Latest / We Are For Good Podcast - The Podcast for Nonprofits / 488. Harnessing AI for Good: AI in the Nonprofit Sector - Justin Spelhaug and Erik Arnold, Microsoft

Transcript

488. Harnessing AI for Good: AI in the Nonprofit Sector - Justin Spelhaug and Erik Arnold, Microsoft · We Are For Good Podcast - The Podcast for Nonprofits

• 0:01
  Speaker 1: Hey, I'm John.
• 0:02
  Speaker 2: And I'm Becky.
• 0:03
  Speaker 1: And this is the we Are For Good podcast.
• 0:06
  Speaker 2: 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.
• 0:15
  Speaker 1: 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.
• 0:23
  Speaker 2: So welcome to the Good Community.
• 0:25
  Speaker 2: We're nonprofit professionals, philanthropists, world changers and rabid fans who are striving to bring a little more goodness into the world.
• 0:34
  Speaker 1: So let's get started.
• 0:35
  Speaker 1: Howdy Becky, what's happening?
• 0:38
  Speaker 2: You just thought you knew about AI.
• 0:40
  Speaker 2: 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?
• 0:48
  Speaker 2: Could it be possibly the two most aforementioned experts on AI?
• 0:55
  Speaker 2: Y'all buckle up, because we got Eric and Justin in the house today.
• 0:58
  Speaker 2: It is our complete and total delight to introduce Eric Arnold and Justin Spielhog.
• 1:03
  Speaker 2: 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.
• 1:18
  Speaker 2: They've committed more than $5 billion to helping roughly 325,000 nonprofit and humanitarian orgs.
• 1:26
  Speaker 2: They're delivering relevant, affordable and innovative cloud solutions.
• 1:31
  Speaker 2: They're helping us y'all tackle the world's biggest challenges.
• 1:34
  Speaker 2: And we don't want you to be scared in this moment, because Eric and Justin are going to take your hand and they're going to tell you how AI can be a force for good.
• 1:42
  Speaker 2: So I'm going to back it up and I'm going to introduce Justin first.
• 1:44
  Speaker 2: He is the vice president and global head at tech for social impact and he's bringing 25 years of experience banning commercial social businesses and, prior to this current role, justin served as the chief marketing and operations officer for Microsoft Asia Pacific.
• 2:00
  Speaker 2: John, like what is our life right now that we are interviewing these two humans, but he was spending over seven years of his career working across developed and emerging agent markets and just incredible human.
• 2:12
  Speaker 2: We're so excited to hear his story and Eric Arnold is the chief technology officer for tech for social impact.
• 2:18
  Speaker 2: He joined Microsoft in 2017 as the chief technology officer and he's leading Microsoft engineering product strategy for nonprofits and the United Nations.
• 2:28
  Speaker 2: Casual Prior to Microsoft, eric served nine years as the CIO over at Path.
• 2:34
  Speaker 2: We love Path Path International.
• 2:36
  Speaker 2: It's a nonprofit focused on global health and 15 years over at a privately held Bill Gates startup which is probably a story in of itself.
• 2:44
  Speaker 2: Y'all, ai is here.
• 2:46
  Speaker 2: We are ready to embrace it.
• 2:48
  Speaker 2: 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.
• 2:55
  Speaker 2: And we have these two incredible gentlemen who are going to take your hands, lead you through it.
• 2:59
  Speaker 2: Eric Justin, so excited that you're here.
• 3:02
  Speaker 2: Thanks for coming to the we Are For Good podcast.
• 3:03
  Speaker 2: Welcome.
• 3:05
  Speaker 3: Thank you, John.
• 3:05
  Speaker 3: It's great to be here and look forward to this discussion.
• 3:09
  Speaker 2: Oh and see Eric's even repping, like every part of his clothing is tech for social impact.
• 3:16
  Speaker 2: So get on YouTube and go check it out, and we don't start any of our conversations here without actually getting to know the human, and so we're going to make you take us back a little bit.
• 3:25
  Speaker 2: And, eric, I'm going to start with you.
• 3:27
  Speaker 2: We want to know about, like, where you grew up and who was little Eric, and how did he find his way into this tech for good sort of movement.
• 3:36
  Speaker 4: Yeah, well, my, I grew up in a small town in Washington state and how I got engaged in the social impact sectors because I was a beneficiary what my parents, or my mom was relatively poor.
• 3:52
  Speaker 4: We were on food stamps, and so you know I was in food banks, I was in kitchens and pretty early on, where how to give back and what it meant to have local organizations, small organizations in small communities, that ever providing services for people at need.
• 4:10
  Speaker 2: That was the most succinct, powerful elevator speech about somebody's upbringing to their career.
• 4:16
  Speaker 1: That is amazing.
• 4:17
  Speaker 2: Thank you for saying that You're honoring your mom with this work.
• 4:19
  Speaker 2: Thank you so much.
• 4:20
  Speaker 2: What about you, Justin?
• 4:22
  Speaker 3: Well, it all comes back to moms, doesn't it Right?
• 4:24
  Speaker 3: So no, I have a similar story.
• 4:27
  Speaker 3: My mother is a child protective services investigator in Seattle Washington.
• 4:32
  Speaker 3: My father built a small nonprofit, which has now turned into a not larger nonprofit, which is senior services, first in the Homish County, and you know, as two 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.
