This conversation between tech industry and global health insiders about how AI will create opportunities to do good and how large companies can support those people. This conversation took place at Imagination In Action’s ‘Forging the Future of Business with AI’ Summit in April 2024.
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TechTranscript
00:00My name is Jacek Siedkowski, I'm the CEO of Tech to the Rescue.
00:05And to end up this beautiful day, I want to take you for a journey to how AI can solve
00:10social problems.
00:12So throughout the day, we have been talking a lot about how AI can be pushed forward when
00:17it comes to capabilities, how it could be used to make a profit in businesses, but I
00:22think there's one very special thing that we need to think about a lot, and it's social
00:27impact.
00:28Why?
00:29Because there's so many social problems that we could solve with AI, but to do it well,
00:33it's very difficult to achieve only by technologists.
00:38So there's one special group of people I want to talk to you about who are essential to
00:42really solve those social problems, and I call them changemakers.
00:46So let me tell you a story of Paul Radu, he's an investigative journalist from Romania.
00:53I call him changemaker because 15 years ago, he started working in journalism, and he started
00:58working on investigative cases of crime worth of billions of dollars.
01:03And it's very difficult, because when we speak about the crime of that size, it very quickly
01:07becomes international, there are many players, many countries involved, so you cannot really
01:11do this work alone.
01:13So he started a network of investigative journalists around the world.
01:17He managed to create a network of over 1,000 people.
01:21But still, to do this investigative work is very difficult, it takes months of research.
01:26So he had this idea that maybe someone could build a joint database of organized crime
01:31around the world and use AI to really help those researchers and investigative journalists
01:37do this work quicker.
01:38So he created an app which is called Aleph, it's open sourced, it operates for the last
01:43two years, and the app helps journalists do the work that usually used to take a couple
01:49of months, right now in hours.
01:51And through the app, they managed to recognize and publish history of crimes of over $10
01:56billion.
01:57But Paul was lucky, because Paul had an access to people who really can build AI for him.
02:05But it's not the case for most of the changemakers.
02:08So changemakers I define as people who spent a couple of years working on social problems,
02:13who perfectly understand how to solve them, but they need technology in order to scale
02:17up their operations.
02:19But 93% of them lack technology or lack resources or say that they miss technology talent to
02:26really push their work forward.
02:28And to solve this problem, there needs to be a movement of tech companies that want
02:33to help them and support their work to really drive the impact.
02:36And that movement already exists.
02:38It's called Tech to the Rescue, I am happy to run the movement.
02:42We managed to create a network of over 1,500 tech companies from 60 countries who joined
02:48us with a willingness to provide at least one pro bono project per year for a nonprofit.
02:53In the last three years, we managed to support over 700 nonprofits building technology, like
02:58technology that Paul is using for his investigative work.
03:03But the basic technology, like mobile solutions or software development, is very important.
03:09But we are in front of AI revolution.
03:12And AI is different.
03:13It's more difficult.
03:14And there are more unknowns right now.
03:15So we really need to give more effort to really help those people do the job.
03:22And I'm happy to announce today that Tech to the Rescue, together with the generous
03:26support of Google.org and AWS, launches a program which is called AI for Changemakers.
03:32So together, we join forces to create an ecosystem that will enable some of the world's greatest
03:38nonprofits to do social impact work.
03:41So together, we want to scout 100 greatest organizations in the world who are working
03:47in five different fields.
03:48Education, crisis response, health, climate change, economic growth.
03:53And we want to put them in place where it's at least as easy to build tech nonprofit as
03:59it is to build tech startup.
04:02So we are putting together the most comprehensive ecosystem for those organizations to really
04:07push the AI work forward.
04:09So within the program, they will have access to education, which is workshops led by companies
04:15like IDEO.
04:16They will have access to our network of pro bono companies that want to build software
04:20solutions for them free of charge or with heavily discounted prices.
04:24They will have access to AWS compute and infrastructure.
04:29We'll organize hackathons for them.
04:30We'll organize opportunities for them to pitch their ideas to world's greatest donors.
