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#GivingTuesday Data Collaborative

Virtual Roundtables

Lucy Bernholz, Asha Curran, and Josh Levy discuss the challenges of building a governance plan and digital infrastructure for giving data worldwide

#GivingTuesday Data Collaborative

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You’ve probably heard about #GivingTuesday, the thriving global movement launched in 2012 that mobilizes resources, unmeasurable acts of kindness, and hundreds of millions in charitable donations in the United States alone. The distributed nature of #GivingTuesday is the biggest factor driving its growth, in that anyone can participate. Nonprofits can design their own campaigns, experiment with branding and messaging, and use the donation portal of their choice.

What happens to the data collected by hundreds of #GivingTuesday giving platforms, payment processors, social media companies, and nonprofits around the world? How can these diverse data sources come together to yield a rich, detailed picture of giving trends? Can this type of global, cross-sector data sharing be done safely and securely?

To answer these questions, the movement’s leaders launched the #GivingTuesday Data Collaborative, an ambitious cross-sectoral project that yields actionable insights and data-driven fundraising tools for the social sector while protecting data privacy and security.


The way people engage with giving has evolved and will continue to do so: Asha Curran says, “The way people express their generosity in this age is fundamentally different, not just from a generation ago but even from five, ten, two years ago. It’s changing all the time.”

Widespread and decentralized, giving data can tell a powerful story: Curran, who hadn’t realized there wasn’t a centralized repository for giving data, “slowly started learning how data in the sector really works and how very, very difficult it was for me to even cobble together anything resembling a comprehensive aggregate number of dollars.” Forming relationships with giving platforms and payment processors uncovered  “a massive world” that offered a unique and comprehensive look at data in the sector.

Most organizations overlook the security and privacy component completely: Josh Levy suggests always looking at philanthropic data projects through a security and privacy lens, and investigating products carefully before implementing them. “It’s definitely worth the investment if you care about protecting the privacy and security of your users and walking the walk when it comes to these issues.”

Collaboration is in critical condition; data philanthropy can help: Pooling data for the common benefit is something everyone in the social sector can benefit from. Nonprofits can learn from private sector partnerships, where pooling data for analysis and sharing it back increases the bottom line for everyone involved. Curran Says “there’s far too little collaboration in a sector that is supposed to exist for so many good social purposes,” adding that “what the data collaborative is becoming for the sector is something that most for-profit industries have had for decades.”

Innovating data isn’t about “moving fast and breaking things,” it’s about claiming your place as a leader: Levy encourages organizations to “lead publicly” by putting data governance models in motion at the start of their projects, adding that nonprofits are innovative when they handle data governance “from the ground up, rather than creating loads of data, then having to figure out what to do with it.”

Audio Podcast and Transcript



Watch the video or listen below, and visit our podcast on iTunes. Follow us on Twitter @dgtlimpact for updates. This transcript has not been edited for clarity.

00:12 LUCY BERNHOLZ: Welcome and thanks for joining today’s Digital Impact Virtual Roundtable on GivingTuesday’s Data Collaborative. I’m Lucy Bernholz, director of the Digital Civil Society Lab at the Stanford Center on Philanthropy and Civil Society.

The Digital Impact Virtual Roundtable series highlights issues related to digital data and civil society. These conversations are part of a larger of activities that digital impact and the Digital Civil Society Lab undertake to bring people together who are thinking about and who are making happen digital civil society around the globe. We invite you to learn more about the initiatives and opportunities available through digital impact, the Digital Civil Society Lab and Stanford PACS. Our primary goal here at Digital Impact is to advance the safe, ethical and effective use of digital data in civil society.

Today, we’re going to be talking about what goes into building a secure digital infrastructure and robust governance plan for global giving initiatives. Now you’ve probably heard about GivingTuesday. It’s a global movement launched in 2012 that mobilizes resources, acts of kindness and hundreds of millions in charitable donations in the US alone. The distributed nature of GivingTuesday Movement is the biggest factor driving its growth. And anyone can participate from anywhere. Nonprofits can design their own campaigns, experiment with branding and messaging and use the donation portal of their choice. But what happens to the data collected by the hundreds of GivingTuesday giving platforms, the payment processors, social media companies and the nonprofits all around the world? How do these diverse data sources come together to yield a rich, detailed picture of giving trends? And can this type of global cross sector data sharing be done safely and securely. These are big questions that lots of organizations and efforts are trying to answer, and we’re going to be talking specifically about this one related to GivingTuesday.

The Movement’s leaders launched the GivingTuesday data collaborative, an ambitious cross-sectoral project that yields actionable insights and data-driven fundraising tools for the social sector while protecting data privacy and security. Over the next hour, our panel will discuss how this ambitious new project plans to account for data privacy and security just as the next phase of collaboration between data partners around the world begins to take shape.

“What the data collaborative is becoming for the sector is something that most for-profit industries have had for decades.”

Before we start the discussion, just a few housekeeping details. Everyone but the panelists is going to be muted for the length of the discussion. So your microphones are on mute. We do want hear your questions and insights, however, so please use the comment function on your control panel to submit questions, and I’ll pass them on to the panelists. Today’s discussion will be recorded and shared on the Digital Impact podcast, which you can find on iTunes and at You can join the discussion on social media with the hashtag GT data and hashtag giving Tuesday, and subscribe to our mailing list for updates. Remember, these conversations are always driven by you, the members of the community. If you have a topic you’d like to explore, please share it with us by emailing us at Now, let me introduce the panelists.

I’m very pleased to introduce Josh Levy who is the founder of the Digital Security Exchange and cofounder of the Center for Digital Resilience. Hi Josh. And Asha Curran who is the chief innovation officer at 92nd Street Y. Hi Asha. Thanks to both of you for joining us today. Let’s get started.

