I, I do you think that what an incredible use case and I'm also sitting in a space of gratitude that you that Microsoft, that individuals like yourselves, are doing this work and making those connections, because Erik you said, the phrase that scares all of us, and nonprofit, which is adjust rapidly. And that is not our skill set, you know, trying to move quickly. And yet we find ourselves standing in this world right now. That is largely new for so many that were either maybe tech averse, or were didn't have time or resources for it. So I thank you for really trying to help accelerate us forward. And I want you to kind of talk about, like, the key challenges that you all are seeing nonprofits are facing, like with their fundraising today? And how how are you seeing AI, you know, uniquely positioned to address those challenges. Love your example, Justin. But any other examples that you think can kind of take on how we can overcome any of these challenges would be so helpful?
Yeah. So really, really specifically, a couple pieces of technology that we're working on one is a likelihood to donate model. And so working with nonprofit organizations, the fundraising data that they have today, what are some of the giving patterns that individual donors have? Is there seasonality there? Is there causal alignment for for certain individuals is or do they have networks? So they, you know, how do they give? And then scoring that? And what is the you know, the next best ask, what's the likelihood to donate for certain individuals? How do you allied that your campaigns to those individuals to get more personalized communications to them for appeals, and get more personalized communication back to them that talk about the impact of that donation, aligned to what they're telling you and their engagement with your organization? So that's one piece. Back to the the interoperability piece. We're also very proud to be a member of the getting Tuesday Data Commons and working with Giving Tuesday on how do we help platform that data and make that data available in fundraising solutions, so you can see kind of trends in fundraising, and use that as you're developing your campaigns and your approaches.
And I just have one additional thing I think, you know, in the nonprofit industry, I think we as a technology community haven't invested enough in kind of the fundamental skills required to, you know, what's this thing called prompt engineering right away right prompts to get these outputs that I want? And how do I just fundamentally get started using some of this technology in a way that's gonna be really effective, whether my job is a fundraiser or a program delivery person, or whatever the function may be, COO, CFO in there, you know, I think we're focused on fundamental skilling. And, and we have a great, it's actually a really great AI learning pathway in LinkedIn that we have 1.4 million people already engaged in right now it's free of charge, go, you could go to LinkedIn, look at the Microsoft AI career pathway. And it will teach you about how to think about prompts, how to think about using tools like Bing chat enterprise, using these open AI tools in a way that's most appropriate for your job. So sometimes, it's just starting with getting scaled up
It's one of the most important things that that I think about why am at Microsoft, why did I leave the nonprofit sector cup here, it's because we think holistically, not just about the technology, but also about the capacity building, I, when I was at Padley, used to talk about you know, this, the way technology evolves is a river like it is not going to stop, you know, the the innovation, the pace of that change likely is only going to increase. At some point you have to jump in if you're waiting for things to slow down so that you can align yourself with technology that you have more confidence in. That's not the world we're in today. Like you really need to think about how you're engaging in this. And one of the ways that we think about it is we provide a lot of skill of content, and a lot of engagement with nonprofit communities and communities in general about how to build that digital literacy.
I mean, y'all are kindred spirits. You're putting the pieces out there for us to pour into. We're a growth mindset oriented community, we talk about the power of just learning the things we don't know, like everything is figure-out-able especially coming out with this open hand to what we can figure out.
I love figure-out-able.
Amazing.
Love it so much. Well, I mean, we've talked about the power of this. There's so much still coming at us. But you'll also lean into just responsible use. It's on the forefront of all of our minds in the nonprofit space. You all put together some core principles that guide fairness, accountability, transparency, etc. I'd love for you to walk us through some of those. Can you list some of the most important aspects of this conversation because I know So it's in there, it's in our minds as we kind of approach this from the nonprofit that are seeking justice and trying to not create more harm in the work that we do.