04:35So it is designed to be a place where you can grow, build solutions, and really make
04:40social impact work.
04:42I call it this ecosystem and I call this movement because I believe that none of the company's
04:49organizations would be able to do it themselves.
04:52And together with Google and AWS, we put together a group of wonderful companies that are joining
04:57us to really make this possible.
04:59And I want to invite all of you to join us as well.
05:03So the program starts today.
05:04We already have a couple of wonderful partners like IDEO, Global Software One, or NetGuru,
05:09or monday.com.
05:11But we need more.
05:12We need to create a place where it's easy to implement AI for social good.
05:16So any company is welcome to join our movement.
05:19You can take one of the free roles so we can start building solutions and implementing
05:22the software you already have to solve social problems.
05:25You can also work with us to create infrastructure for organizations to really make this work
05:29easier.
05:30You can help us grow the ecosystem.
05:33This is very important.
05:34And without you, that won't be possible.
05:36And together we can really save lives of millions.
05:39So starting from today, we opened applications for nonprofits from disaster response and
05:44climate cohort.
05:45And we are open for working with tech companies to really make this work effective.
05:51So this is the end of the announcement.
05:53I'm happy to do it.
05:54It's a lot of months of our work.
05:57And right now I want to invite my wonderful panelists to actually talk about the whole
06:01social impact space and AI.
06:02We want to talk about why it's important, what is the opportunity, and how to make sure
06:06that this work will benefit many people globally.
06:11Wonderful people, can you join me?
06:20So these are the real people.
06:22Not all images actually match real faces.
06:26But I assure you that these are the real people, not AIs that we have at our disposal.
06:34That's AI gone rogue.
06:37So we want to talk about AI and social impact work, AI and nonprofits.
06:44We believe that it's essential to implement AI in nonprofit organizations to really push
06:48the work forward.
06:49We want to talk about what is the opportunity, what are the challenges, and how the business
06:53can support.
06:54I have some of the greatest people working in the fields in the whole world, so I'm happy
06:58for that.
06:59I have Alex Diaz, who is head of social impact at Google.
07:03I have Marnie Webb, who is chief community impact officer at TechSoup.
07:07I have Amy Guterman, who leads AI for good work at Salesforce, Maggie Carter, director
07:13of social impact at AWS, and Jackie Ugokwe, who is a community manager and works with
07:19wonderful community of changemakers at Gates Foundation.
07:23So we want to start today through talking about what can really happen if we do this
07:28work right.
07:29So starting from some real tangible examples of AI that was already used in nonprofits
07:36and works.
07:37So I want to ask some of you, starting from Alex, what type of work that Google has already
07:42done through its Google.org arm has been productive?
07:46What are the most exciting use cases of using AI for good that you've seen?
07:50Thank you, Jessica.
07:51It's such a pleasure to be on this panel with you all.
07:54We are the closer, so I need y'all's energy to help us end the day on a great note.
07:59Yeah.
08:00So I'm Alex, as Jessica mentioned.
08:02I help lead our AI for good grant making at Google.org.
08:05Google.org is Google's philanthropy.
08:08We've given over $200 million in cash in the last five years to nonprofits working at the
08:13intersection of AI and social impact.
08:15I will shine some light on some climate examples, and I know others will have examples from
08:19other domains.
08:21So listen, AI, when applied thoughtfully into domains where it's useful and helpful, and
08:28we can get into that in this panel, can be a force multiplier.
08:31Our grantees report that they can achieve their primary outcomes in a third of the time
08:35and at half the cost, which really shows that efficiency dividend that AI can provide in
08:40a programmatic side.
08:42From the climate space, there's organizations like Climate Trace that use computer vision
08:46models built on satellite images that now they can track 99% of greenhouse gas emissions
08:52at the source.
08:53That's publicly available, open source, and an open platform.
08:57You have organizations like Rainforest Connection that use acoustic technology to monitor and
09:03stop illegal deforestation in rainforests, as well as monitoring biodiversity in those
09:08rainforests and trying to help conserve and preserve endangered species.