04:05 LUCY BERNHOLZ: Question number one, Asha, I’m going to start with you. And I’m going to quote you back to yourself. In a recent interview with Global Giving, you described generosity as a universal human value, adding, and I quote, Giving Tuesday is an adaptable movement that was created to be changed and evolved and used by people and organizations and countries in whatever way is relevant to them. It doesn’t have to be a one-size-fits-all movement, end quote. Well that approach has certainly paid off, both in terms of mobilizing funds and obtain insights through the process and data collection. You started the Giving Tuesday data collaborative as a way to make sense of how much money was being donated on the actual day itself, which I should mention is coming up very soon. And its purpose has evolved into something much bigger.

So here’s the question. Why does the social sector need a collaborative like this? What can the data that you’re collecting tell us about human behaviors around giving? And a second part of the question, how is the new initiative designed to help nonprofits particularly make better use of the data that’s being collected.

05:20 ASHA CURRAN: As you mentioned, the data collaborative started with a much, much simpler idea which was just to try to understand how much money was being donated just in the US on GivingTuesday. Just as I am really a neophyte to the data space, I was also a neophyte to the giving space in general and the social sector. And so I just didn’t realize that there wasn’t sort of one central repository where all this information was held. And I kind of figured I could just dial them up and say how much money was given yesterday, and they would just hand me a number and that would be five minutes of my day. And obviously, I slowly started learning how the data in the sector really works and how very, very difficult it was for me to even cobble together anything resembling a comprehensive aggregate number of dollars. So what we started to do was to, we actually took this idea from one of the first GivingTuesday campaigns in Baltimore to try and understand how much money was being donated in Baltimore, they essentially had a bank of volunteers just calling up nonprofits and giving platforms and then adding the number together. And I thought, well, if they did that in Baltimore, we can do something similar on a sort of nationwide basis.

“The way that they express their generosity in this age…is fundamentally different, not just from a generation ago but even from five, ten, two years ago. It’s changing all the time.”

And so we started forming relationships with the different giving platforms and payment processes of whom there are like 150, 200, it’s a massive world. And then just getting the numbers from those 24 hours only online, that’s all we could measure, and then adding them up. Once we had those relationships that we were starting to build and we had the data coming in, we sort of slowly realized, and this was all part of my journey that I’m like 10% along on and trying to become much more fluent in data myself as somebody who’s senior in the sector. It’s kind of shameful how little I knew, how very, the most basic level I started from. So we slowly started realizing how much richness there was in this data, how much it had to tell us. And particularly now that everything is changing with regard to giving. We’re at a moment where we’re examining everything we think we know about what drives generosity, about what the levers are, about what the impacts are. But most of all, just about the way that people engage with giving. About the way that they express their generosity in this age, which is fundamentally different, not just from a generation ago but even from five, ten, two years ago. It’s changing all the time. And so this data that we have, which is from multiple platforms, so from all different kinds of places within the social sector. It ends up being quite comprehensive.

Woodrow Rosenbaum who is our data lead for GivingTuesday points out that for the, what the data collaborative is becoming for the sector is something that most for profit industries have had for decades, right. They’ve realized that pooling their data for the common benefit does involve some risk, right. Other people might make money as well, but everybody’s going to do better with that data analyzed. And so, my favorite example is that there is a, very similar to our data collaborative, an association for the galvanized steel dipping spoon industry. So all the makers of the galvanized steel dipping spoons pool their data, and then it gets analyzed, and then they turn it back to all of the manufacturers, and they all make more money. And so like, you know, they’re making galvanized steel dipping spoons, and we are trying to make the world a better place, and we’re not pooling our data for the common benefit of all the people who are doing that work. And so that’s, I think, what we can find out is things that everybody in the sector stands to benefit from.

And then I also think that the collaboration piece itself is really crucial. I think there’s far too little collaboration in a sector that is supposed to exist for so many good social purposes. And so even getting all of these different players to really work together and essentially actually practice data philanthropy. None of them are under any obligation to give us this data. I think is kind of a really important piece of it as well. So I think there’s a lot that we can do and a lot that we can figure out. But along the journey, sort of all of these questions about security and governance come up, and we have to answer those as well.

09:53 LUCY BERNHOLZ: Right, thanks Asha. I mean it seems at the very least we should be able to repeat what the dipping spoon industry is doing. Maybe not. Maybe, but anyway it’s a good metaphor. So let me just get Josh in the equation here. You founded the Digital Security Exchange in 2016, so just a few years ago. You try to strengthen the digital resilience of US civil society groups by improving their understanding and mitigation of online threats. You work through the Center for Digital Resilience which you cofounded. And the exchange then draws on a network of tech experts who work with nonprofits and other civil society organizations, not only in the US but around the globe.

“There’s still a role for advocacy and public messaging when it comes to…security and privacy, not just in the policy realm but also in the realm of technology and consumer-basing products.”

Now, you’ve teamed up with GivingTuesday to find ways to make the giving data more collaborative and secure across the board. So that’s where you fit into this conversation. Here’s another two-part question. First, why don’t more projects make data privacy and security a priority from the start? I mean, it seems like we’re kind of past the moment when we can sort of not think about these claims. So what is it that’s holding organizations back? And second, some examples of successful projects, social sector projects, that might serve as guides or inspiration for others, for those folks on the phone.

11:11 JOSH LEVY: Sure, thanks Lucy. Hi everybody. So, first off, why don’t more organizations or projects or collaboratives do this, incorporate security privacy into their work? It seems obvious to a lot of us who work in the sector. But it’s not an obvious step for, I would say, the majority of folks who are embarking on projects like that still. So there’s still a role for advocacy and public messaging when it comes to the importance of security and privacy, not just in the policy realm but also in the realm of technology and consumer-basing products and also products like the one that we’re building where there’s an easy way to do it, or easier way to do it that disregards or doesn’t take security or privacy into account. And then there’s a slightly harder but in the end a much more valuable way to do it that starts, that looks at this project as a security and privacy project, in addition to being a philanthropic data project. And that’s the way that we’ve taken, that’s the approach that we have taken on this.