• 4:57
  Speaker 3: My mom had an incredible run, an incredible career.
• 5:01
  Speaker 3: 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 and through my work.
• 5:16
  Speaker 2: Oh, that's incredible Legacy building, John.
• 5:18
  Speaker 2: Before you jump in on the first question, we got to name the moms here.
• 5:21
  Speaker 4: Let's give them a shout out.
• 5:23
  Speaker 2: Give us their names guys Barbara and Teri, Barbara and Teri Good women Raising my iced coffee to them right now.
• 5:32
  Speaker 1: I mean thank you both for your vulnerability.
• 5:34
  Speaker 1: 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.
• 5:43
  Speaker 1: So thank you for being vulnerable enough to take us into those places today.
• 5:47
  Speaker 1: So I want to hear about let's set some tone and tell us about Microsoft tech for social impact, like what's the scope of your work and mission?
• 5:54
  Speaker 3: Yeah, you know, and I'll just say one note, john Everybody in tech for social impact has their own story and it's what makes the team so special.
• 6:02
  Speaker 3: They're all a great group of people with with very mission driven attitude.
• 6:05
  Speaker 3: But when we look at the tech for social impact business, we really look at the nonprofit and IGO industry.
• 6:14
  Speaker 3: So the UN entities, the development banks there's 10 to 12 million of these organizations worldwide and they in the United States, as an example, command over $2 trillion in total revenues.
• 6:27
  Speaker 3: 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.
• 6:47
  Speaker 3: So that's why we created the tech for social impact team 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.
• 7:02
  Speaker 3: We brought together both affordable offers you mentioned I think you mentioned $5 billion.
• 7:09
  Speaker 3: We'll do $3.9 billion of discounts and donations per year, so supporting 325,000 organizations.
• 7:18
  Speaker 3: So affordability is a big part of our strategy, so that that nonprofits have access.
• 7:25
  Speaker 3: Eric leads technology, so we built specific patterns and solutions for critical processes like fundraising and program delivery.
• 7:33
  Speaker 3: 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 TechSoup to do that.
• 7:47
  Speaker 3: 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 good 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 in the way that we serve the sector.
• 8:20
  Speaker 2: Wow, I mean just some casual numbers there and I really think you're right, john, it's easy to gloss over the numbers, but when you think about $3.9 billion being invested in a nonprofit and I think about the systemic issues that 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 two string budgets working off a database of Excel, and it's just so gracious and we really appreciate that all that you're doing.
• 8:52
  Speaker 2: And I just think the AI conversation is just booming.
• 8:56
  Speaker 2: 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.
• 9:12
  Speaker 2: How do we connect with people who are, who are really passionate about our mission?
• 9:16
  Speaker 2: 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.
• 9:26
  Speaker 2: It's embedded in almost everything we do.
• 9:28
  Speaker 2: It's in our workflows, it's embedded in data.
• 9:30
  Speaker 2: Whether you like it or not, it is here.
• 9:33
  Speaker 2: So if you can just talk to us about where 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.
• 9:48
  Speaker 3: Yeah, I think we're going to get through that in the discussion.
• 9:50
  Speaker 3: You know it's funny is 25 years ago when I started my career at Microsoft, it was on an AI project.
• 9:54
  Speaker 3: It was on machine learning to optimize certain things we were doing in our supply chain.
• 9:58
  Speaker 3: So AI has been around for a long, long time and we've been using it and it's been incrementally improving.
• 10:06
  Speaker 3: But what's been breathtaking and surprising, I think, 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 the very unique problems that it's able to solve.
• 10:26
  Speaker 3: You know, just in a matter of days, when we've launched Bing Chat, we saw over 400,000 nonprofit users working with Bing Chat to do everything from drafting initial donor proposals to analyzing grants, and so it is actually getting a lot of adoption and there is a lot of speed.
• 10:48
  Speaker 3: But we've got to kind of gone through this hype cycle right when AI was first going to save the world and then it was going to destroy the world, and I think we all have whiplash.
• 10:58
  Speaker 3: Yes, yes, all of it, and I think people are now kind of in the stage of like, well, how do we use it usefully?
• 11:04
  Speaker 3: And so, as we go through this conversation, I think we're going to highlight some of the ways that we think AI can really make an impact in fundraising, in donor engagement, in delivering missions.
• 11:14
  Speaker 3: But it's here, right, and it's powerful and there's a lot of capability yeah.
• 11:17
  Speaker 4: But back to you.
• 11:18
  Speaker 4: You're exactly right.
• 11:19
  Speaker 4: Like you can't stop the tide, right?
• 11:21
  Speaker 4: 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.
• 11:29
  Speaker 4: You know that.
• 11:29
  Speaker 4: I think it's the sun also rising, the Hemingway quote around.
• 11:33
  Speaker 4: You know how did you go bankrupt gradually, then, suddenly, that's how we're experiencing AI.
• 11:37
  Speaker 4: Right, we spent years where AI was really the purview of you know, really well-funded projects with data scientists and big data solving big problems.
• 11:47
  Speaker 4: You saw these lighthouse projects, you know, here and there.
• 11:50
  Speaker 4: And then GPT came along last November and it's everywhere.
