Welcome to Digitally Curious, a podcast to help you navigate the future of AI and beyond. Your host is world-renowned futurist and author of Digitally Curious, Andrew Grill. Andrew's guests will help you become more curious about the latest tech and what's just around the corner.

Today's guest is Jacek Czajkowski, the co-founder and managing director of Tech to the Rescue, who's at the forefront of leveraging technology for social good. Jacek has dedicated his career to using technology to address some of the world's most pressing social and environmental challenges. At Tech to the Rescue, Jacek leads a global movement that connects tech companies with non-profits to solve real-world problems using advanced technologies, including AI. Today, we'll delve into how AI is being harnessed to drive social change, the challenges non-profits face in adopting new technologies, and the future of AI in the social sector. Welcome, Jacek. It's a pleasure to be here. For those who haven't heard about Tech to the Rescue, could you outline your mission and your journey to date?

Tech to the Rescue. Could you outline your mission and your journey to date? Tech to the Rescue was founded because there's one big problem in their world, which is non-profits. Globally, they lack technology resources to invest in scalable solutions that could make their work more accessible, more adopted and more impactful. So we work with non, with nonprofits, every single day.

We see that all around the world there are thousands of great social entrepreneurs who have tested proven social impact interventions. Basically, they know how to solve social problems. They work with beneficiaries hand in hand. Every single day they crack the code on how to change people's lives. But their impact is limited to working with the community or with a small region, because technology gives this opportunity to copy paste something that works everywhere.

Right, and without access to technology, they are limited in impact to small communities and because of that, the whole humanity and the civilization misses the chance to, you know, improve social problems here and now. The problem is big, yeah, because you know it exists in every single country and it's difficult to solve because technology is expensive today and it will be very, very difficult to bring additional billions of dollars into the non-profit market. So the solution that Tech2TheRescue founded and believes makes sense is a cultural solution. So basically, what we want to do is we want to make sure that every single tech company in the world will collaborate with non-profits on a pro bono basis, and we mean that every single company can afford sending at least one qualified professional team for a non-profit for two, three, maybe six months per year to build a technical solution that would help this non-profit scale up their work.

So we're going to talk about AI, which is now everywhere. So what do you see as the role of AI within nonprofits and social impact organizations?

Many nonprofits that we work with have some bottlenecks that are solvable with automation. So you know, if you run a nonprofit, your typical size is less than 50 people, you don't have hundreds of staff, you don't have automated facilities, have hundreds of staff, you don't have automated facilities and sometimes you are limited by simple things like okay, we don't have that many advisors or consultants to help every single person with problems to understand what to do next. And when we work with nonprofits, we see that they have limitations in their internal work, understood by how well do they organize processes? But also with external work, basically meaning that they are limited with serving many people because they lack staff. And AI, especially generative AI, brings these new capabilities to the market and we believe that almost every single nonprofit-profit that is bigger than you know, working with the community, could leverage those solutions to a rise.

More funds, because we could automate relationships with donors, and this is very important because funds are unlocking many different things. It's the same thing as sales in businesses. Second thing non-profits could make sure that their work is more efficient, right, and it's very important to offer the world with a high-performing solution which is cheap to deliver impact, right. So implementing AI-based solutions could reduce the cost of serving one person or one animal or one social problem and, of course, because we could automate the interface of interacting with the direct beneficiary. In the end we could make sure that one organization can serve much more people. So we believe a gigantic potential in almost every field of work within nonprofit. But there's one challenge, obviously, because AI is in a very early stage right now, that we need to be sure that we won't provide people with the wrong information or that algorithm won't provide misguiding hint to a beneficiary, because in some cases that could be very detrimental.

So it sounds like you've got a really important mission that you've got here. So tell me about how you set it up, what was the journey to say we need this, no one else is doing it in the way that we can do it, and how you actually then got this off the ground.

Tech to the Rescue. It's a movement story. So prior to launching Tech to the Rescue, I used to own my own digital company. It was basically a digital agency that was building software solutions for other non-profits with a very special twist because my company was focused on building gamified solutions. So basically, we were transforming boring life into interesting games that help people change habits and improve behaviors. The work was very impactful. Everyone who worked with us observed improvements in how people behave in their own lives.