And so, this actually goes into answering the second question which is what kinds of projects have done as well? I’m going to offer a kind of surprising answer I think, which is we’re using Amazon’s infrastructure, AWS infrastructure, to build a lot of this, the project out. And there’s different places where different pieces of the data gets stored depending on what’s being done to the data. And we’re actually modeling this on the way that much larger projects are created and maintained. For example, the US Department of Defense uses Amazon’s web structure, AWS structure for similar kinds of projects, right. Big corporate projects are using Amazon’s infrastructure.

Now, I know Amazon is this big behemoth that’s actually in the news a lot today, and there are other questions around the use of infrastructure like this. But what it does offer is security and privacy out of the box if you want it. And so we’re actually looking to these more corporate types of projects or government-funded projects that have compliance to deal with and that much incorporate security and privacy because they’re dealing with state secrets or they’re dealing with corporate secrets as models. There’s no reason why we shouldn’t treat the data of donors with just as much sensitivity as we would treat the data of governments or big corporate actors.

So, there’s a way to do this and actually products like Amazon web services offer a pathway to making your web projects really, really secure and offering different levels of user authentication at every step of the process so that only the people you want to access the data can. But you have to spend time investigating what those solutions are. You have to work with people who are knowledgeable about building those kinds of databases and those kinds of network infrastructures that we’re building. And so it can be more complicated, but it’s definitely worth the investment if you care about protecting the privacy and security of your users and walking the walk when it comes to these issues.

14:22 LUCY BERNHOLZ: Thanks, Josh. And we’re going to come back to this I’m sure. I’ve got lots of questions about this because, you know, there’s at least two sides, two strands of thinking that have to go into to trying to build a secure privacy protecting system. One is the actual technological infrastructure, which you’ve emphasized. There’s a massive global scale one or a few already built that many different kinds of players use so that this is not about investing necessarily in your own technology but investing them in the governance and decision making processes by which the vested interest in the data that you’re talking about are going to know who has access, who gets those different kinds of authentications, what’s it going to be used for. That’s the human side of privacy and security, which I know is a big part of this project as well.

“We’re too busy to become fluent in this new language that might be really intimidating, but it’s crucial for us to be able to speak about [it] with knowledge and intelligence.”

And let me take that question then back to Asha, who I know has been known to describe just good old collaboration, whether or not it’s about data but just actually working across organizations as a muscle that nonprofits need to experiment with. One argument that GivingTuesday’s skeptics often proffer is that nonprofits, especially the small ones, and it’s important to point that out because when Josh refers to donors, we’re not talking necessarily or only here about big wealthy people. We’re talking about you and me. We’re talking about all the people around the world who power GivingTuesday with very small gifts. They do deserve the same kind of privacy and security as anybody else. But the skepticism that comes through is that the nonprofits that work with these communities can spare the time or the staff to run the kind of campaigns that really make GivingTuesday, you know, as mediagenic as it’s become. They just have to do the regular work.

So, Asha, tell us a little bit more about what you mean particularly when you refer to collaboration as a muscle. And why the stress on experimentation in this work that you’re doing? When GivingTuesday tries to promote the widespread adoption of something like crowdfunding, what do you say to the small and midsize nonprofits who say we just can’t add that into the list of things we have to do today.

16:47 ASHA CURRAN: So I think that kind of skepticism is scarcity mindset, finding yet another voice in the sector. It’s just like saying, you know, we are too busy chasing after our next dollar, so we can’t think about leadership. We’re too busy chasing after our next dollar so we can’t think about governance. We’re too busy chasing down our next dollar, so we can’t think about innovation, about experimentation, about collaboration. And I would actually say that it’s not just a great thing for nonprofits to be able to do it, or data, for that matter, right. We’re too busy to become fluent in this new language that might be really intimidating, but it’s also of crucial importance for us to be able to speak about with knowledge and with intelligence. I think it’s absolutely urgent that nonprofits do that. That they learn to experiment, that they learn to collaborate. Not only is it much more fun, but it is really the only way that we can ensure vibrancy and sustainability in the sector.

And when I, one thing that I’ve learned from traveling around the world and visiting all of our different GivingTuesday country leaders is that they’re to the last one, really worried about the pipeline of leadership in this space. That, you know, we need to be attracting the very best and brightest people into this world. But we pay too little and don’t innovate enough, and it just does not always seem like the sexiest way to go. The small and midsize nonprofits in my experience do a fantastic job with innovating and with experimenting because they’re not burdened by the kind of bureaucracy and sort of top-heavy weight that much bigger nonprofits are. So certainly, we see some big nonprofits doing amazing things. I would say, in particular, the United Way has come sort of about full circle, but it’s been quite a journey in working with them. And we’re seeing some incredible leadership from some United Way chapters. But on the whole, it’s small nonprofits with small operating budgets who manage to do incredible things.

“Each datapoint in this data mountain is an indicator of a personal transaction, an action by a person on behalf of some interest.”

And very little of GivingTuesday’s success is driven by big marketing budgets. Nobody takes out big ads, and if they do, it’s usually given to them pro bono. It’s not that sort of thing. It’s not a celebrity marketing-driven sort of movement. Very much driven by the grassroots, and it really shows the fact that this is, we’re not living in an age where a respected philanthropic body or the president or, you know, a celebrity is going to tell people what to do and they’ll automatically activate in droves. Things work much more laterally now, right. It’s your peer network. It’s your social network that’s going to influence you much more. You know, the main lever of giving is because a friend or a respected person in your network asks you to. So those, the way that that power is working differently now means that nonprofits with much smaller budgets actually have an incredible opportunity.