• 11:53
  Speaker 4: You know it's really democratized.
• 11:54
  Speaker 4: The access to AI in productivity tools we use every day.
• 11:59
  Speaker 4: You know, gary, to you, if you're a non-profit thinking about using AI, you're already using AI.
• 12:04
  Speaker 4: You're smart.
• 12:05
  Speaker 4: We're using big chat enterprise or experimenting with it in other places.
• 12:09
  Speaker 1: I mean let's double click.
• 12:11
  Speaker 1: I love all this tone setting that we're doing.
• 12:12
  Speaker 1: Let's double click into, like, what is the impact specifically on fundraising, on donor engagement and then program effectiveness that y'all are seeing?
• 12:19
  Speaker 4: 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 how fundraising is happening, like we've all kind of know some of the generational shifts that are happening.
• 12:32
  Speaker 4: And then with COVID lockdown, that really forced different ways of giving and it's challenging for non-profit 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.
• 12:46
  Speaker 4: 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 giving trend data together with the data that you have in your own systems, whether that's an Excel database or whether that's an NSE or M system, and so I think 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.
• 13:18
  Speaker 4: It's happening in both areas, but I think everyone is recognizing, first of all, every non-profit fundraisers and so it's kind of a natural place for all of us to go.
• 13:26
  Speaker 4: But it's been really interesting to see some of the partnership conversations that have come up.
• 13:30
  Speaker 4: We're, as Microsoft, a huge believer in having open standards, interoperability and making sure that you know we're playing our role as a platform technology company that can help light up 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 into technology and solutions that we and our partners can take forward in very specific fundraising scenarios.
• 13:58
  Speaker 3: Well, and maybe I just add one additional on the program side, john, given that you asked the question.
• 14:03
  Speaker 3: You know, there we're seeing kind of a thousand flowers bloom, and I'll give you one example of a pretty compelling use case.
• 14:09
  Speaker 3: So we're working with the International Criminal Court, not necessarily a small maldravid.
• 14:13
  Speaker 3: They are the largest court in the land that prosecutes war crimes, right, Humanitarian war crimes, when a state can't or won't do it, and so they're operating in Ukraine.
• 14:26
  Speaker 3: They're operating in many, many different places and it turns out war crimes are documented.
• 14:32
  Speaker 3: There's a lot of documents, photos, social feeds, videos that need to be analyzed.
• 14:38
  Speaker 3: 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.
• 14:59
  Speaker 3: What that results in is prosecution right, and what that results in is just as faster for those that have been victims of war crimes.
• 15:08
  Speaker 2: I mean that was probably the most perfect example, and I mean war is very heavy on all of our hearts right now.
• 15:15
  Speaker 2: We're all thinking about it and I do think that what an incredible use case.
• 15:19
  Speaker 2: And I'm also sitting in a space of gratitude that Microsoft, that individuals like yourselves are doing this work and making those connections because, eric, you said the phrase that scares all of us and nonprofit, which is adjust rapidly and that is not our skill set trying to move quickly, and yet we find ourselves standing in this world right now.
• 15:44
  Speaker 2: That is largely new for so many that we're either maybe tech averse or didn't have time or resources for it.
• 15:54
  Speaker 2: So I thank you for really trying to help accelerate us forward and I want you to kind of talk about the key challenges that you all are seeing nonprofits are facing, like with their fundraising today, and how are you seeing AI uniquely positioned to address those challenges.
• 16:11
  Speaker 2: 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.
• 16:19
  Speaker 4: Yeah, so really really specifically couple pieces of technology that we're working on.
• 16:25
  Speaker 4: One is a likelihood to donate model, and so we're dealing with nonprofit organizations, the fundraising data that they have today.
• 16:33
  Speaker 4: What are some of the giving patterns that individual donors have?
• 16:37
  Speaker 4: Is there seasonality there?
• 16:38
  Speaker 4: Is there cause alignment for certain individuals?
• 16:41
  Speaker 4: Do they have networks?
• 16:43
  Speaker 4: How do they give?
• 16:44
  Speaker 4: And then scoring that and what is the next best ask what's the likelihood to donate for certain individuals?
• 16:51
  Speaker 4: How do you align that your campaigns to those individuals and 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.
• 17:06
  Speaker 4: So that's one piece.
• 17:07
  Speaker 4: Back to the interoperability piece, we're also very proud to be a member of the Giving 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 trends in fundraising and use that as you're developing your campaigns and your approaches.
• 17:29
  Speaker 3: Yeah, and I just have one additional thing.
• 17:31
  Speaker 3: I mean, I think in the nonprofit industry, I think we as a technology community haven't invested enough in kind of the fundamental skills required to what's this thing called prompt engineering.
• 17:43
  Speaker 3: How do I write 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 going to be really effective, whether my job's a fundraiser or a program delivery person or whatever the function may be COO, cfo and there I think we're focused on fundamental skilling 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.
• 18:11
  Speaker 3: It's free of charge.
• 18:12
  Speaker 3: You can 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.
• 18:28
  Speaker 3: So sometimes it's just starting with getting skilled up.
• 18:31
  Speaker 4: It's one of the most important things that I think about why I'm at Microsoft, why did I leave the nonprofit sector and come here?