But every single time we were approached by a client meaning a non-profit we saw a potential. But we also saw that they could afford hiring us for one month or two months, because bidding technology is very, very expensive, and how do you scale up such a company if your clients don't have budgets to actually afford any margin? Right, you cannot hire more people, you cannot invest. So you know, being in this type of company was very fulfilling in a social impact sense. It was very difficult in a business sense. So I was observing the situation. I saw clearly that so many great nonprofits lack resources and, on the other hand, I was a participant of the digital solutions market. I was hiring the same people as the commercial companies are hiring and so on. So I had this insight that when you run a digital services company, sometimes you have the situation where at least one of your teams is in between projects, right? So, for example, they finish some multi-year project with one big client and before the next client buys their services, they wait for two, three, sometimes four months until something new comes in. And these people are waiting. You won't fire them because it's too expensive to hire new staff. You want to have them available because sometimes clients need them right away and you know they're essentially you know getting bored, frustrated because they don't develop themselves as engineers. So I had this insight that most probably it is possible to encourage thousands of companies worldwide to dedicate these people waiting for the next project for a non-profit project, because that could be win-win-win for everyone and for a company. It's a way to utilize and mobilize staff for those people who are waiting for the next project, an opportunity to learn new skills, to do something very fulfilling and very purposeful and, for a non-profit, the only way sometimes to actually invest in technology and build something which is not doable using only the grant money, which is very little. So I had this idea in my drawer because I thought well, you know, building a movement of thousands of companies is not easy. Would I have to attend thousands of meetings to actually build this critical mass that needs to be there? But then something happened, something that everyone felt at one moment, and that thing was COVID. When that big crisis hit, like COVID, like war in Ukraine, everyone in the society is mobilized and people want to be useful, and people from the technology sector also want to be useful.

It was, I think, april 2020, when one of the tech entrepreneurs in Poland had this insight and he wanted to do something. So he published a LinkedIn post that, basically, he will donate his team to a non-profit that knows what to do to stop the pandemic. He didn't feel as an epidemic expert, he didn't know what to do, but if there is any nonprofit that has a good recipe for stopping this or for helping people, then take my people, use them for nine months and do whatever is needed. So he published this post. It got viral very quickly, so he saw that people are picking up the idea, so he included a very simple Google spreadsheet link in the comment and he wrote if you like the idea and he included a very simple Google spreadsheet link in the comment and he wrote if you like the idea and if you want to donate your tech company stuff, just sign up here. After the weekend there was like 35 companies signed up. So he felt like, wow, I didn't expect it, maybe there's something we should invest in. So he asked his team that he wanted to donate to the non-profit to actually promote the idea. So they built a website, they launched a product hand campaign, they did everything that startups do and after six weeks there were like 150 companies already.

So I was observing this and I was like, okay, this could be the movement I was hoping for. So I basically picked up the phone. I called the person. I offered him this insight. I told him, you know, like this initiative will die if we don't transform this into something bigger than the pandemic. Then we started working together. The first 10 sponsors from Central Europe joined us like in two weeks and then we started building this. Right now, the community is bigger than 1500 tech companies from over 60 countries and we see every single day that this idea, it makes sense. People in technology are creative, they want to do something impactful and in the regular business sometimes they don't have this opportunity. So if some wonderful nonprofit from other parts of the world is coming, they see those people, their motivation, they see how, every day, they are changing people's lives. They feel it. They just want to do something, they just want to join. This way it's scaling quickly and this way it brings impact every single day.

Yeah, just to sort of reflect on what you said, when I was at IBM and I was running a consulting practice, often people in other teams had people on the bench. People listening to this will be aware of that. They haven't got a project at the moment, they're in between projects. They're still keeping the bench warm. What a great idea to have people on the bench doing something for good. Tech for good. It's an amazing initiative. Covid has come and gone. We've now got this new amazing tool called AI. I mean, it's been around for 74 years, but I think now everyone's talking about it. So maybe you could talk about some examples of how AI has been used in projects facilitated by Tech to the Rescue.