It's critical and I'm glad you brought it up, Jon, and and, you know, Microsoft, in fact, years ago, as we were doing our work on AI, we built responsible AI framework that has six core principles as you started to it to enumerate their fairness, accountability, transparency, and it was important is how they're used in in the way that we engineer our product. Not only are they a guide for our engineering work, and how we implement AI within customers, but they form the basis of our engineering policies, our standards, and ultimately, they flow into the way that we've set up our training, our tools, our testing, procedures, and, you know, they're auditable, and and verifiable. So that these are critical principles. Now, if I if I took a step back and said, what principle am I most concerned about at the moment? Where do I see the biggest challenge, right? When having spent a lot of time in the last, I'll just say, six months in in Africa and India and other parts of the Global South, I do think the principle of inclusivity and ensuring that we're not widening the digital divide, but we're narrowing the digital divide is is a tough problem. Right? It's a tough problem. And what's really interesting is some of the work that our Microsoft research team is doing on how do we engineer this technology, so that it can work effectively in lower resource markets with lower bandwidth, perhaps with more limited budgets so that the AI needs to be more affordable in the way that we roll it out. And how do we use AI, as really a superpower to unlock digital capabilities for those that may not be very digital fluent, and, and one of those superpowers is language, right? Being able to interact through local language with a computing system and get what you need, whether that whether you're making a payment, whether you're filing for a property permit, whether you're getting information on your on your farm, right, and the soil conditions, and what you need to plant, and being able to do that in what we will call lower resource languages. So things like Swahili, or other languages around the world, I think, could be a real game changer. And our MSR Microsoft research team is working hard on these problems to ensure that not only does AI, you know, support us here in Redmond and Seattle, but it's actually helping narrow that digital divide in in the Global South. And we have a lot of work to do, I'll be honest with you, we have a lot of work to do. But it's something that we're very focused on.
I would maybe add a couple things to that what is your principles are, are great, but they're, they're not really effective as if it's just a poster on the wall. And so we first of all, all of the principles that we have are embedded into how any engineering team at Microsoft does its work. And we all have to go through audit and compliance to ensure that any solution that is using any of our copilot resources or any open AI components are adhering to that policy. But it's not just us. You know, we provide the guidance of the toolkits for any technology partner at any organization, the nonprofit organization or for profit organization to adopt those same principles and have guidance for how you incorporate it into your own organization. We think about it, especially in how we think about the effect of how we train these models for vulnerable populations, for example. And so it's not just a language component, but also from a privacy and security layer, like how, as an organization working with vulnerable populations, can you trust that LLM how can you trust your GPT is using your data and make sure that we have the transparency and and control that organizations want to be able to combine their their own organizational private data together with well trained large language model. And you'll really get the best results as you combine those two things without exposing the data for the populations that you serve.
Justin, Erik, I like you so much. You guys get it? I mean, it is true when you when you talk about we could have these ethical principles. We could put them on a poster or we could you know, rah, rah at your team meeting. But when you bring it back to the human who's actually trying to connect, I get it. I'm going to share a story from somebody within our community. We have an incredible community member. He is in rural Uganda. Hi, Simon. And he has this incredible organization that provides microfinance loans to women in rural Uganda. And you can imagine how far $100 could go for a woman in one of those communities. We have been working like mad to try to get a giving platform up so he could accept credit cards, we have worked to get him a new laptop, because he hasn't had one in 15 years, you know, small changes like this, not only do they transform his nonprofit, it transforms the community, it can transforms connectivity, it brings not just resources in but it opens the world. And I just, I mean, we have such a heart for Haiti, and you think about the infrastructure in a marginalized population by that, but even in the United States, I mean, we have trafficking organizations and hunger organizations, and you get so mired in feed, helping the beneficiary on the front line that you, you kind of forget to prioritize these things without thinking this is the long game, this is going to help you play the long game in every possible way. So thank you for living, and seeing humans, you know, in this work, we think ethical storytelling and ethical, just really walking with intentionality through what we do giving dignity. And all we do is the best way that we can show up and serve. So I want to talk a little bit about you mentioned vulnerable populations and how data can be trained, because we know that there's going to be biases, you know, they're going to be that are going to be surfacing. And how do we address that? How do we use data to address something that we still want to be so ethically sound? And so we're really centering that dignity for all human people with either one of you to take that?