• 18:39
  Speaker 4: It's because we think holistically not just about the technology but also about the capacity build.
• 18:44
  Speaker 4: When I was at Path, I used to talk about the way technology evolves is a river.
• 18:49
  Speaker 4: It is not going to stop the innovation.
• 18:52
  Speaker 4: The pace of that change likely is only going to increase At some point.
• 18:56
  Speaker 4: You have to jump in If you're waiting for things to slow down so that you can align yourself to the technology that you have more confidence in.
• 19:02
  Speaker 4: It's not the world we're in today.
• 19:04
  Speaker 4: You really need to think about how you're engaging this.
• 19:08
  Speaker 4: One of the ways that we think about it is we provide a lot of skill and content and a lot of engagement with nonprofit communities and communities in general about how to build that digital literacy.
• 19:51
  Speaker 1: Y'all are kindred spirits.
• 19:52
  Speaker 1: You're putting the pieces out there for us to pour into.
• 19:55
  Speaker 1: We're a growth mindset oriented community.
• 19:57
  Speaker 1: We talk about the power of just learning the things we don't know.
• 20:00
  Speaker 1: Everything is figureoutable, especially coming at it with this open hand to what we can figure out.
• 20:05
  Speaker 1: I love the honorable.
• 20:07
  Speaker 3: Amazing.
• 20:07
  Speaker 3: I love it so much.
• 20:08
  Speaker 3: We've talked about the power of this.
• 20:16
  Speaker 1: There's so much still coming at us.
• 20:18
  Speaker 1: Y'all also lean into just responsible use.
• 20:20
  Speaker 1: It's on the forefront of all of our minds.
• 20:22
  Speaker 1: In the nonprofit space, y'all put together some core principles that guide fairness, accountability, transparency, etc.
• 20:28
  Speaker 1: I'd love for you to walk us through some of those.
• 20:30
  Speaker 1: Can you lift some of the most important aspects of this conversation?
• 20:33
  Speaker 1: I know it's in there, it's in our minds as we approach this from the nonprofit, that are seeking justice and trying to not create more harm in the work that we do.
• 20:42
  Speaker 3: It's critical.
• 20:42
  Speaker 3: I'm glad you brought it up, john.
• 20:44
  Speaker 3: Years ago, as we were doing our work on AI, we built a responsible AI framework that has six core principles, as you started to enumerate their fairness, accountability, transparency.
• 21:00
  Speaker 3: It was important as how they're used in the way that we engineer our product.
• 21:06
  Speaker 3: 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.
• 21:25
  Speaker 3: They're auditable and verifiable.
• 21:27
  Speaker 3: These are critical principles.
• 21:30
  Speaker 3: Now, if I took a step back and said, what principle am I most concerned about at the moment?
• 21:35
  Speaker 3: Where do I see the biggest challenge?
• 21:37
  Speaker 3: Right, having spent a lot of time in the last well, I'll just say six months 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 a tough problem, right?
• 21:59
  Speaker 2: It's a tough problem.
• 22:00
  Speaker 3: 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 one of those superpowers is language right.
• 22:37
  Speaker 3: Being able to interact through local language with a computing system and get what you need whether you're making a payment, whether you're filing for a property permit, whether you're getting information on your farm right and the soil conditions and what you need to plant and being able to do that in what we would 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 or Microsoft research team is working hard on these problems to ensure that not only does AI support us here in Redmond and Seattle, but it's actually helping narrow that digital divide in the global south.
• 23:20
  Speaker 3: And we have a lot of work to do.
• 23:21
  Speaker 3: I'll be honest with you we have a lot of work to do, but it's something that we're very focused on.
• 23:26
  Speaker 4: I would maybe add a couple things about what is.
• 23:28
  Speaker 4: Principles are great, but they're not really effective 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 co-pilot resources or any open AI components are adherent to that policy.
• 23:55
  Speaker 4: But it's not just us.
• 23:56
  Speaker 4: We provide the guidance of the toolkits for any technology partner, 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.
• 24:09
  Speaker 4: 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 privacy and security layer, like how, as an organization working with vulnerable populations, can you trust that LLM?
• 24:29
  Speaker 4: How can you trust GPT using your data and make sure that we have the transparency and control that organizations want to be able to combine their own organizational private data together with a well-trained large language model and really get the best results as you combine those two things without exposing the data for the population that you serve.
• 24:54
  Speaker 2: Justin, Eric, I like you so much.
• 24:58
  Speaker 2: You guys get it.
• 25:00
  Speaker 2: I mean, it is true when you talk about we could have these ethical principles, we could put them on a poster, we could, you know, rah-rah at our team meeting.
• 25:08
  Speaker 2: But when you bring it back to the human who's actually trying to connect, I'm going to share a story from somebody within our community.
• 25:17
  Speaker 2: We have an incredible community member.
• 25:18
  Speaker 2: 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.
• 25:33
  Speaker 2: We have been working like mad to try to get a giving platform up so he could accept credit cards.
• 25:40
  Speaker 2: We have worked to get him a new laptop because he hasn't had one in 15 years.
• 25:45
  Speaker 2: You know, small changes like this not only do they transform his nonprofit, it transforms the community, it can, transforms connectivity.
• 25:56
  Speaker 2: It brings not just resources in, but it opens the world.