19:44 LUCY BERNHOLZ: So we’ve got a lot on the table already. We’ve got collaboration. We’ve got the size of nonprofits. We’ve got lateral relationships. We’ve got peer-to-peer. We’ve got collaboration. We’ve got all kinds of things. Let’s go back to data for a second. We’re talking about a lot of it. That’s got to be obvious. What might not be clear to everybody listening in in the conversation is that the data that’s generated when somebody makes a gift, an online gift, an SMS gift, a click the button kind of gift, is that it sticks around after you’re done with the transaction. All of that transactional data sticks around somewhere.

One metaphor comparison that we’ll use here just to help people connect with this idea is that it’s a little bit like Styrofoam. You use the cup. You’re done with it, but the Styrofoam can be around for an awful long time, as we know. It doesn’t evaporate. And just like that Styrofoam, leaving data by the wayside is both bad for the environment. And it, in the digital data world, the equivalent of that metaphor holds in that you’ve got this big pile, many piles of Styrofoam, that can be breached. That people can get access to. That information can get out where it’s not meant to be or be seen by those who are not meant to see it. And given the kind of data that nonprofits in general collect on people, losing control of it could cause real harm to real people. It can also bring some serious legal consequences from the nonprofit, reputational damage for the organization, the kinds of things that could actually sink a small or a big organization.

Josh, starting with you, how do you process all of this information, all of this data, in a way that is both aligned with the horizontal nature of GivingTuesday, the distributed decentralized global nature of it? But then build in that respect for the people who are making those transactions. Because we have to, I mean each datapoint in this data mountain is an indicator of a personal transaction, an action by a person on behalf of some interest. So how do you marry those two things? How do you really create? Is it possible to create to just kill this metaphor I’m in the process of killing here, a biodegradable system or a more Earth-protecting system, human protecting system of digital data on the scale that GivingTuesday is already working?

22:36 JOSH LEVY: That’s a great question. I think that the easiest response is, you know, we’ve made this system out of corn husks, which is biodegradable. That’s my joke for the day. I hope you appreciate that. So basically, all of these issues, Lucy, that you just raised were at the top of mind when we started collaborating with GivingTuesday on this project. Specifically, thinking about protecting the rights and the behaviors of small donors, small-scale donors, to thousands and thousands of organizations and campaigns around the world. And so we built in a number of safeguards to help protect that data from getting exposed and being used in the wrong ways. I mean, and so the number one thing is the vendors that we collaborate with are required to scrub the data that they submit to this collaborate project, as much as possible from the start so that from the beginning, the data that we are receiving doesn’t contain any personally identifiable information. So while we can’t 100% ensure that that is the case, that is the requirement. So I think that weeds out a lot of problems from the start. And we have a very strict policy about that.

Number two, as referenced before, there are a number of containers that the data goes through on its way to being seen and analyzed. And at every step of the way, it has an opportunity to be scrubbed and for us to ensure that nothing compromising exists in those datasets. And so the first process actually is a process of normalization. Taking all of that data from different vendors that looks different depending on who’s giving it to us, and making it all look the same, standardizing it. And when you do that, if there’s any piece of data that shouldn’t be there, it kind of gets discarded, right.

“We built in a number of safeguards to help protect that data from getting exposed and being used in the wrong ways.”

And then finally, after the data has been used and analyzed, if we don’t need it anymore, it’s actually hard to truly delete information. You know, as we know, you can always recover it from a hard drive even if it has been quote/unquote deleted, but part of our process is to truly delete forever the data that’s been submitted once it’s not useful anymore. And again, that kind of process is kind of simple in the same way that building security and privacy is kind of simple if you do it from the start, but you have to be intentional about it, and it has to be part of your grander strategy for the product that you’re building. So this is, right? So in the same way that Snapchat pretends to kind of be private and things disappear. But hey, you know, your messages are still living on a server somewhere after you think they’ve been deleted. We don’t want that possibility to exist, so we built in this true delete policy that will exist once the product is out a while.

25:33 LUCY BERNHOLZ: And I want to ask the same question then of you, Asha, but I want to point out that those steps that you just described, Josh, because I’m about to use a phrase that I think some folks find, I think is critical, and it’s also an off-putting phrase, and that’s the governance word, the data governance word. It’s a lot of syllables for decisions that actually are really the kinds, some of the kinds of decisions that you just referred to, Josh. Those were choices that were made about which information to request from the vendors, in what format, what to keep, what to not ask for, what to literally not collect. Because you don’t, can’t guarantee that you can protect it. So don’t collect it in the first place. Those kinds of decisions, that’s what data governance is. It’s that chain of thinking about this resource that you have an end goal for that you’re going to use. You have to come up with beg, borrow, steal, clutch together a set of, a process for how you’re going to do it.

“We are all building GivingTuesday as it goes. Like a Minecraft world.”

So, when you’re working on that side of it, Asha, where the technology choices are going to be advised by an expert with that set of goals, you’re thinking about the values that you want reflected in these decisions. How are you going about that, given the nature of GivingTuesday and its distributed scale and the mix of players, which you mentioned at the beginning but I’ll just reiterate for folks. You’re talking about hundreds of competing companies. Actually, the giving platforms are commercial, many of them, enterprises that are each trying to compete for that business for providing that service. I don’t even know countless nonprofit and other kinds of organizations. In all kinds of countries, speaking all kinds of languages and all kinds of regulatory systems. So, there’s the Thanksgiving table that people are coming around. And you’re trying to lead a process of saying okay, how are we going to use this digital resource to do what we want to do in a way that protects the people who actually conducted these transactions? How are you going about that?