09:14And then you have teams at Google, like our Google research teams, that have been improving
09:18the state of flood forecasting, as an example, both providing more elite time and more granularity
09:25to give folks additional time to get out of harm's way.
09:27But then that now, when encapsulated and handed off and empowering nonprofits, to give them
09:34more time to do the stuff in advance of disaster that really helps save and protect lives and
09:39livelihoods.
09:40So just a smattering of examples across mitigation and adaptation.
09:44But so much more that we can say here.
09:45And Maggie, I know that you invest a lot in AWS in health equity.
09:52Can you provide some examples of using AI in this specific space or anything that you
09:56think is super exciting that you've already seen?
09:59Yeah.
10:00So AI is the most transformative technology of our generation.
10:05And what we're seeing in the social impact space is AI, and more so Gen AI, has the power
10:13to really fuel, empower nonprofits and social enterprises and the great work that they're doing.
10:20So in health equity, which you mentioned, Jacek, we have a health equity initiative
10:25at AWS that we're funding.
10:28It's a three-year commitment of $60 million, where we're funding solution development to
10:34help advance efforts to address inequities in health globally.
10:39And one of my favorite use cases is a small startup that's Seattle-based.
10:45It's Huron AI.
10:46But the bulk of their work addresses health inequities in sub-Saharan Africa.
10:54So they have a solution, Kazika, that they've developed.
11:00And it's being used in Rwanda, where there's more than 13.5 million residents.
11:06And with that, there's only 15.15 oncologists.
11:11So they've developed a solution, leveraging Amazon Bedrock, to connect cancer patients
11:18in a more timely fashion with oncologists to get more acute and accurate care.
11:23So it's pretty powerful to see how AI has really transformed that experience for a cancer
11:30patient.
11:31Yeah.
11:32Wonderful example.
11:33I think, especially in Africa, we've seen some panels today talking about the huge need
11:38that is there that could be very, very useful.
11:40Amy, what about education?
11:41I know that you're personally a huge fan of using AI in education.
11:46Have Salesforce pushed some of the work here in this space?
11:50Yeah.
11:51So we've done some work in education.
11:54We launched our first AI for Impact Accelerator last year, right as Chad's GPT was hitting
12:00its one million users mark.
12:03We recognized what a potential amplifier this work could be for those in the education economic
12:09opportunity sector, specifically nonprofits working to achieve those goals.
12:13And so really, I think we at Salesforce are looking at the combination of what does AI
12:19plus data plus CRM look like and how can an organization better connect with the constituents
12:24it serves through leveraging tools like AI to do, I think, two main things.
12:28So the first is augmenting their own human capacity.
12:31And the second is around building efficiencies as an organization who's often resource constrained
12:36and trying to do everything they can to serve the populations that they're working with.
12:41And so there's two examples I'd love to share.
12:43The first is this amazing organization, Teacher Development Trust.
12:47And they develop training modules for teachers, largely in the UK, to help them understand
12:53how to manage classrooms.
12:54And what's surprising is it actually can be pretty lonely to be a teacher.
12:59You're isolated in your classroom.
13:00The only adults.
13:02You don't often have somebody observing or providing any kind of feedback to you in real
13:06time.
13:07And so they are working with us to create a chat-based AI simulation tool where they
13:12can start to engage in these classroom dynamics.
13:14And it's grounded with all of the best pedagogy and resources.
13:19And they've worked with our team of researchers to help develop protocols to test the prompts
13:24that they're running through and make sure that it's coming back sound and accurate.
13:29And then always keeping a human in the loop.
13:31So a coach that's reviewing.
13:33Another great example is just simply an organization who is trying to get a bunch of due dates
13:40for important information around, like, financial aid for students across 4,000 different college
13:45websites and tailor that to the individual.
13:48And so they're looking to use AI to scrape that data and then write short form content
13:53that can reach these, they serve specifically first generation students more effectively
13:57in their work.
13:58So really exciting ways in both sort of augmenting human potential, but then also streamlining
14:02their work.
14:03Yeah.
14:04Some wonderful examples.
14:05I think so many educational organizations could also leverage this work to enable their
14:11own interventions.