• 26:01
  Speaker 2: And I just I mean we have such a heart for Haiti and you think about the infrastructure in a marginalized population by that.
• 26:07
  Speaker 2: But even in the United States, I mean, we have trafficking organizations and hunger organizations and you get so mired in helping the beneficiary on the front line that you kind of forget to prioritize these things without thinking this is the long game.
• 26:22
  Speaker 2: This is going to help you play the long game in every possible way.
• 26:26
  Speaker 2: So thank you for living and seeing humans.
• 26:30
  Speaker 2: 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.
• 26:40
  Speaker 2: 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.
• 26:49
  Speaker 2: You know that are going to be surfacing, and how do we address that?
• 26:53
  Speaker 2: 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.
• 27:01
  Speaker 2: Would love either one of you to take that.
• 27:04
  Speaker 4: Yeah.
• 27:04
  Speaker 4: So, from a training perspective, 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.
• 27:22
  Speaker 4: So how do we effectively work with United Nations missions?
• 27:26
  Speaker 4: How do we work with humanitarian global humanitarian organizations?
• 27:29
  Speaker 4: How do we work with the small health and human services organizations and urban environments?
• 27:35
  Speaker 4: Part of this is large language models are trained on data that's publicly accessible on the internet.
• 27:42
  Speaker 4: How are you managing your data and ensure that you've got the right practices inside your organization?
• 27:49
  Speaker 4: So, first and foremost, you're not exposing the data for potential consumption by any LLM, but understand the engagement between how an LLM is trained large language model is trained, like GPT and how you use your own organizational data.
• 28:07
  Speaker 4: And so what we're working on are ways that where these generic models are trained and how they're applicable in specific scenarios, be they no-profit scenarios or other industry scenarios and how you combine your own organizational data with the trade model in ways that give you the richness that allow you to then either drive more directed program impact or whatever it is.
• 28:32
  Speaker 4: And so we're in the, as 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 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.
• 28:59
  Speaker 4: It helps us, as a major technology player, learn what we need to learn to ensure that where we are seeing biases, we could help you tune and adjust.
• 29:08
  Speaker 4: Where we see the opportunity for creating maybe different approaches for large language models, as Justin was talking about, for lower resource settings, that we can make our investments wisely.
• 29:19
  Speaker 3: Yeah, the only thing I just add to that is we often say at Microsoft, you'll hear us around the halls talking about how Microsoft is built on trust.
• 29:28
  Speaker 3: And, 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 the business model that we have, and we hope that that business model engenders trust, both in the way that we talk 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.
• 30:01
  Speaker 3: Right For control, thank you For control, and that is just, I think, critical so that organizations have choices that they can make to use these models in the most appropriate ways.
• 30:14
  Speaker 1: Love that Well.
• 30:15
  Speaker 1: I mean I'm feeling the need to transition to activation.
• 30:19
  Speaker 1: 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.
• 30:25
  Speaker 1: A lot of people listening are wanting to implement new technologies, but we know it's going to come with challenges.
• 30:30
  Speaker 1: We've addressed the big elephant in the room.
• 30:32
  Speaker 1: We have to have a growth mindset.
• 30:33
  Speaker 1: So that's table stakes here.
• 30:34
  Speaker 1: But what are some other challenges they nonprofits could face when adopting AI?
• 30:39
  Speaker 1: What have y'all seen specifically for, maybe fundraising, and how can they overcome these hurdles?
• 30:44
  Speaker 3: Well, I think and then Eric just will just riff on this one together I think one of the questions is like how do I even get started?
• 30:49
  Speaker 3: Like how do I get?
• 30:51
  Speaker 3: into gear on anything Right, and let's start simply.
• 30:55
  Speaker 3: Right, let's start simply.
• 30:57
  Speaker 3: Which is number one what let's figure out, what are the resources that we can deploy to help build that knowledge, that clear essentials on generative AI is a four-hour course you can take it.
• 31:09
  Speaker 3: It's a great course as an example, and that will equip you with the fundamental kind of language and knowledge and and it's help me actually figure out a right prompts that we're 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'll be helpful.
• 31:27
  Speaker 3: The second thing is just get started.
• 31:30
  Speaker 3: 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.
• 31:47
  Speaker 3: Now, what is Bing chat enterprise?
• 31:48
  Speaker 3: It's Bing chat with all of the enterprise security and controls that you would want to use inside of a, inside of an organization, and it's it's freely available, and so getting people the starting to use Bing chat enterprise for writing a grant proposal, for analyzing a fundraising plan, is just a great starting point.
• 32:11
  Speaker 3: It's low friction.
• 32:11
  Speaker 3: You don't need it to implement anything, you just get started.
• 32:15
  Speaker 2: Hello, yeah, that's important right.
• 32:17
  Speaker 2: No offense guys.
• 32:19
  Speaker 3: What important point is.
• 32:20
  Speaker 3: Of the 325,000 organizations that we serve, like 320,000 of them are about seven people or less.
• 32:27
  Speaker 3: 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 Managing director, right?
• 32:38
  Speaker 3: So, yeah, we gotta be, we gotta be really honest about making it easy to use this technology, not and, and that that is the the next easiest step, the third step, right.
• 32:47
  Speaker 3: If we were to then try to get to more advanced levels, right is Alright.