28:00 ASHA CURRAN: So, the focus of my fellowship at PACS at the Digital Civil Society Lab was really this exact question. I actually really like the word governance, because I think that like the word infrastructure, it’s something that we are in a really exciting moment that we can sort of fundamentally reimagine what the definition of that word is, just like the word infrastructure. But I was also, you know, very aware of everything I didn’t know and aware that there are many things that I didn’t know that I didn’t know. And true for all of us on the team, because we are all building GivingTuesday as it goes, right. Like a Minecraft world. So, I think, you know, we, one really foundational sort of conversation I had at Stanford was with a woman who’s very experienced working with administrative data research facilities. My advice for the data world would be to think of sexier names for these kinds of things. But the administrative data research facility is very much along the lines of what we were already thinking that we wanted to put together. And so realizing that that model existed was really great, because I could ask tons of questions about how those manifest. And those are facilities that collaboratively host data from transactions and public records and not just academic research. And they can be used and accessed by all kinds of people for all kinds of purposes. And they have to answer lots of governance and security questions as well. So that was really, really helpful to our own work.

You notice we don’t call it the GivingTuesday administrative data research facility. That would be very off-brand. But it’s the same kind of idea, including the fact that there’s really limitless possibilities, right. So, we right now are hosting data from 60-plus payment processors both for and nonprofit as you mentioned. But we foresee a future where we’re incorporating all kinds of other data there and trying to learn things like once someone is expressing generosity, are they more likely to be civically engaged in other areas? And you can imagine all kinds of other datasets being folded in to answer questions like that. Questions about movement learning that might inform other more nascent movements around other social justice issues, etcetera. So I think the answer to the governance question where we are now is it’s a process of co-creation, just like GivingTuesday is a process of co-creation.

“The portal itself, the infrastructure itself, is meant to be used and accessed by all of these different partners.”

And it’s a process where we’ve built in all kinds of checks and balances for ourselves, right. So we work with Josh, and he helps keep us real in a security way. We have a data advisory panel, which you know very well because you’re on it. And we work with very, very closely in collaboration with this group of platforms who we really view as co-creating this whole process with us. And that will be true of all of the data partners that we fold in. So that doesn’t mean there’s no decision making from our team or no leadership. But we certainly don’t think that creating this in a vacuum without all of the advice from people who are very smart in this space and all that collaboration and co-creation would not be productive at all and wouldn’t be in the GivingTuesday spirit.

31:09 LUCY BERNHOLZ: Thanks, Asha. Josh wanted to actually add something into that last question, so Josh.

31:20 JOSH LEVY: Yeah, I just wanted to mention innovation came up earlier, and when you’re talking about data governance and innovation, you know, there’s an idea about innovation that it’s about moving fast and breaking things, right, the Facebook model. And I actually think there’s another way to be innovative as a small organization or a medium-sized organization, and that’s to think about data in a way that we’re talking about it. And to think about data governance from the ground up rather than creating loads of data and then having to figure out what to do with it when it becomes the Styrofoam that’s polluting the environment. It’s actually a very innovative and forward thing to do to come up with a data governance model from the beginning of a new project. And to be able to lead publicly with that and show others the way. And I think that that incident we have an opportunity to do that, but a lot of others have the opportunity to do that too.

32:10 LUCY BERNHOLZ: Yeah, and I want to, yeah, thank you for that, Josh. I couldn’t agree more. And we’re starting to get some questions in from the audience. I’ll remind people that they can submit those questions, and we’re going to start folding them in right here, because this is meant to be your conversation. So let me turn to the audience now. There’s a question here about will the data be used only by the GivingTuesday team, or is the end intent, even if we don’t start there, for this data actually be accessed by any charity? Will the charities be able to easily use the database to create reports? And the if so, I guess, or maybe it’s parallel, are there any plans to help train or support organizations engaged in GivingTuesday and actually doing that? Let me just leave the rest of the words on the page there. So what’s the arc of who gets to access this now and over time? And I’ll go to Asha first and then to Josh.

33:11 ASHA CURRAN: So I think the idea right now is that in a safe and secure way, the idea is that we are creating these systems and processes and methodologies to be shared in an open-source environment and that it be with the goal of fostering more innovation and more data fluency. We don’t want to use this data to create top heavy white papers that live on a website that nobody ever reads. They’re meant to be accessible and actionable insights that everyone from the smallest nonprofit to the largest one can use in a way that will actually benefit their work and that the portal itself, the infrastructure itself, is meant to be used and accessed by all of these different partners. Again, not without any sort of tiers of access or credentialing and so forth, because we have to be safe.

34:09 LUCY BERNHOLZ: Josh, is there anything that you want to add to that?

34:12 JOSH LEVY: I mean I can’t speak to the content of the project in the same way that Asha can, but I can say that I think the structure of what we’re building, which we’re doing from the ground up, we’re not taking another preconceived or prebuilt system. That structure I would be very happy to make publicly available to folks. We have [inaudible] network maps and other pieces of documentation that I think should be made publicly available, and I would love to share with others and engage in any kind of collaboration with them if they’re considering a similar project.

34:51 LUCY BERNHOLZ: So just to be clear on that, Josh, you’re actually talking about the work that you’ve done to design the systems and the thinking, both the technological infrastructure and governance infrastructure for using the shared data resource – you’re willing to make available to other social sector networks who might be thinking about doing this in a different set of data. Is that what I just heard you say?

35:14 JOSH LEVY: Absolutely. And you know, what you might call the blueprints of the system, right. There’s nothing proprietary about those blueprints, and there shouldn’t be.

35:24 LUCY BERNHOLZ: Right, fantastic. That’s a wonderful offer. Let me go back to the audience questions, because there’s lots of curiosity here about how might the insights from this data set be used? So the long-term aspiration you’re described, GivingTuesday itself is coming up in about less than two weeks now I guess. What might folks see differently, or is there anything that you’ll be able to be doing differently in early December 2018 that organizations that [inaudible] are well into making Giving Tuesday plans should be thinking about now?