14:12I know that Gates Foundation is really invested into education.
14:16Bill is talking a lot about how education is going to be disrupted by generative AI.
14:22But I also know that it's not the only field that you are engaged.
14:27And Jackie, can you tell us maybe a bit how Gates Foundation thinks about the big AI for
14:33good bets?
14:34Like, what are the fields that may be potentially most impactful and interesting from the philanthropic
14:40perspective?
14:41Yeah.
14:42Thank you.
14:43Like my fellow panelists have mentioned, health care is a big one.
14:47Education is a big one.
14:49But I think another sort of area that the foundation is focused on is actually agriculture.
14:56And one of my favorite use cases really is thinking about a company out in Tanzania where
15:05they're able to use basically generative AI and basically look at early detection of crop
15:16disease before it happens.
15:19And so you're talking about farmers out in rural areas where 50% of the cash in that
15:26area of the cash flow comes from crop, specifically maize.
15:30And so being able to utilize AI to look and say, OK, we can predict if this plant is about
15:36to go diseased or we can mitigate against some of that using some of that technology,
15:43you're saving livelihoods when you're doing that.
15:47And so I think agriculture is one of the big spaces that we're focused on and investing
15:49in as well.
15:50Great.
15:51My parents are farmers.
15:55So I think there are huge applications in Global South, but also like every other farmer
16:00could use this technology to really make sure that we can produce more food for people around
16:05the world.
16:06Marnie, you were a part of TechSoup, which is one of the most amazing tech for good organizations
16:11in the world, being present in, I think, all of the countries, almost all of the countries.
16:16You work with millions of nonprofits, helping them apply technology to their work.
16:22From your perspective, what could be the most transformative or interesting when it comes
16:26to the potential of AI in the social sector?
16:28Yeah, I think a couple of things that are the most interesting, like across the board
16:33for organizations, is the ability to use AI to identify specific communities that aren't
16:39thriving in the way that others are.
16:43So they can identify pockets of population, and with that, start to identify and target
16:50resources, either at the hyperlocal level, because just there's some reason that population
16:54isn't thriving, or to say, actually, this is an indicator of a systemic inequity.
17:01And so what do we do to go in and change the systemic part?
17:05But I think the ability, the AI, to pick that out of enormous data sets offers a lot
17:11of opportunity for small, individual organizations, but also people that are working in the space
17:16and have resources that they can bring to bear as well.
17:21That sounds very powerful.
17:24Okay, but we were speaking about organizations that are very progressive, and not the whole
17:31change-making space looks alike.
17:34So I'm curious how far we are from the wide adoption of AI and nonprofits.
17:42So let's talk a little bit about it.
17:43So my experience at Tech to the Rescue is that actually there are at least four different
17:47kinds of nonprofits.
17:48So first of all, there are innovators.
17:51So nonprofits who employ AI engineers who can really push the work forward, who are
17:58on the frontier of innovation.
18:00Then we have organizations who I call the nonprofit scale-ups, organizations that have
18:04already established some amount of operations.
18:07They could leverage AI technology to make big progress, but they may lack some of the
18:12resources.
18:14And maybe using some technology could help them to make big progress.
18:18Then we have established local organizations, so basically organizations present in one
18:22country that are doing their work and potentially could use off-the-shelf solutions.
18:28And probably the local organizations who maybe don't even need AI to do their work well.
18:35But all of you work with nonprofits.
18:37I'm curious, what are your lessons about the biggest challenges, the biggest blockers that
18:42organizations see, how we might empower organizations to really make bigger progress?
18:47And maybe we could start here again from Alex.
18:51Yeah, I mean, a couple things come to mind.
18:56First, I think we need to be careful to not be AI solutionists.
19:00I think oftentimes the first question that we ask nonprofits is, what problem are you
19:04trying to solve?
19:06And then from that problem set orientation, try to figure out what are the set of solutions,
19:11technological or not.
19:12And if they are technological solutions, if AI can play a critical role, then great, we'll
19:16pursue that path.
19:18But that's key.