• 32:52
  Speaker 3: 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?
• 33:04
  Speaker 3: They do require skills and some knowledge and we've got good training on that.
• 33:07
  Speaker 3: 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 with the bank.
• 33:26
  Speaker 3: That drives you crazy, right?
• 33:27
  Speaker 3: It's much more intelligent than that.
• 33:29
  Speaker 3: I think one of the most powerful tools for small organizations, small nonprofits, is going to be the Microsoft Office co-pilot.
• 33:39
  Speaker 3: Now, today there's a 300 seat limitation.
• 33:43
  Speaker 3: We're working on bringing that down right.
• 33:45
  Speaker 3: We got, we're doing that work.
• 33:47
  Speaker 3: But if you think about what is the number one fundraising system?
• 33:50
  Speaker 3: What's the number one accounting system?
• 33:52
  Speaker 3: What's the number one HR management system in the world?
• 33:55
  Speaker 3: It's probably Excel and bringing intelligence across all of your documents, all of your email, all of your Systems that you're running in Excel.
• 34:04
  Speaker 3: For your smaller organization, that is going to be a game changer.
• 34:08
  Speaker 3: 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.
• 34:20
  Speaker 4: I'll give 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.
• 34:28
  Speaker 4: So we, we have a really simple demo where you can go into a Bing chat enterprise and enter a prompt like as an executive director for a food bank in a Community, I need to organize a food drive for Thanksgiving.
• 34:42
  Speaker 4: Write me up, you know, write me an appeal letter and you will get a first draft of an appeal letter.
• 34:47
  Speaker 4: Is it perfect?
• 34:48
  Speaker 4: No, probably not, but it's a great place to start.
• 34:50
  Speaker 4: So you're not sitting there looking at a blank piece of paper.
• 34:53
  Speaker 4: How do I, how do I eat?
• 34:54
  Speaker 4: You know this, this, this artifact.
• 34:57
  Speaker 4: Another example on what Justin was saying around power virtual agent if you're an organization that has an FAQ or has Annual report, you can load that FAQ or load that annual report into power virtual agent.
• 35:13
  Speaker 4: Takes about 10 or 15 minutes.
• 35:14
  Speaker 4: I'm to go through the whole process and now you have a chat bot that can answer questions about your annual report or, you know, captain, interactive Chatbot for for your FAQ.
• 35:24
  Speaker 4: We've, you know, tried really hard to make 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 know, really, in the Arctic quite yet.
• 35:41
  Speaker 4: I was talking with a family foundation based here in the Northwest.
• 35:44
  Speaker 4: They have an annual proposal drive.
• 35:47
  Speaker 4: They finished their funding cycle four months earlier this year because the quality of the proposals work and the amount of proposals Were coming in so quickly and it was because we're using chat GBT to write the proposals.
• 36:01
  Speaker 4: So, pointing chat GBT on your proposal library, looking at the RFP, write me a proposal based on what we've done before and what's been successful and it will give you a first draft of our proposal response.
• 36:10
  Speaker 4: So we're already seeing kind of some of these really practical use cases where people are experimenting with the technology.
• 36:16
  Speaker 4: So, as Justin said, the capacity building is essential and You've got access to these tools today now, becky and John, I've got a question for you.
• 36:26
  Speaker 3: Are you using I know, are you using any of these GPT power tools for any of the work that you're doing, and what are you finding?
• 36:37
  Speaker 2: We have to.
• 36:38
  Speaker 2: There's just too much going on and and I mean I, I have I was telling the story the other day.
• 36:43
  Speaker 2: I mean I even got chat GPT out for my attorney husband the other day who had never used it and 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.
• 37:09
  Speaker 2: And I really Appreciate what you've been saying, like Eric, 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 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 gonna help boost us.
• 37:38
  Speaker 2: I'm on the hopeful side of AI.
• 37:41
  Speaker 2: I actually think that it's gonna breathe.
• 37:43
  Speaker 2: 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 and work that we have to carry with so little resources.
• 37:57
  Speaker 2: The mental health you bring up mental health, justin.
• 37:59
  Speaker 2: I mean we are 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 it more efficient, find the right people.
• 38:13
  Speaker 2: We're talking about prompts.
• 38:15
  Speaker 2: Like we're geeking out About the prompt thing.
• 38:17
  Speaker 2: That is total idiot proof.
• 38:19
  Speaker 2: I want that you know and give me what the data is telling me.
• 38:22
  Speaker 2: So I just I just celebrate that what you all have done on the tech for social impact side and I just want anyone listening to just feel like do a 1% shift.
• 38:33
  Speaker 2: That's what we say in here.
• 38:35
  Speaker 2: Pick one thing, pick one thing, try it out.
• 38:38
  Speaker 2: You know, do one a week.
• 38:40
  Speaker 2: Once that gets comfortable, do one a day.
• 38:42
  Speaker 2: Start getting in flow of this share what you know, because we think that we're gonna fail forward but we're gonna fail faster together.
• 38:50
  Speaker 2: 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?
• 39:00
  Speaker 2: Where's the best place that we connect, could connect them up?
• 39:03
  Speaker 3: Yeah, I think a couple of places.
• 39:04
  Speaker 3: What one place is for that training?
• 39:06
  Speaker 3: I think LinkedIn is a great location.