Let me start with saying that Tech to the Rescue supports nonprofits working in any field. We are not limiting ourselves to climate or to health. We try to be helpful for everyone because we know that tech companies worldwide have different preferences and we just want to make sure that any company that comes to Tech to the Rescue, they will find the project they will love. But sometimes we launch campaigns, so bigger efforts to support organizations in a given field, and one example of such a campaign is the campaign that we launched last year with the support of AWS, where we wanted to move the needle of the air quality movement worldwide. So first we decided to prioritize two regions in the world, which is Southeast Asia and Sub-Saharan Africa, because the air quality problem is getting worse and worse in those areas and there are not many non-profits that are working on this. And then we scouted excellent non-profits in almost all of the countries in those regions and then we basically asked those organizations what kind of technology do you need to make your work more impactful? And I will tell you about three examples of solutions that we built, I think, in quite interesting cases. So first organization is called Sensors Africa. The organization's mission is to make sure that the data about air pollution in whole Africa is publicly available so that people could raise their awareness and they could design better public policies, knowing what actually the problem is, right. So they are building the global network of air quality sensors, but those sensors are usually low-cost sensors and they sometimes break. So what organization asked us to do is to create AI-based solution that will simulate the air quality sensor in a situation where it has a downtime right. So when it breaks, it's broken for one or two weeks and we miss the data. So we built a machine learning algorithm that is estimating what would be the air quality level in a specific area if the sensor was working. So this is one of the cases.

Second case, a very interesting one, comes from Thailand. So there's an organization called Clean Air Thailand and they designed a new air quality bill that they want to take into the parliament, but to be able to do it, they need to collect 100,000 signatures from the citizens, and it's not easy because the bill is quite complicated and people don't understand what it means for them, especially that air quality problem is not very popular in Thailand. So what they did is they built a generative AI-based solution that is translating the bill to any person. That is speaking to the bot, right? So let's assume you are a farmer, andrew, and you want to understand, okay? So, if the bill is passed, how this impacts my life, is my work more difficult? Is it easier, what it means, what it means for my children, for my family, for my farm. So, basically, they built a simple solution that is explaining the impact of the bill and helps collect new signatures, which I believe is a very interesting way to explain politics and explain the impact of different policies on everyday lives.

And the third solution, also from the political field, was built for an organization from Indonesia. It's called Bikara Udara and they wanted to like in a specific year. Last year they had parliament elections, so they wanted to help citizens elect people who care about their quality. So they built a solution that was scraping internet looking for any statements that parliament candidates are making about their quality, and they built a tool that lets people find the candidates that really care and choose the best candidates of the candidates that are available in a specific region you are voting.

So it's interesting, right? Because we have one problem. We have different kind of layers of it, right from data collection to, let's say designing the public policy and making sure that people understand, to making sure that the right people are elected to be able to actually pass the bill right, and it goes on and on. In every other social problem area. We could use this methodology for health, for climate, for education. The possibilities are basically limitless. But the difficult thing is how to make sure that this technology is predictably impactful in a positive way and how do we avoid potential harms that could come, for example, from hallucinations.

So you mentioned you work with AWS. I understand you're also doing work with Googleorg.

Tech to the Rescue started as a bottom-up movement of tech companies in Poland, but we very quickly grew to the global movement of anyone from two people WordPress agency working in India to the global giants working in the technology field. So Tech to the Rescue right now is working very closely with Googleorg and AWS. They are our main supporters and recently, together, we launched a whole new big program for AI. It's called AI for Changemakers, through which, together with them, we are supporting 100 awesome nonprofits with implementing AI in a way which is impactful and both which reduces risks of doing harm.

Importantly, you want to get the right people into the right projects. So how do you identify and select the nonprofits and tech companies that participate in your projects?