19:19We can't be trying to use an AI hammer in search of a nail.
19:23It really needs to be tailored to specific problems where it can be helpful.
19:26And there are certain underlying features of certain domains that make an area high
19:30potential for AI, very data-rich environment, et cetera.
19:35So that's one.
19:37Our team just launched a large survey where we surveyed a broad group, I think several
19:44thousand folks that are in the Google for Nonprofits program, specifically on generative
19:48AI.
19:49And it's published.
19:50So if anyone that's interested, please search it on your favorite search engine.
19:55And what we found was four out of five nonprofits would say, hey, there's something about this.
20:00I've read it.
20:01I've seen it.
20:02Some demos.
20:03There's something here that is exciting.
20:04But over half of them quoted, I don't have the time, the awareness, the tooling, the
20:11funding to really make progress against this.
20:14So that's a call to all of us to meet these organizations where they are and provide the
20:19necessary training, the resources, the awareness and availability of these tools that can be
20:24off the shelf.
20:25And for those that are more technically savvy, you can customize.
20:27But there's a huge effort that we need to do to really make sure that we're bringing
20:31and lifting the tide of all boats, because AI has a really, really powerful capability
20:36to be a great leveler.
20:38But that's not going to happen by chance.
20:39It's going to really take all of us to do that together.
20:41Yeah.
20:42Jackie, I know that Gates Foundation in the last year, I think, made a $30 million investment
20:47into supporting a huge amount of organizations into piloting AI use.
20:52What are the learnings from this process?
20:53Like, can you tell if we learn something from that experience and we can use that experience
21:00to inform the broader interventions on the market?
21:03Yeah, I think one of the biggest learnings, and I think you were sort of somewhat alluding
21:09to it, is AI can absolutely be a great leveler, but it's really not that yet.
21:15One of the things we learned was that there are huge inequities when you're looking at
21:21even access to AI and AI solutions.
21:25So the $30 million fund you mentioned was actually provided for AI-based solutions in
21:30Africa, where there is sort of a bigger disparity between the global north and the global south
21:39in having access to AI-based solutions.
21:42It's interesting because you would think $30 million is a lot, but it really isn't when
21:47you're looking at...
21:48You're not only just trying to churn out quantities of solutions, what you're actually trying
21:52to do is seed and cultivate an environment that will create sustainability over time.
22:00So you want solutions that can last, and what you have to do there is also build out infrastructure
22:05that will last.
22:06You have to engage with policymakers to create policy that will help grow and cultivate.
22:10So I think those are some of the learnings where it's not enough to just sort of give
22:13the funds and provide the funding.
22:15There are a lot of underlying factors that are challenges in various regions that don't
22:21allow or don't sort of create the best environment for AI solutions.
22:26Yeah.
22:27Maggie, AWS works with both non-profits and for-profits, and we talk a lot about how non-profits
22:35seem to evolve to be ready for AI, but potentially every other organization in the world could
22:41have, right?
22:42And so I'm curious, what are your learnings?
22:44And do you think the non-profit market is in a different place than the for-profit market
22:50is?
22:51What are the differences and where are the gaps?
22:54Well, you see trends, whether it's non-profit or for-profit, and it just depends on where
23:00a customer is and their technical maturity model.
23:02But with non-profits, you tend to see there's less investment in technical expertise in-house.
23:10And so some of the gaps that you find are access to education and skilling and access
23:20to technical expertise.
23:21So that's why partnerships with other organizations and private sector, like those of us at the
23:27table here, are critically important because you can help teach them to fish, right?
23:33Through mentorship and through training programs that are offered at Amazon.
23:40We launched last year an Amazon AI Ready program that provides training about AI.
23:53Up to two million individuals are committed to training.
23:57Just to better understand from a baseline, from a responsibility standpoint, the importance
24:04of AI and acting responsibly.
24:06And then we have training certification programs as well about how to build and deploy sustainable
24:12solutions.
24:17So we spoke a little bit about the funding, the readiness, access to talent.
24:23Amy, I know that within the Salesforce Accelerator for non-profits, I think they have them all, right?