36:12 ASHA CURRAN: Yeah, and I would say the things that we’re learning from the data that we’ll continue to learn much, much more about are things that organizations can be thinking about, even if they never engage with GivingTuesday, right? So they are not things that with GivingTuesday lessons. They’re just good lessons in general. And when I talked about [inaudible] I always kind of makes sure to kind of qualify that I’m not selling the idea of GivingTuesday, but I think that the lessons we can learn from it are applicable all the time. So for example, there’s a lot of worry, a lot of fretting in the sector, about what we’ve been thinking of as, and even the name of it is tremendously bias as replacement behaviors. So our new ways of giving, of expressing generosity, replacing traditional giving to nonprofits, and is that going to be detrimental to civil society in general because the funds are being directed elsewhere. And our data shows that’s not the case at all, you know, that something should actually be extremely intuitive to us is true, which is that generous people are generous. And if they give to, you know, if I’m giving to Josh’s neighbor’s dog’s surgery, it doesn’t actually make me less likely to then give to a nonprofit that I care about. So I think that, you know, we tend to worry about something as a way of not forcing ourselves to reckon with how to leverage it better. And I think that the fact that there are so many channels of expressing generosity now is actually a really interesting thing. I don’t want to say positive or negative, but it’s there. And we might as well kind of confront it and come to terms with it and understand that it’s not about people not wanting to give. It’s about how we engage them and inspire them to do that. So I think that that’s a scary thing for many, but I think it’s a tremendous opportunity.

“We’re not going to be able to as nonprofits build relationships with people often in the same old way.”

There’s also, I think, a longstanding belief in the sector that people get tired of giving. And again, that’s, you know, according to all of our data, that is just not the case. Generous people do give over and over again, whether they’re giving to crowdfunding. Whether they’ve given to seven different natural disasters. They’re still going to give again if they have that capacity. And I think there’s some really interesting rethinking that we have to do about, to use a kind of industry buzzword about things like donor stewardship, right. So we’re not going to be able to as nonprofits build relationships with people often in the same old way. Because we’re just not going to be able to collect the same kind of data on them. And often, the truth is they don’t want to hear from us again. So the most powerful lever of giving, right is peer-to-peer, right. Josh asks me to give, I’m going to give, because I know Josh, and I like him, and I trust whoever he’s asking me to give to. If that is like 30 or 40 percentage points higher as a mechanism of giving as a driver of giving, then I’m going to give to Josh’s neighbor’s dog or whatever it is, but I don’t want to hear from him, right. I don’t want to be stewarded as a lifelong giver to that dog. I did it as a one-time thing. So I think, again, like it’s not good or bad. It just is. Things are changing, and we have to do the best we can with it.

39:24 LUCY BERNHOLZ: I’m actually going to just push back a little bit on this, Asha, because I’ve been trained as an [inaudible]. So I don’t think the multiplicity of generous acts, I don’t think there’s anything [inaudible]. I think we’ve always behaved that way. We haven’t always done crowdfunding because crowdfunding hasn’t always existed. But when my neighbor needed help, I always helped my neighbor. But I handed her a dollar bill, or I went to religious services, and I handed them cash. And what has happened is we have an extraordinary new level of visibility into the multiplicity of behaviors that humans, that make us human and the ways we act. And the, you talked about kind of the, well you don’t like the phrase replacement behavior, which is, you know, a sociological term. But part of, another way to flip what’s happening here is to realize that in the, and this is a US perspective, because the US does have a fairly robust system of tracking charitable giving to 501(c)(3) nonprofits. That was one of many behaviors that existed 75 years ago when that system was created, 60 years ago. And that’s the one the laws were passed and the regulations were put in, and the money was invested in making that particular set of actions visible.

It doesn’t mean the other actions didn’t exit. It just means we weren’t actually looking for them. And now in the age that you’re doing this work with the data collaborative, a lot of those different kinds of actions have been shifted to digital platforms, so they can be more visible. And that’s what we’re doing is we’re kind of looking not just under the streetlight anymore, we’re looking on the whole sidewalk to see how, now I’ve mixed up all kinds of metaphors. I think that’s really important for folks to understand in terms of the diversity of platforms, for example, that you’re trying to work with and the sort of evening out of the judgment about what counts as generosity and what doesn’t is just acknowledging that we’ve always behaved this way. And now we’re trying to look at, we’re trying to see all the things that we might be able to see as opposed to concentrate on one.

I also want to point out something in what you’re doing and the way you’re doing it is not just about, this goes to some of the questions that have come in from the audience, this isn’t being built as a resource for GivingTuesday. It’s being built as a, to go back to one of your preferred words, a new kind of infrastructure about generous behaviors. And turning, it’s like turning on the lights in all those other rooms as opposed having operated in one room that had a light on it, and the light was shining on charitable giving to 501(c)(3) nonprofits. We’ve turned on the rest of the lights at the house. As I look, they’re doing all these other things. Which, again, to our topic here of security and governance, doesn’t make your life any easier. But in terms of what’s trying to be created here as a resource to be learned from makes it relevant to a far broader group of people.

42:51 ASHA CURRAN: Yeah, I think it’s meant to be a resource for the generosity economy writ large and even I would say for anybody interested in civic engagement writ large and generosity is often really undervalued as a metric of civic engagement. Like voting kind of gets all the attention in that regard. But a generous community, whether that’s a very small generous community or a human community is a healthier or more resilient one. I also, I think you made a really important point, Lucy, in terms of when you were giving a dollar to your neighbor or these acts that went less noticed because everything wasn’t on social media or online, no one would have considered you a less generous person, right. You would be considered generous by all of those measures. And if you wanted to then give $100 to UNICEF or whatever, you would have done that. Giving the dollar to your neighbor wouldn’t have prevented you from doing that, and no one would have assumed that. But people are fundamentally thinking about things in a different way when everything is happening online.