That's a difficult task and it's called matching, and sometimes we tell people that don't really understand how Tech to the Rescue works. We call ourselves a Tinder for tech companies and non-profits. So, starting from non-profits, I think it's important to find a nonprofit that is actually capable of using technology. If you run a tech company and you wanted to help someone right away, your immediate instinct would be to help orphanage which is somewhere around, right, like in your neighborhood. But does the orphanage really need technology? What do they need? A new website? A new CRM? Like? Most likely, they have different needs, right? So it's very important to be able to find a non-profit that is in the stage of development, where the intervention is scalable and they just need to implement this solution to be able to increase the impact. Right? So, every single day, our staff is scouting the world looking for great organizations in all continents, organizations that have proven social impact, that have scalable interventions, that could use the technology and that has some level of investment in technology to make sure that any technology built by tech company will be then maintained and further developed. Right, because technology is not only about building the first iteration and vpr prototype. It's about constantly, it's about constant innovation. So we try to select organizations that are ready, that know what they want and that are capable of working with global tech companies.

From the tech perspective, it's a little bit more difficult because, first of all, we need to understand what the company specializes in. You will want to engage in a different project if you run a React native company and a different project if you run a generative AI company. We need to understand what the company actually cares about, because some people will be motivated by helping people with cancer and some other people will be motivated by solving climate change right. So we ask company you know what kind of social problems really motivate them to work? And also we need to understand what is the context of a tech company.

You mentioned Bench. Bench is one of them. We actually mapped 12 different use cases for tech companies to do pro bono work, and all those use cases come with different pros and cons. For example, bench is great because you have a fully professional team available, but for the limited time, right. So you need to adjust the scope of the project to the time availability of the team, and then we take all those factors into one algorithm that is recommending projects to tech companies, which is also supported by the work of beautiful human beings called matching managers, who recommend nonprofits to tech companies and who later facilitate the conversation, because, guess what? Tech companies are not perfectly prepared to work with nonprofits, and vice versa. Right, we need to translate the language of technology to nonprofits, language of nonprofits to technologists, and we need to make sure that the deal is well scoped out and everyone knows what they are getting into.

So, just coming back to AI for a moment, some of the challenges that are there. You mentioned Tinder as a dating app. I'm sure all the dating companies are very keen to understand that they do some level of screening to make sure that real people being matched to genuine human beings. So how do you ensure the AI solutions that are developed as part of these programs are ethical and don't inadvertently cause harm?

It's the most important thing in our work, and I mentioned the AI for Tradersmakers program. The program is divided into five thematic cohorts and we are working with a disaster management cohort right now. So, in essence, we are working with humanitarian organizations In the humanitarian world. There is this very important rule, which is an overarching rule of the humanitarian work. There is this very important rule which is an overarching rule of the humanitarian work, which is do no harm. And if you visited us in any of the meetings that we have within the program, you would quickly understand that there is no better industry in the world that is managing risks than humanitarian sector, because every single bad decision could lead to doing harm and they are really conscious about it. And so we ensure that this conversation about the responsible ai is present at every stage of the project. We talk about it when we talk about what ai is right, just to make sure that people understand its limitation. It's not a magic wand that is doing stuff. It's technology, algorithms that have its own profile and characteristics we need to understand. Then, when we talk about the use cases that organizations have, we talk about you know, do we need a human person in the process to make sure that it's making good decisions. Is this specific use case life-threatening or life-saving? You know what are the risks, to identify where the AI could be applied for with a risk that is manageable.

And then every project can count on the advice of the world's greatest companies and their responsible AI teams.

So, for example, every project that we do is going through Google's committee of AI principles team, which is rating the project under every principle, and they suggest what are the specific risks we should take care of specifically. But this is a theory. And then we have practice. We need to deploy the model and we need to test it right, and then I believe that the work is getting more and more difficult. So, in this specific case, it's very important to make sure that nonprofits have resources and capabilities to really deploy models in a testing environment, and this is something that we put a lot of attention to, and our program is not a program in which we mobilize everyone to make success. It's the program that we encourage everyone to experiment, learn and share the learnings. So every nonprofit-profit that will implement AI solution will be encouraged to organize testing environment, to test with real people on a limited scale and then publish the results, improve and then only launch on production to everyone who wants to use this solution.

So measuring success and the performance of the projects is obviously very key. So how do you do that and how are you able to maintain the quality and standard across all the projects?