24:31What is happening when they have them all?
24:33Yeah.
24:34So, right, correct.
24:35For Inner AI from Back to Seller, we're providing product unrestricted grant funding and pro
24:41bono experts from Salesforce to surround these organizations and support them in both thinking
24:47strategically about their solutions, making sure that AI is the right fit for that problem
24:51that they're trying to solve, to your point earlier.
24:54All the way through to thinking about, you know, is their data clean enough?
24:58Is it organized enough?
24:59Do they have it stored in the right way to be able to access it?
25:02And those are really powerful sets of skills for organizations because, as others mentioned,
25:09you know, a lot of organizations don't have that talent in-house.
25:11It's really expensive to hire AI talent, especially in today's market when all of your major corporations
25:18are vying for that same talent, frankly.
25:21And so to be able to provide that support to help grow the capacity within an organization
25:28so that, sure, even if this project that they're working on that they've proposed fails, they
25:33still leave learning something new.
25:35And so we see our role intentionally as being risk tolerant.
25:41We want to provide the room and the flexibility for these organizations to grow, to try something,
25:45to experiment that they otherwise may not have been able to do for lack of resources,
25:50lack of capacity, whatever the reason is.
25:53But I will say I think the number one thing we've offered, and I've said this many times
25:57already, is the pro bono support.
25:59They come for the funding, they stay for the pro bono support.
26:02It's like very powerful what can happen when you partner all these different diverse perspectives
26:07together and skill sets that can unlock for the organization.
26:12Pro bono support, again, and access to talent, but mainly like that would be very difficult
26:17to provide pro bono services to one million organizations, right?
26:20So what are your learnings from the perspective of the ecosystem, right, working with millions
26:24of nonprofits?
26:25Yeah.
26:26I think that, you know, what we think about, so most of the organizations that we help
26:30in a given year have a budget of under one million U.S., no matter what country they're
26:36in.
26:37U.S., Germany, Kenya, Brazil.
26:39And obviously in some countries that top number is much lower, right, than one million.
26:44But they're small relative to their economies of the country that they're in.
26:49Their budget relative to their local economy for technology is less than a high-end laptop
26:54annually.
26:57And so, you know, when we think about their context, you know, the tools and expertise
27:03are often out of cost for them.
27:05They can't afford that staff person.
27:07They can't afford the monthly user license.
27:10So we're thinking more and more, how do you put together collectives of organizations
27:15so that you can meet their needs as a group and not just as an individual organization,
27:20right?
27:21What does it look like when you start building geographically bound communities of purpose
27:27that can share and benefit from some of these models?
27:30But there's a lot of nonprofit funding that make that hard.
27:33They're often competitive with those other organizations that would be in their community
27:37of purpose.
27:38Yeah.
27:39Yeah, but it sounds like we all need to do more to create this ecosystem that can support
27:46those organizations because the potential award is huge, right?
27:50So let's talk about what is the role of business.
27:53We are at Enterprise AI Conference.
27:56So starting with Maggie this time, what are the specific things that AWS commits to do
28:05to make sure that social impact organizations can leverage AI for the best?
28:11Yeah.
28:12So, well, what is the responsibility of business?
28:15I think that's what we're representing, the commitment that our companies have.
28:21But what AWS is doing specifically is we have many programs that nonprofits and social enterprises
28:28can tap into.
28:29One is our AWS nonprofit Imagine Grant program, which is access to unrestricted cash grants,
28:40marketing support, and then pathways to technical support as well through our Gen AI Innovation
28:47Center, which recently launched.
28:49And that's where we teach a nonprofit to fish.
28:53So hands-on skills development, where we have technical staff that are building a solution
29:01side by side with the nonprofit.
29:03So those are some of those that stand out.
29:05And then specific to health, we have our AWS Health Equity Initiative that really doubles
29:11down in addressing inequities in health through our technology, focusing primarily on Sub-Saharan
29:19Africa and Latin America, where we see some of the greatest need.
29:22Yeah.
29:24So education for most of the organizations, and then investing specifically with all the
29:28tools in some specific fields that are of the most interest.