Yeah. So from a, from a training perspective, it it starts with understanding what some of the concerns are making sure that we're entering the conversation, recognizing that we're not a the only player and B, we have a lot to learn from the organizations that are on the ground delivering these services. So how do we effectively work with United Nations missions? How do we work with humanitarian, global humanitarian organizations? How do we work with the small health and human services organizations and in urban environments? Part of this is, you know, large language models are trained on data that's publicly accessible on the internet, how are you managing your data and ensure that you've got the right practices inside your organization. So first and foremost, you're not exposing the data for for potential consumption by any LLM. But understand that, you know, the engagement between how an LLM is trained, large language model is trained like GPT, and how you use your own organizational data. And so what we're working on are ways that you know, where these generic models are trained, and how they're applicable in specific scenarios, be they nonprofit scenarios or other industry scenarios, and how you combine your own organizational data with the you know, the the trade model in ways that give you the richness that allow you to, to then either drive more more directed program impact or whatever it is, right. And so, you know, we're in the midst, Justin was saying, we're in this hype cycle where we have a lot of fear on one side, and a lot of hope on the other side, and we're, you know, let's worry wisely about the fear. And let's appropriately on what some of the promises are. And let's really focus on what are some of the practical solutions that help how organizations are thinking about how they adopt the technology and help us as a major technology player, learn what we need to learn to ensure that you know, where we are seeing biases, we can help you tune and adjust, where we see the opportunity for creating maybe different approaches for large language models, as Justin was talking about for lower resource settings that, you know, we can we can make our investments wisely.
Yeah, the only thing I just add to that is we often say Microsoft, you'll hear us around the halls, talking about how Microsoft is built on on trust in, you know, honestly, when I look at all of the other partners out there technology providers, I do think one of the ways that we differentiate ourselves is is our is the business model that we have and and we hope that that business model engenders trust both in the way that we we talked about the principles we use in building AI, the way I was just articulating the way we're trying to tackle problems of inclusion for languages in the Global South, but also the way we give organizations control over how their data is used by these models, right? Full control,
Thank you.
like full control. And that that is just I think critical so that organizations have choices that they can make, to use these models in the most appropriate ways.
Love that. Well, I mean, I'm feeling the need to transition to activation. I mean, we've heard a lot of really great talk about how this translates but I want to get active and put this into practice. A lot of people listening are wanting to implement new technologies, but we know it's gonna come with challenges we've we've addressed the big elephant in the room, we have to have a growth mindset. So that's table stakes here. But what are some other challenges that nonprofits could face? When adopting AI? What have y'all seen, specifically for maybe fundraising? And how can they overcome these hurdles?
Why I think and then Erik, just we'll just riff on this one together. I think one of the questions is like, how do I even get started? Like, how do I get into gear like on anything? And let's start simply, right, let's start simply, which is number one, what let's figure out what are the resources that we can deploy to help build that knowledge that career essentials on generative AI is a four hour course you can take it, it's a great course as an example. And that will equip you with a fundamental kind of language and knowledge and, and it's helped me actually figure out how to write prompts that were that were getting better, better outputs. And for the work I was doing, whether you're trying to write a fundraising proposal or analyzing a grant, it will be helpful. The second thing is just get started, just start using it, right. And when we think about the easiest way to start getting power out of these tools, you know, any organization that's that's running, Microsoft 365, has access to Bing Chat Enterprise now what is being chat enterprise, it's big chat with all of the enterprise security and controls that you would want to use inside of inside of an organization. And it's it's freely available. And so getting people to starting to use big chat enterprise for writing a grant proposal for analyzing a fundraising plan is just a great starting point. It's low friction, you don't need it to implement anything you just get started.
Holler!
Yeah, that's important, right?
No offense, guys.
Well, no. One important point is of other 325,000 organizations that we serve, like 320,000 of them are about seven people or less, I mean, a lot of community based organizations with small teams where the the IT person is also the fundraising person as well as the as the Managing Director, right? So we got to be we got to be really honest about making it easy to use this technology not and and that that is the next easiest step. The third step, right, if we were been trying to get to more advanced levels, right, is all right, how do we start using some of these low code, no code platforms like Power Platform, which, again, don't require coding experience, don't require deep technology skills, they do require skills and some knowledge, and we've got good training on that. But you can set up things like power virtual agents, to help beneficiaries as they engage your organization get routed, in a much more effective way to the services that they may need in your organization or get information in a self service way that doesn't feel like one of those old, you know, phone trees that you dial into with a bank that drives you crazy, right? It's much more intelligent than that. I think one of the most powerful tools for small organizations, small nonprofits is going to be the Microsoft Office co-pilot. Now today, there's a 300 seat limitation, we're working on bringing that down, right? We got it we're I'm doing we're doing that work. But if you think about what is the number one fundraising system, what's the number one accounting system, what's the number one HR management system in the world, it's probably Excel and bringing intelligence across all of your documents, all of your email, all of your systems that you're running and Excel for your smaller organization, that is going to be a game changer. And so training, get started with Bing Chat Enterprise. And then we can start to step into some of these more advanced tools is a great way for organizations to get to get into gear and start getting value out of this.