The measurement is tricky because the whole measurement thing in non-profits is way more difficult than in business. In business the performance of a company usually boils down to profit or the revenue in some cases. In non-profits the success will be defined differently for every other non-profit working in different area, in different intervention and so on. So we try to find the common denominator for organizations and in our case it's one of the three aspects. First one is how many people or how many beneficiaries the organization can serve, so basically how widely they adopt their services and how many people or living beings are impacted by them. Second thing is the unit cost of making one unit of impact, so basically how expensive it is to change people's lives. And third, one is time to make an impact, so how quickly organizations are able to deliver their services.

And we measure those three metrics when organizations join Tech2DeRescue and we measure those three metrics after two years from the implementation of technology to see what's the impact. We want to see the positive change in at least one of those three factors. But obviously, if you ask me about this in a storytelling way, I would tell you that we are working with a nonprofit from Nicaragua which is providing sexual health education to women and before working with Tech to the Rescue, they were driving the bus around the country and providing direct education to women in rural areas and they were able to serve 20,000 people in three years and after they built an app with Tech to the Rescue, they served 50,000 women in one year. So this is the impact that we want to see.

So I could ask this question to corporates or nonprofits, but what are some of the most common misconceptions about using AI in the nonprofit sector?

I see less misconceptions about AI in nonprofits than in business. I believe that the reason is that in business, people are more oriented towards building processes and towards building scalable systems. In nonprofits, people are more focused on working with real human beings and helping them, and I think that those negative stories about using AI in some specific context, the stories that went wrong, are more adopted or more picked up in a nonprofit space, where people are afraid of doing some mistake. So we don't see people being crazily optimistic about AI. We see people being responsibly optimistic about AI and also having many concerns about the long-term viability of those solutions, how expensive they will be because they operate on limited budgets, and the very specific challenges that we see in many cases are making sure that the systems, especially the generative AI systems, will maintain quality, especially if they use models that are built by black box tech companies without much description or a benchmark test that they can trust. Second thing is we see that many non-profits, especially those bigger ones, they work with people in different nations or languages and the big question mark is, for example, how well different foundational models cope with less popular languages. It's not something you can easily test using some online tool, so many organizations are considering fine-tuning models to less popular languages. And I think, last but not least, there's a big question about the cost.

Some tech companies are very generous and they provide credits for the solutions. So, for example, aws invested 6 million dollars of AI credits for our AI4Chainmakers program. But obviously credits are available for a specific time and after 24 months you need to start paying right. So we need to be really aware of the cost of the solution, about the unit cost of maintaining the solution for many people, and so far, comparison of different Gen AI models, especially when it comes to the costs, are tricky. It's not easy, it's not very intuitive. You need to talk to the expert to really understand. Actually, you need to test it in real life to be sure what the real costs are. So there are many questions, but I wouldn't be afraid of people not asking difficult questions when they implement projects. More I will be afraid of the tech market being more transparent and more user-friendly when it comes to helping people understand how expensive it will be to use their products.

So final question before we go to the quickfire round, let's look to the future. What are the future plans for Tech to the Rescue and how do you see the organization growing in the next decade, and how can we bridge the gap between big tech and nonprofits?

Yeah. So first of all, I want to see every bench in the world being utilized for a nonprofit project. I don't care if it's a bench of IBM, if it's a bench of IBM if it's a bunch of small Polish or Indian software development company. I want to see that people that work in tech companies, when they see unutilized resources, they have an idea of working with a nonprofit. And this will take time. We believe that this could take us like five to 10 years.

There are multiple dimensions of the work that we need to do. We need to make sure that doing pro bono will be easy, that it will be manageable for companies and that companies will be able to measure the performance of those processes. But also we need to make sure that it will be present in the mass media culture. Why? Because look at the legal market. In the legal market, doing pro bono is a standard. Everyone knows that it's something that companies do, and they know it because some of the very, very popular pieces of culture promote this. So there's this famous tv show about lawyers the Suits, and in the Suits one of the, mike, is doing pro bono case in every season of the series, and then hundreds of millions of people are watching the series and they see that this is what legal companies do.