29:31That's right.
29:32Amy, from your perspective and Accelerator, what do you think?
29:37What companies should do to really help the whole society leverage AI for the most?
29:43Yeah.
29:44So the way I think about it, we're lucky at Salesforce to have had philanthropy baked
29:49into our model from the start.
29:52So we've always viewed business as a platform for change.
29:55And we were founded with something we call the 1-1-1 model, which is about giving back
29:581% of our time, 1% of our product, and 1% of our equity back to the social sector.
30:06And so that has led to 56,000 nonprofits and schools using our technology either for free
30:13or for heavily discounted pricing, which is amazing.
30:16So I'm so glad that we were able to do that.
30:19And I think every company should find the way that feels like a good fit for them to
30:22what they can naturally build into their business that feels attainable.
30:26For AI specifically, I think there's a couple of areas that come to mind.
30:31So first, I think about trusted AI.
30:34We are thinking about, as a tech company, how do we build in responsibility and trust
30:39into the product?
30:40So we house a lot of organizations' data.
30:43We don't own that data.
30:44That is not our data.
30:45How can we be responsible stewards of that and help our customers, both for-profit and
30:51nonprofit customers, feel confident in their experience with that?
30:55And so that's been a really big topic of conversation for us in how we're thinking about deploying
31:01the technology and advising the nonprofits that we work with on how they should be thinking
31:05about building their own governance models internally.
31:10And then from, I think, from another important perspective is thinking about us being an
31:16active listener.
31:17Right?
31:18Like, we are hearing from our community, especially in the accelerator, you know, I heard this
31:21come up earlier in one of the talks, but the last thing anybody wants to do is do more
31:25harm.
31:26Like, especially nonprofits who are working with the most vulnerable populations.
31:29And so how can we listen to them, hear what they're saying, where their concerns are,
31:33and bring that back into the work that we're doing, especially as, you know, many people
31:37in this room are AI engineers and experts and technical experts, like, how do we really
31:41listen to the communities who are going to be using this technology and make sure we're
31:45hearing their voices and perspectives and bringing them back into our work?
31:50You mentioned access to data.
31:51I think we haven't really covered this, but all the research shows that nonprofits really
31:59struggle with the data, especially for the ML model training.
32:04And I know that Google is starting some of the investment in this field, which is pretty
32:08new.
32:09Alex, can you share more on that and how you think other tech companies could help the
32:14society to really leverage the data which is there, but not maybe easily available to
32:20nonprofits?
32:21Yeah.
32:22And I'd love to build on what Amy was saying.
32:23I think, like, in terms of the business responsibility, like, Google also has committed the 1% pledge
32:29and think about bringing our best assets, which are our people, right?
32:33We have a program called the Google.org Fellowship where we can second full teams of employees
32:37for up to six months full-time pro bono to build tools and products for nonprofit organizations,
32:43and then it's their IP, it's their product afterwards.
32:47I think to your point, Yasik, we try to take a holistic approach for our AI grantmaking.
32:53That starts with data.
32:55So we brought with other peer funders, like the McGovern Foundation and Rockefeller Foundation,
33:00and we cofounded this thing called the Lacuna Fund that is focused on funding locally led
33:06and managed data sets into existence on critical topics like climate and health and education,
33:13which we want to make sure to fill that representative and that fairness gap that exists in the ecosystem
33:17for some downstream models that can get built on top of them.
33:21But critically, I mean, just having access to data is insufficient.
33:26There's a team at Google that we work closely with called Data Commons that works to interoperate
33:31publicly available data sets so that you can now query across multiple data sets that might
33:36be in different formats, on different timelines, to really drive that insight, that novel insight
33:42that you're looking for that can really truncate the time from understanding data to insight
33:47to most importantly, action.
33:50And then now with the advancements in large language models, you can smack a natural language
33:54front end and you can literally just learn at the speed of your curiosity.
33:57I think trying to find ways to get this this tool to anyone that's out there, please look up
34:02Data Commons. We work with the U.N.