• 39:09
  Speaker 3: 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 resource that start there.
• 39:21
  Speaker 3: That's the first thing.
• 39:22
  Speaker 3: Second thing is to get access to the technology that we were talking about.
• 39:26
  Speaker 3: Go to Microsoftcom forward slash, 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, what you need to enable, you know.
• 39:46
  Speaker 3: 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?
• 39:55
  Speaker 3: I do want to know that you know what it is.
• 39:58
  Speaker 3: I think it's ubiquity.
• 39:59
  Speaker 3: I think it is the fact that in everything you do, whether it's donor retention, campaigns, event design, it's gonna be built into the tools kind of by by default.
• 40:12
  Speaker 3: 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 Non-profit leaders.
• 40:23
  Speaker 3: It's not about replacing right, it's about being the co-pilot, a ubiquitous co-pilot, in every single Activity that you do.
• 40:30
  Speaker 3: That helps you just do it faster or more efficiently, more effectively, so that you can unleash your, your creativity To solve the problems that you're trying to solve in your communities.
• 40:40
  Speaker 3: And that's why we named every one of our technologies co-pilot, because we, we, we think they're an assistant to, to human ingenuity, not replacing human ingenuity, the only thing.
• 40:52
  Speaker 4: I would.
• 40:53
  Speaker 4: 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 and the partners that we work with the technology partners that we work with can engage more effectively.
• 41:12
  Speaker 4: So we're really leaning in to create space for An additional nonprofit community that that is thinking about the application of AI.
• 41:23
  Speaker 3: And we're launching that community.
• 41:24
  Speaker 3: I'll say we're launching an online platform at the end of January, so you'll see us roll that out, which will be a virtual space where nonprofits can go, engage in topics, talk about these things will have experts on standby to make sure that we're providing input to those communities so that nonprofits can support nonprofits and we could be part of that process to.
• 41:48
  Speaker 2: So, cool communities.
• 41:49
  Speaker 3: Everything I was going to say, that's one of our values here.
• 41:53
  Speaker 1: 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, the person.
• 42:07
  Speaker 1: I want to give you all space to talk about a moment of philanthropy that's happened to you in your life.
• 42:12
  Speaker 1: We celebrated on the daily we fight.
• 42:14
  Speaker 1: These are the moments that are sometimes small but they stick with us, our life.
• 42:17
  Speaker 1: I'd kick it to you, eric, to take us back to one of those times.
• 42:20
  Speaker 4: Yeah, absolutely.
• 42:21
  Speaker 4: So.
• 42:21
  Speaker 4: I will tell you about the first time I went to Africa when I was a new employee at path.
• 42:27
  Speaker 4: Path is a large school 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 Kaka Mega.
• 42:39
  Speaker 4: And so you spent six years flying to Nairobi and then you fly to Kasumu and then you get in a Jeep and you drive to Kaka Mega and you're really amazing experience.
• 42:52
  Speaker 4: 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.
• 43:01
  Speaker 4: And I did not expect that we had an act this form that they used to order medications for the clinic from the central store Nairobi, and there was a new medication he knew was available but it wasn't available in the application and the simple question was how do I add it?
• 43:23
  Speaker 4: So in this situation, for organizations that are grant funded organizations working in technology, you'll recognize some of this as pilot ITIS.
• 43:33
  Speaker 4: Every grant at every program resulted in a small point of service application that didn't connect to anything else.
• 43:42
  Speaker 4: There weren't data standards, there wasn't ever interoperability.
• 43:45
  Speaker 4: What was this application?
• 43:46
  Speaker 4: If you were a doctor or a nurse in this clinic, you had two phones with five apps and you were working with one individual and doing your survey and asking malaria questions.
• 43:54
  Speaker 4: I go into this survey tool and that's phone.
• 43:56
  Speaker 4: And now we're talking about HIV, aids and it's this phone and this survey.
• 44:01
  Speaker 4: 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.
• 44:21
  Speaker 4: 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.
• 44:31
  Speaker 4: 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 and data and our operability.
• 44:40
  Speaker 4: So it really became kind of core to me on how I engaged when I was in the nonprofit sector and a big reason why I came into Microsoft.
• 44:51
  Speaker 2: I love topping that Justin.
• 44:54
  Speaker 3: No, it's a different story 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.
• 45:07
  Speaker 2: Oh, we love Team Rubicon I love Team Rubicon.
• 45:09
  Speaker 3: 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.
• 45:19
  Speaker 3: They go out and work in areas that need support, and we deployed out with the Team Rubicon team to the Midwest that was absolutely devastated by these floods.
• 45:33
  Speaker 3: These 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.
• 45:45
  Speaker 3: You know just what they called mucking out a house and so that's with the shovel and just clearing debris and mud all day long.
• 45:54
  Speaker 3: 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 barriers that the law enforcement had put up and got back to their home and they just broke down.
• 46:17
  Speaker 3: You know, when they saw 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 what was a relatively small act of service can make such a huge difference in somebody's life.
• 46:36
  Speaker 3: And to see that, to feel that, to see the gratitude of that family and their emotion as they were coming back into their home was just a reminder to me of why we do what we do.
• 46:49
  Speaker 3: 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.
• 46:59
  Speaker 3: So it's multiplied by a million or more.