I'll give you a good maybe a few really specific examples about like if you're sitting at a computer right now and bring up a browser what you can do. So we, we have a really simple demo, where you can go to big chat enterprise and enter a props like, as an executive director for a food bank, in a community, I need to organize a food drive for Thanksgiving, write me up, you know, write me an appeal letter, and you will get a first draft of an appeal letter. Is it perfect? No, probably not. But it's a great place to start. So you're not sitting there looking at a blank piece of paper. How do I how do I, you know, this, this, this artifact, another example on what Justin was saying around Power Virtual Agent. If you're an organization that has an FAQ, or has an annual report, you can load that FAQ or load that annual report into power virtual agent takes about 10 or 15 minutes to go through the whole process. And now you have a chat bot that can answer questions about your annual report or, you know, you'll have an interactive chatbot for your FAQ. We've tried really hard to make really, really, really easy access for some of the most common challenges that organizations are having and What we're seeing without, you know, having having co pilot, you're really in the market quite yet. I was talking with a family foundation based here in the Northwest, they have an annual proposal drive. They finished their funding cycle four months earlier this year, because the quality of the proposals were and the amount of proposals were coming in so quickly. And it was because organizations were using chat GPT to write the proposal. So pointing Chat GPT at your proposal library, looking at the RFP, writing your proposal based on what we've done before and what's been successful, they will give you a first draft of a proposal response. So we're already seeing kind of some of these really practical use cases where where people are experimenting with the technology. So as Justin said, the capacity building is essential. And you've got access to these tools today.
Now Becky and Jon, I've got a question for you. Are you using nervous? No? Are you using any of these GPT power tools for any of the work that you're doing? And what are you finding?
Heck to the yes.
Heck yes.
We have to. There's just too much going on. And, and I mean, I have I was telling the story the other day, I mean, I even got Chat GPT out for my attorney husband the other day who had never used it, and asked for certain case law with precedent on this certain topic in Oklahoma with but and his mind was completely blown. And I just think that, you know, once you use these tools, the friction, just the more you use them, the friction just kind of I don't want to say it goes away, but it minimizes significantly. And I really appreciate what you've been saying, like Erik, your example, because I can assure you program officers everywhere at foundations are cheering, because it's really taken a lot of what is a manual process out and we're able to streamline this and I want to use streamline as a way to say streamline means efficiency, streamline means that we get to move faster. In our missions, it means that we get to adjust quickly. And so I think that this is only going to help boost us. I'm on the hopeful side of AI, I actually think that it's going to, I hope that it brings more ease, because one of the things that I worry about so much with nonprofit is just the amount of tactics and in work that we have to carry with so little resources, the mental health, you bring up mental health, Justin, I mean, we're a very sick sector right now in compassion, fatigue and burnout. And I think that these tools are an absolute lifeline to us to not only work smarter, but be more efficient, find the right people, we're talking about prompts, like we're geeking out about the prompt thing that is total idiot proof. I want that, you know, and give me what the data is telling me. So I just, I just celebrate what you all have done on the tech for social impact side. And I just want anyone listening to just feel like doing 1% shift. That's what we're saying here. Pick one thing, pick one thing, try it out, you know, do one a week, once that gets comfortable, do one a day start getting in flow of this share what you know, because we think that we're going to fail forward, but we're going to fail faster together. So I really just appreciate Microsoft taking a really big lens on this. And we want to make sure that we're creating space to like say, where can nonprofits get these resources? Where's the best place that we connect? could connect them up?