34:04Statistics Department on a data commons for the SDGs, Sustainable Development Goals, that can really
34:08help track and monitor progress against the SDGs.
34:11And then underpinning a lot of this, there's a huge need, to Amy's point, to really support the
34:17responsible ecosystem.
34:19So last November, we came together with other peer funders and other philanthropists to launch
34:24an inaugural AI safety fund to really start to to make sure that organizations have the
34:30resources that they need to fund model evaluation cards and bias busting efforts into
34:35existence, because that is critical to ensure that not just we're putting these powerful
34:40tools out there, but that they're safe and trusted by design.
34:44Thank you. Jackie, I know that Gates Foundation is perceived by many people as the world's
34:50largest philanthropic initiative, but I know that you collaborate with businesses as well.
34:54And that's happening for a reason.
34:57Can you share more? And from the perspective of such a philanthropist like Bill, why the
35:02role of companies is important?
35:04Yeah, no, I think Alex just touched on it here.
35:08When you're, you know, thinking about sort of building out more, thinking about, you know,
35:16the resources that need to go into it.
35:18Yes, the foundation is pretty big and gives pretty large sums of money out to, you know,
35:24invest large sums of money into, you know, funds for AI and other things.
35:29But you think about it, it's not enough, right?
35:31I think there absolutely has to be more.
35:34And this is why there has to be collaboration across businesses, other big foundations,
35:39smaller foundations, other top philanthropists, right, to collectively together continue to
35:45invest in products that, one, we need globally, right?
35:49Like whatever region or area you're working in, these are things that affect human beings
35:53and human lives.
35:55And so being able to fund that for just the greater development, I mean, you know, how
35:59can you argue with that?
36:02And, you know, going to my sort of little SDG Suresh feel, usually you think about,
36:08you know, SDG 17, right, which is collaboration and partnerships and achieving the goals.
36:12And I think one of the big ways that the foundation really truly does try to do this is through
36:16partnerships with other organizations, building out those, you know, funds.
36:21We understand business is a major leader, right?
36:25Everything can't come from philanthropy alone.
36:28Business has a part to play because they make profits, right?
36:31And so, you know, working with those organizations like these, you know, on the panel today
36:37is what will help us accelerate towards the progress we're looking for.
36:42Yeah.
36:43Marnie, you bring the business contribution to non-profits at scale.
36:50From this perspective, not only thinking about the big players like Google AWS or Salesforce,
36:55but from the perspective of the solution providers or another perspective, what do you think
37:01would be crucial for the business sector to offer to make sure that we can leverage the opportunity?
37:06I would love a chance for the small civil society organizations that we work with to
37:12have two things.
37:13One, to have facilitated ways to aggregate their use cases and put them in front of these companies.
37:21So your pro bono effort is meeting the need of a thousand organizations in ten different
37:26countries, you know, like that kind of work.
37:30And how do we do that and provide regular feedback?
37:33And then the second thing is to support these organizations, and maybe a lot of this is
37:38driven by more traditional philanthropy, actually.
37:42But also philanthropy that comes from corporations.
37:46But to drive data aggregation in common format so it can be investigated in things like data
37:51commons, which you were mentioning, right?
37:54Because you're all data aggregators when you get information back from the organizations
37:58that you supported about your projects.
38:01And so how do we make that data available is another way we see our communities the
38:05same way AI is looking at commerce data or health data or other metrics.
38:12Thank you.
38:13So to summarize, the opportunity is big, right?
38:16We can win a lot, but the needs are also huge.
38:20There's a big gap.
38:21We are only starting.
38:23There's a room for everyone to contribute.
38:26So we welcome you to join our movement.
38:29All of us are fully invested in making sure that AI can benefit nonprofits and people
38:34as much as possible.
38:36You can join us.
38:37If you have ideas, if you have ways to contribute, please reach out to any of us, and let's do
38:43more good for everyone.
38:45Thank you so much.
38:46Thank you, my dear panelists.
38:48And let's continue our work to make the world a better place.
38:53Thank you.
38:54Thank you.
38:55Thank you.
38:56Thank you.