So one of our dreams and informal goals that we have is to revive the Silicon Valley series one day and to make the whole season of the series about the guys building technology for a non-profit. So this is the ambition. There are metrics. So we hope to facilitate services tech services of a value of $1 billion until 2030. And we hope to collaborate with both big tech companies and large tech companies like IBM, aws and Googleorg. But we also hope to work with the whole market of tech companies that employ more than 10 people and are able to donate some weeks or some months to build something interesting and impactful for a nonprofit and impactful for a nonprofit, having run six startups.

Watching the Silicon Valley show about startups and Pied Piper going from working around the kitchen table to a huge conglomerate was fascinating. Not sure you'd want the Silicon Valley team helping nonprofits. I think there might be some dysfunctional behavior there, but that's for another time. We're almost out of time. We're now to my favorite part of the show, the quickfire round, where we can learn more about our guests, so I'm going to fire some questions at you. Window or aisle, aisle. I'm tall. I need space for my legs. Iphone or Android?

Android, your biggest hope for this year and next We'll be able to ship at least five amazing AI projects for nonprofits in the community. I wish that AI could do all of my B boring communication. The app you use most on your phone, it's Whoop. It's the fitness app that helps me sleep better, train better and become healthy.

The best advice you've ever received.

It's actually a piece of entrepreneurial advice. So I was a participant of the mentoring program with one very esteemed manager and I asked him you know what, in your opinion, is a key characteristic of a very good leader? And he told me there are two things. First of all, 95% of your work is an excellent communication. Second thing 5% is an ability to spot the opportunities and to use them.

What are you reading at the moment?

I'm actually reading a book on startup boards because at nonprofits one of the most important aspects of running the organization is having an excellent board that helps organization grow.

One thing I've been pushing for a long time about boards is having someone that's digitally curious on the board, or more than one. They actually understand the technology, so that is a key thing for both corporate and not-for-profit boards. Who should I invite next onto the podcast?

key thing for both corporate and not-for-profit boards. Who should I invite next onto the podcast? I would recommend inviting the founder of an organization called Humane Technology. It's Tristan Harris. He used to work at Google. He's the person who is behind the famous Netflix show, which is the Social Dilemma, and I believe that he could bring lots of interesting insights into this whole AI craze. He's the person to bring more awareness on how we should deploy this technology responsibly.

Great suggestion. The social dilemma is a few years old now, but I remember encouraging my friends to watch that to see how social media has really developed. I think we could probably update that for AI, so I will reach out to him. Final quick fire question how do you want to be remembered?

I want to be remembered as a person who spent his life on unlocking potential of a wonderful human being that cares about other people.

As the actionable futurist, I always ask my guests for three actionable things they can do. So what three things can our audience do this week to better understand how AI can be used for good?

First of all, check Tech2TheRescue out. Tech2therescueorg is our website and you can join the community and volunteer your company to work with non-profits. I believe that any company in the world has those opportunities, like Bench, to engage in non-profit projects, and sometimes it's as easy as one person in the company signing the company up, and then our team will help you discover how to crack the code of doing pro bono at your company. Second thing, following an impactful person who is the Amazon CTO, werner.

Vogels, I know Werner. I've been on stage with him in Abu Dhabi. I know him and we're in contact. Yeah, he's a great guy.

He's a great guy and he spends lots of his time on finding people who care and who build very impactful solutions. Also, werner recently announced that he will join our AI for Changemakers program and he will offer his personal time to spend with nonprofits advising them on how to become better CTOs and how to push the innovation agenda harder and more effectively. And third thing is, I think, following our social media tech to the rescue, because we recently launched our own podcast where we speak with social impact innovators. We publish lots of blog posts and insights into how to work with AI when you are a non-profit, so I think it's a pretty good source of information on understanding how to build impactful AI solutions.

Jacek, a fantastic discussion about tech for good, doing some real good. How can we find out more about you and your work?

Tech2TheRescueorg is our website. I'm most active on LinkedIn. Thank you so much for your time today. Thank you, Andrew.

Thank you for listening to Digitally Curious. You can find all of our previous shows at digitallycuriousai. Andrew's new book, digitally Curious your simple guide to navigating the future of AI and beyond, is available to pre-order at digitallycuriousai. You can find out more about Andrew and how he helps corporates become more digitally curious with keynote speeches and C-suite workshops at digitallycuriousai you.