Yeah, I think a couple of places. One place is for that training. I think LinkedIn is a great location. So if you go to LinkedIn, and you type in the look at the Microsoft LinkedIn AI Career Pathway, it is a great, great, great training resources. Start there. That's the first thing. Second thing is to get access to the technology that we were talking about, go to microsoft.com/nonprofit. And that will bring you to all of the resources that you need to get assets. And then of course, within that is also local partners that you can work with, to enable what you need to enable. You know, one thing you mentioned, though, Becky, I wanted to highlight was, you know, if you if you were to say, Hey, what is the next killer feature? Like? What is the next thing?
I do want to know that
You know what it is? I think it's ubiquity. I think it is the fact that in everything you do, whether it's donor retention campaigns, event design, it's going to be built into the tools kind of by by default. And there's a really important principle that we think about as we do this, and that is that it's about creating a smarter, more efficient, nonprofit leaders. It's not about replacing, right it's about being the copilot, a ubiquitous copilot in every single activity that you do. That helps you just do it faster or more efficiently, more effectively. so that you can unleash your creativity to solve the problems that you're trying to solve in your communities. And that's why we named every one of our technologies co pilot, because we think they're an assistant to human ingenuity not replacing human ingenuity.
The only thing I would I would add to that Justin is how we are increasingly thinking about community and the role that Microsoft can play to help create the opportunity for nonprofits to talk about the application of this technology and what they need to learn and how it's working for them, and how we and the partners that we work with the technology partners that we work with, can engage more effectively. So we're really leaning in to create space for an additional nonprofit community that that is thinking about the application of AI.
And we're launching that community, I'll say we're launching it online,
you heard it here
platform at the at the end of January. So you'll see us roll that out, which will be a virtual space where nonprofits can go and engage in topics, talk about these things, we'll have experts on standby to make sure that we're providing the input to those communities, so that nonprofits can support nonprofits, and we can be part of that process too.
So cool. Community is everything I was gonna say, here. So I mean, you're bringing up the heart of all of this, like the humanity is the piece that's not going to be replicated, we're going to have a lot more ease with AI. But like the core of why we do what we do the human interaction, this transformation that happens with people, that person, I want to give you a space to talk about a moment of philanthropy that's happened to you and your life. We celebrate it on the daily we'd like these are the moments that are sometimes small, but they stick with us our life. I kick it to you, Erik, to take us back to one of those times.
Yeah, absolutely. So I will tell you about the first time I went to Africa when I was a new employee path. Path is a logical health organization. And it works in vaccine development, vaccine delivery, medical device technology, and I was running an HIV AIDS clinic in rural Western Kenya and Kakamega. And so you spent six years flying to Nairobi, and then you fly to Kisumu. And then you get into Jeep and you tried to copy omega and you're really amazing experience. And I was touring the clinic there. And at the end of the tour, the doctor took me aside brought me into his office, where there was an elderly computer. And we had an app that they used to order medications for the clinic from the central store in Nairobi. And there was a new medication he knew was available, but it wasn't available in the application. And simple question was, how do I add? So in this situation for organizations that are grant funded organizations, working in technology, you'll recognize some of this as pilot is right, every grant and every program resulted in a small point of service application that didn't connect to anything else, their work data standards, wasn't everything, our operability what was this application? If you were a doctor or a nurse in this clinic, you had two phones at five apps, and you were working with one individual and doing your survey? Okay, we're asking malaria questions, I go into this survey tool on this phone. And now we're talking about HIV AIDS. And it's the spine of this survey. So I became really passionate about the intersection of digital technology and the nonprofit sector and what role companies like Microsoft and others could play, to contribute to the solution to that problem, really thinking about the beneficiary, the center of the modeling, and how everything in terms of service delivery kind of needs to result from there. How do we build common data model for nonprofits and make that available open source for any technology partner to use and make sure that's informed by nonprofits and philanthropy organizations, make sure that we're building on top of that, make sure that our architecture is open. And we're open to partnering with other kinds of organizations that we focus on data data interoperability, so it really became kind of core to me on on how I engaged when I was in the nonprofit sector and a big reason why I came to join Microsoft.
Good luck topping that Justin.