“They’re accessing a scrubbed kind of containerized version of it that is a version of the raw dataset…the version that’s been made publicly accessible.”

But because of the shift that you mentioned, the fact that so much of that was hidden before, and now it’s visible and it’s shared and it’s multiplied. That is not, that has actually affected a massive shift in behavioral norms, right. So my [inaudible] believed that the most noble form of giving was that which was anonymous, right, for which no credit was taken, no announcement was made, no sharing was done. And I wonder if my [inaudible] would feel like that is the most noble form of giving now when we know how powerful it is to spread a message of generosity among your peer network. So if I give money to a breast cancer charity, and I know that I can raise more money for that nonprofit by sharing it with my network, then don’t I almost have a moral obligation to do that if I really support that cause. So that’s like, the shift in mindsets and behaviors around giving our massive, and I think that’s what we have the opportunity to study and to study it across languages and cultures and borders where generosity is sometimes expressed in ways that would seem incredibly familiar to us and sometimes not.

44:54 LUCY BERNHOLZ: Right, which is, right, and I think we’re hinting at a next virtual roundtable about the changing nature of what we actually include in our definitions of generosity and the very rapid interactions between human behavior and new technological expressions of those behaviors. Let me take you back to the audience. There’s a very specific question back up at the top about, and I know you’ve just returned from South Africa and Kenya and probably other places in Africa, but what are you learning in a context like Nigeria, and how is GivingTuesday interacting with folks far from the shores of New York City?

45:41 ASHA CURRAN: I mean, it’s just amazing. It’s really, really amazing. It manages, because GivingTuesday is, you know, not branded and is meant to be co-owned and meant to be adapted and meant to be changed, it managed to attain, I’m sorry, to retain this incredible feeling of sort of collective movement like we’re all in this together. We’re all doing the same thing. We’re all driving toward a common goal, which is a more generous human society. And yet, GivingTuesday in each of these places really reflects the local identity and feeling of those different places. So in, I was not in Nigeria. But GivingTuesday in Eastern Africa, so it’s the fourth year of GivingTuesday in Kenya, Rwanda, Uganda, and Tanzania. And you know, there are certain challenges that are very specific to those areas. Tax policy, you know, history of individual giving. History of philanthropy, funding for generosity projects, things like CSR and all those things that are very, very specific to place. But things like lack of collaboration, lack of innovation, worries about leadership pipeline, scarcity mindset versus abundance mindset. Like those are common to every single place that I visit. So, you know, in Eastern Africa, generosity has its own kind of regional challenges and its own very, very universal challenges. And that’s where we can all help each other. If we’re all sharing that information as one big peer learning ecosystem, we’re going to be able to learn a tremendous amount from each other. But also, to implement these new best practices in real time. So we’ve been traveling around the world setting up data chapters partly to kind of steward those different leaders through the process of doing the data collaborative that we’re doing here. But also to learn from them. Because there’s places where, you know, the kind of data world, data fluency in the sector is miles behind us and places where they’re miles ahead.

47:40 LUCY BERNHOLZ: Yeah, yeah, great. Another question that’s come in, and Josh this is to you as well is, I mean especially given that diversity of participating and perspectives and real world wisdom. As you’ve been doing this, and you’re talking to all kinds of self-proclaimed experts or documented experts, are you, what’s not holding true. What are you learning that’s particularly surprising or contradicts received wisdom about how to go about something like this? And anything that comes to mind in that category.

48:21 JOSH LEVY: I feel like this is a bit of a broken record response. But there, I think is a typical knee-jerk reaction regarding larger projects like this one that it’s impossible to truly encrypt the data that you’re interacting with for example, right? And it’s actually not true. It is very tricky if you’re trying to build a real time analysis engine, for example, where you’re typing in search terms and then you’re receiving results based on those search terms. It’s pretty tricky to make that data end-to-end encrypted. But what we have done through this container system that I described before is to encrypt data every time it’s at rest, every time it’s traveling and every time it’s moving from one container to the other. And we’ve crated the snapshot systems so that when somebody actually is asking for data using a series of search terms for example, they’re not accessing the actual pot of data that we’re collecting. They’re accessing a scrubbed kind of containerized version of it that is a version of the raw dataset. But it’s the version that’s been made publicly accessible. So we basically introduced these firewalls so that it’s pretty much impossible to get at the raw data itself, meaning that it’s harder to get at any inadvertent leaking of personally identifiable information. But also, it allows us to keep the large datasets encrypted at every step of the way so that they can’t be inadvertently accessed.

50:13 LUCY BERNHOLZ: Great, thanks for sharing that. Asha, what about you? Anything less technical perhaps or just, human behavior-related that surprised you where you thought, everybody told me it would work this way, but it doesn’t seem to be working that way. I mean you mentioned —

50:38 ASHA CURRAN: Oh, I feel that way about almost everything people told me. I mean, really, really, I am in a full mode of slaying sacred cows. Because it just seems like so much of what we have assumed to be true for a long time just isn’t anymore. And again, like I just really see that as a hugely fun opportunity for us, and I think we should be less wringing of hands and more figuring out how to really just give ourselves a quantum leap forward using all this new information and these new possibilities. One mistake that I made, this isn’t regarding the data piece so much, so I might not even mention it, but at one point, my strategy with GivingTuesday, particularly with its global growth was to sort of find the right people to lead GivingTuesday and do the work in all these different places. And I realized that we, as a team collectively, realized that it works much better when people step forward because they really get it. Because they really believe in it. Because they really think there’s a lot to learn and there’s a lot of possibility. And I think that’s been true with the people who’ve stepped forward and engaged in these acts of data, philanthropy and data collaboration with us as well. You can’t, you just can’t go out and manufacture that stuff.