• 47:03
  Speaker 3: And if we in our work can make those organizations just 1% more efficient to your point, john, I'd like to make them a lot more than 1% more efficient, but just 1% more efficient.
• 47:13
  Speaker 3: The world helped a lot of people.
• 47:15
  Speaker 3: We'll have been a part of helping a lot of people and enabling this great industry here and around the world.
• 47:22
  Speaker 2: You guys are such good dudes.
• 47:24
  Speaker 2: I'm not kidding.
• 47:26
  Speaker 2: I just think sometimes we can gloss over the veneer of things just because you have these big titles.
• 47:33
  Speaker 2: You work at this massive company that is one of the most well-known brands in the world.
• 47:41
  Speaker 2: But at the end of the day, it's about humanity.
• 47:43
  Speaker 2: It's about looking that person in the eye and saying you know, it was my pleasure to be here, to muck out and give you space to come back in.
• 47:53
  Speaker 2: It was my pleasure to be able to put that prescription in so that you don't have to suffer from whatever it is that you're suffering.
• 48:02
  Speaker 2: And I just think if we can all embrace this, we all can do something, sort of mentality then that's.
• 48:09
  Speaker 2: You used the word generative before.
• 48:11
  Speaker 2: That's generative to the world.
• 48:12
  Speaker 2: And so I just am sitting here with a heart full of gratitude, feeling like Justin and Eric have got tech for social impact and such good hands, and we kind of wind down all of our conversations with a one good thing.
• 48:25
  Speaker 2: And it could be a piece of advice, maybe a life hack.
• 48:28
  Speaker 2: What would be your one good thing?
• 48:30
  Speaker 3: Okay, well, john already said it.
• 48:32
  Speaker 3: In fact, my thing would be growth mindset.
• 48:36
  Speaker 3: 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 challenge and setback.
• 48:51
  Speaker 3: 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.
• 49:04
  Speaker 3: That resilience is all encapsulated in this idea of growth mindset and I think it's just such a critical attribute for us in this ever changing and what feels like a much more volatile world to keep front and center in the way that we work.
• 49:19
  Speaker 4: So I'm a, I'm a certain sky.
• 49:21
  Speaker 4: So I like catch that growth mindset like change.
• 49:25
  Speaker 2: That's why you're so good together.
• 49:28
  Speaker 4: This kind of change, that this effort, think about it.
• 49:31
  Speaker 4: Think about how.
• 49:32
  Speaker 4: How do you need to train your staff?
• 49:33
  Speaker 4: How do you need to train yourself?
• 49:34
  Speaker 4: How do you introduce these concepts into your organization?
• 49:37
  Speaker 4: How is it going to impact your donors?
• 49:39
  Speaker 4: And you know quick example there you know again back to how an organization was quickly using chat GBT where a fundraising officer, her native language wasn't English and she was started using chat GBT in the donor communications and the donors were coming back and saying did you hire someone new?
• 49:57
  Speaker 4: And no, it was that.
• 49:59
  Speaker 4: You know it gave this fundraising officer so much more confidence to be able to engage with the donors.
• 50:06
  Speaker 4: But you know that kind of change and how you think about introducing these concepts does take some, some conscious effort and change management with the organization.
• 50:14
  Speaker 1: Incredible.
• 50:14
  Speaker 1: I mean, wait around this out, fellas.
• 50:16
  Speaker 1: This has been such a delight of a conversation.
• 50:19
  Speaker 1: 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 to this free resources and all the good that Microsoft's brought.
• 50:28
  Speaker 3: Yeah, I know I think the best way is probably LinkedIn.
• 50:30
  Speaker 3: So you can find me, justin Spahog, and you can find Eric Ronald, who's prolific on LinkedIn, and connect with us.
• 50:37
  Speaker 3: We'd love to do that.
• 50:38
  Speaker 3: And then again on LinkedIn, we again have that generative AI learning pathway.
• 50:45
  Speaker 3: Look that up, it's four hour course.
• 50:47
  Speaker 3: You can take the first four minutes or all of it, and then again at Microsoftcom.
• 50:53
  Speaker 3: Slash nonprofits is where you'll find all of the resources available to you.
• 50:58
  Speaker 3: So those will be the main areas.
• 51:00
  Speaker 2: Eric, justin, you have done Barbara and Terry so proud today and every day as you work and walk through this life and the way that you do.
• 51:09
  Speaker 2: Thank you for coming in, thank you for just the way you have poured into this community.
• 51:13
  Speaker 2: We will see you over in your community and your platform at the end of January.
• 51:17
  Speaker 2: It'll be exciting.
• 51:18
  Speaker 2: Thank you for your input.
• 51:19
  Speaker 1: Thank you, friends, awesome, thank you.
• 51:21
  Speaker 1: Thank you.
• 51:22
  Speaker 1: Thanks so much for being here, friends, and you probably hear it in our voices, but we love connecting you with the most innovative people to help you achieve more for your mission than ever before.
• 51:33
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• 51:35
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• 51:39
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• 51:42
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• 51:44
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• 51:48
  Speaker 1: It means the world to us and your support helps more people find this community.
• 51:51
  Speaker 1: Thanks so much, friends.
• 51:52
  Speaker 1: Can't wait to our next conversation.