No I have it's a different story. And and I think, a couple years back, you guys will remember that there was severe flooding in the Midwest and you may know of a nonprofit called Team Rubicon. As you may have seen in my bio, I'm a Marine. And on Team Rubicon, it's a lot of former service members. And what they say is kick butt civilians, too. They go, they go out again, we're, you know, in areas that need support, and we were we deployed out with the Team Rubicon team, to the Midwest that was absolutely devastated by these floods. He's houses were overcome with mud and water and dry and mildew and where they were uninhabitable. And so I spent the day on the ground with the Team Rubicon team, you know just what they call mucking out a house. And so that's what the shovel and just clearing debris and mud all day long, relatively simple, relatively straightforward. And by the end of the day, we had one of the houses in much better shape, but nobody was in it. And as we were cleaning up and wrapping up for the day, the family had made it through kind of the, the barriers that the law enforcement have put up and got back to their home. And they just broke down, you know, when they saw the, our work and kind of the state of their house. And the fact that they were going to be able to move back into it. And it just reinforced to me the what was a relatively small act of service can make such a huge difference in somebody's life. And to see that to feel that, to see the gratitude of that family and their emotion as as they were coming back into their home was just a reminder to me of why we do what we do. You know, there are one over a million organizations in the United States, doing small and large acts of service every single day just like that. So it's multiplied by a million or more. And if we in our work can make those organizations just 1% more efficient. To your point, Jon, I'd like to make them a lot more than 1% more efficient, but just 1% more efficient, more have helped a lot of people will have been a part of helping a lot of people and enabling this this great industry, here and around the world.
You guys are such good dudes. I'm not kidding, I just, I just think sometimes we can gloss over the veneer of things just because you know, you have these big titles, you know, you work at this massive company that is one of the most, you know, well known brands in the world. But at the end of the day, it's about humanity, it's about looking that person in the eye, and in saying, you know, it was my pleasure to be here to muck out and give you space to come back. And it was my pleasure to be able to put that, you know, prescription in so that you don't have to suffer from whatever it is that you're suffering. And I just think if we can all embrace this, we all can do something sort of mentality, then that you use the word generative before that's generative to the world. And so I just am sitting here with a heart full of gratitude, feeling like Justin and Erik have got tech for social impact in such good hands. And we kind of wind down all of our conversations with a one good thing and it could be a piece of advice, maybe a life hack. What would be your one good thing?
Okay. Well, Jon already said it. In fact, my thing would be would be growth mindset. You know, when all of the nonprofits listening to this, when they look at the challenges they're trying to solve in their community, they are hard and doing anything hard or big. The default setting is challenging setback. That's the default setting, right. And so kind of the ability to keep the energy to keep learning to keep the faith to take one step forward. Even if you have to take one step back and take another step forward, that resilience is all captured, encapsulated in this idea of growth mindset. And I think it's just such such a critical attribute for us in this ever changing and what feels like a much more volatile world to keep front and center and the way that we work.
So I'm a I'm a Systems guy. So I like catching that growth, mindset change. That's how you're so good together. This kind of change that this effort. Think about it, think about how do you need to train your staff? How do you need to train yourself? How do you introduce these concepts in your organization? How is it going to impact your donors and, you know, quick example there yet again, back to how an organization was quickly using chat GPT where a fundraising officer her native language wasn't English. And she was started using Chat GPT in the donor communications and the donors were coming back and saying Did you hire someone new? And no, it was that it gave this fundraising officer so much more confidence to be able to engage with the donors but you have that kind of change and how you think about introducing these concepts does take some some conscious effort and change management with the organization.
Incredible.
I mean, wait around this out fellas, this has been such a delight of a conversation I want to give y'all a chance to say how can people best connect with you follow your work and then connect us up against the this free resources and the all the good that Microsoft is putting out there?
Yeah, no, I think the best way is probably LinkedIn. So you can find me Justin spa. org and you can find Erik Arnold whose prolific on LinkedIn and connect with us, we'd love to do that. And then again, on LinkedIn, we again have that that generative AI learning pathway, look that up. It's a four hour course you can take the first four minutes or all of it. And then again at microsoft.com/nonprofits is where you'll find all of the resources available to you. So those would be the the main areas.
Erik, Justin, you have done Barbara and Terry, so proud today. And every day as you work and walk through this life in the way that you do, thank you for coming in. Thank you for just the way you have poured into this community. We will see you over in your community and your platform at the end of January. It will be exciting. Thank you for your input.
Thank you, friends.
Awesome. Thank you.
Thank you.
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