51:54 LUCY BERNHOLZ: Interesting, great. So this will be my last question to you both before we try to wrap up at the hour. And it’s a big question. It’s a take a step back question. I actually really like the house metaphor I just came up about we’ve been shining a light on one type of behavior, and now we’ve turned on the lights on the rest of the house. It’s also true, and this speaks a little bit to something you mentioned earlier, Asha, that you did reach out to the folks working on these administrative data research facilities to think about what might be there. And my point is this, these kinds of data collaboratives or social sector efforts where there’s a digitized data resource, essentially at the center around which behavior is coalescing, people are collecting it and thinking about its possibilities, are by no means unique to this example. This is an example of a much larger phenomenon that in some ways we’ve been talking about it coming for at least a decade. So, and it’s here now. I’m thinking about the opportunity atlas which is a dataset about a very carefully curated dataset of mobility analysis of economic data collected by the economist Raj Chetty that shows that, you know, in the US children born, you know, on the other side of the street have had significantly fewer opportunities over their lifetime than children in another zip code. And they can parse that information a thousand ways from Sunday, and it’s already influenced last time I looked, publicly announced influence of tens of millions of dollars in philanthropy that have said aha, here’s this common dataset. We’re going to start working off of it.

Another example would be, again a US-based example, and I encourage people on the call to share non-US examples with me. The eviction lab dataset carefully curated academic resource informed the book Evicted now being shared publicly housing advocates who’ve also been collecting data. Look at this data. They can assess their own strategies against that system. They can try to improve the data that’s [inaudible]. In other words, digitized datasets are becoming a possible shared resource for a whole new kind of philanthropy or philanthropy at a different scale and new kinds of activism. The other big example is the social science one example which has been created just this year to take Facebook data about behaviors that might have implications for election research and create a set of containers by which social scientists will be able to use that research.

Here’s my question, long-winded intro. Those are new topographical features on the map of the social sector. These digitized data pools, whatever you want to call them, whether it’s a trust or a resource facility or social science dot one. Chances are for the folks on this phone call, there is something like that being built with data about the issue that they work on that’s now in their space, if you will. So what does it mean for all of us as we think about that kind of new, no unnecessarily centralized facility, but a new resource that is on the landscape. This isn’t future, this is present, these data orgs popping up if you’re working on housing issues or health issues or education or dogs or whatever it is, there’s, chances are, there’s a new third-party dataset out there that people are using to make decisions. How should nonprofits be thinking about that? Last question. Sorry for the long lead up to that. Either one of you has a thought on that.

56:00 ASHA CURRAN: Josh, why don’t you take that first.

56:05 JOSH LEVY: Why don’t we create a shared resource? That’s always where my brain goes, Lucy, so I really like that you ask that question. And you know, we actually spend a lot of time in this sector talking about like open-source, which I think is a very broad term and it’s a term that gets contested, and it’s a terms that I think people have different meanings for. But if you think about the, an open-source ethic that I’m familiar with within the digital security and human rights and technology world where there is currently a lot of work being done to collaborate on documentation of human rights digital security trainers. What are some standards that we use to assess the needs of an organization? What are the steps that we take to implement certain kinds of practices? How do we train people according to a certain kind of shared methodology, this kind of thing? And it’s all done using open source technology, things like GitHub or GitLab.

And I hate to take these responses of mine always back to technological solutions because I don’t believe that these are technological solutions. But I think that there are certain structures in place that help us collaborate. And in the case of the technology in digital security human rights world, people are collaborating around how do we build a global community of practice when it comes to aiding human rights defenders, right. And I think that there’s a way to have a global community of practice around these kinds of projects as well that actually use some technologies that are freely available to us to document the way that we’re building projects.

For example, what I was talking about earlier in the car or in the conversation about providing a blue print of how to build a certain system. Let’s make that publicly available and let’s actually provide some benefits for other people to make their own methods and their own strategies publicly available so that they can freely take from others, right, and collaborate with them and also fork projects and make them into their own. I think there’s a lot of work that can be done to do that. Is that going to be a centralized repository, or is that going to be a centralized project with a proper name? I don’t know, but I think that there’s a set of practices that we can all engage in a lot more than we are now.

58:33 LUCY BERNHOLZ: Great, thanks, Josh. And since we’re up against the time limit, I’m just going to ask Asha that we will make all of these notes are available. People are asking how to get in touch with you, Josh, to get a hold of that blueprint. That’ll be attached to the transcript and to the recording of this. I think we touched on most of the questions. If you do have some questions that you feel weren’t addressed by the panelists, please take a look at the transcript and the podcast, which will be available very shortly. Usually, just a day or so, and we’ll try to get some answers up there.

So, with respect for everybody’s time, I want to wrap us up for the day. Thank you to both Josh and Asha for all of your work on GivingTuesday and on this new data collaborative.

We’ll have a full list of all of the resources that have been mentioned throughout the conversation. If you want to learn more about Josh’s work at the Center for Digital Resilience and how it connects organizations and digital security experts, you can check out to see how the digital security exchange strengthens the digital resilience of US Civil Society groups as a For a closer look at how the 92nd Street Y inspires action by bringing together exceptional thinkers and influencers for social good visit And to learn how you can join more than 100 GivingTuesday community coalitions in 150 countries for the global day of giving, visit

Please be sure to stop by Digital Impact for tips on how to advance the safe, ethical and effective use of data. Thanks again. I’m Lucy Bernholz of the Digital Civil Society Lab at Stanford PACS, and thanks for joining us. Goodbye everybody.