SPEAKER_00 0:12

You're listening to the Philanthropisms podcast with Rodri Davis.

SPEAKER_01 0:37

Hello, you're listening to the Philanthropisms Podcast. This is the podcast where we try to put philanthropy in context. I'm your host, Rodery Davis, and this week we are in conversation with Anne May Chang. Now Anne May is the chief executive of Candid, the US nonprofit uh data organization that provides basically the most comprehensive data source about the social sector certainly uh in the US. Um and I sat down with Anne May a few weeks ago now to talk um all things nonprofit data uh and to find out a bit more about candid's work. Um so yeah, we talked about uh what candid is and what it does and the data that they collect, kind of how they decide uh what to collect, how that goes above and beyond the data that nonprofits already provide to the tax authority, to the IRS, and how they make sure that the process benefits the nonprofits that are providing the data rather than just being another burden for them. Um linking to that, we talked about how nonprofits and funders and others use the data that Candid uh provides and what sort of uh decisions that they are able to make off the back of that. Um we talked about how uh Candid um sees its role in kind of modelling more ethical and transparent approaches to data collection and use and sort of what role the nonprofit sector more broadly um can play in that. We talked about the specific challenges at the moment around federal funding cuts and the role that Candid had played in kind of tracking where some of those cuts had hit the hardest and trying to allow organizations to sort of navigate some of those uh changes and to sort of find ways of pivoting. Um we talked about whether you know data collection is just a kind of neutral objective activity or whether it could have uh more of a proactive aim of trying to make giving and funding more equitable um and more effective, uh, and kind of what that might look like. Um we talked also about the relationship between data and transparency and public trust and how collecting data and publishing data in the way that Candid uh does can help the non-profit sector and philanthropy more broadly to become uh more accountable um and to ensure that you know the seemingly declining levels of public trust are slowed down and and hopefully uh reversed in future. Um we also talked about how Candid uh addresses issues of uh kind of diversity through data and whether actually you need to sort of take a proactive approach to overcoming the fact that data obviously uh contains historical biases and that if you want to uh represent uh fully the kind of diversity of societies that it is now, you have to take a more active stance on doing that. Um we also talked about how Candid is using artificial intelligence uh in its operations to improve its own processes uh and also kind of how it makes decisions in various interesting ways. And then we also talked about the challenges more broadly of kind of leading an organization through disruption. Um obviously the pandemic is not that far behind us, and since then there's been a lot of political upheaval. And I talked to Anne May about how uh Candid had been able to uh adapt and remain flexible and sort of ride out some of those challenges. Okay, well, without further ado, let's uh get into the conversation. I will be back at the end uh for the usual bit of housekeeping, but enjoy the conversation with Anne May. Okay, great. Well, I'm here with Anne May Chang. Hi there, Anne May.

SPEAKER_02 4:23

Hi, Rodri. Thanks for having me on your show.

SPEAKER_01 4:26

Oh no, it's great to have you. Um, and yes, everybody uh who's listened to the intro will know you are the CEO of Candid, uh the nonprofit um data organization in the US. Love to get into lots of issues around the work that you guys do, uh, the role that you play within the nonprofit ecosystem in the US, and lots of the kind of issues around data, and particularly uh how that relates to the kind of emergence of new technologies and new capabilities at the moment. But maybe the best place to start for people listening is for you to just tell us a bit about what Candid actually is as an organization, how it came about, and what you guys do.

SPEAKER_02 4:58

Thank you. Um, Candid is a nonprofit in the United States. Uh, we're a data and tech nonprofit. Um, Candid was actually only formed a little over six years ago, um, but but it was formed through the merger of two decades-long predecessor organizations, Guidestar and Foundation Center. GuideStar was a nonprofit that had the most comprehensive data about nonprofits in their work, and Foundation Center was a nonprofit that had the most comprehensive data about foundations in their giving. And so together, Candid has a 360 view now of the social sector in the United States and beyond. And we do use that data in three different ways. We provide tools such as Guidestar and Foundation Directory and now Candid Search that allow users to access those tools, sort of nonprofits to be able to find sources of funding, funders to be able to research and vet nonprofits. We also provide raw data to other platforms and researchers who use that data for their own products and research. And then finally, we leverage the data to be able to provide public goods such as our own research, uh various different campaigns to improve the ways that we use data and uh just drive better insights uh for the sector as a whole.

SPEAKER_01 6:17

Yeah, absolutely. And just to kind of dig into that a bit, obviously there are other data sources out there as well, kind of some of them statutory. So there's a certain amount of information that nonprofits, if particularly if they've got a structure like a 501c3, needs to report on. But obviously, what you do, it collates that and puts it in more usable form. But do you go above and beyond some of that data? And if so, kind of how do you decide which data to collect and what would be useful for the people using the information that you provide?

SPEAKER_02 6:46

Yeah, that's a great question. Let me start with what we have. So Candid gets data from three major sources, um, or three three types of data is probably a better way to say that. Um, the first type of data is official data. So this is data we get from the government, um, largely in the form of 990 data. Uh in the United States, all foundations and nonprofits need to file a 990 that gives a fair bit of detail about their work and their financials. We not only, you know, the 990 um forms are now publicly available through the IRS, but we don't just take the 990 raw data. We have a data science team that processes that data, cleans the data, deduplicates the data, but applies taxonomies to the data to make it useful and discoverable. And then beyond just the official government data, we think that is the sort of baseline starting point. We also get what we call real-time data from sources across the internet. So looking at web pages, news sites, um, social media, and so forth to enhance that data and get much more current data than might be reported in the 990s. And then the real secret sauce for us is we also have what we call contributed data. So this is data that is shared directly with us. Um, that is the most detailed, accurate, and timely data available by both nonprofits and funders. So we have over 100,000 nonprofits that are actively sharing their data with us in the form of a nonprofit profile. And on the funder side, we have hundreds of nonprofit funders who share their grant data with us, again, in more detail and much more timely than we can get through official government sources. So the compilation of all this data gives us the most robust, comprehensive, and current data that's available about the sector. And in terms of what we collect, um, first and foremost, we listen to our users. What are nonprofits and funders asking for? What would be most useful to them? And so from that, there's some things that we have introduced in recent years. For example, we started collecting demographic data about the staff and board of nonprofits because there was a real interest from funders in understanding not only what they were funding, but who they were funding. We also recently have started collecting data about fiscally sponsored organizations. These are organizations that don't have their own 501c3 status but are working with another 501c3 as a fiscal sponsor. And we heard from another funders that they're funding both nonprofits and fiscally sponsored organizations, and so they wanted to also have data about those. And so those are just some examples. But in all cases, we all we want to look at balancing the cost and benefit of the data that we're collecting. And by collecting this data, we really allow nonprofits to tell their own story, so in their own words, what the work is that they do, what they want to highlight, and then what we do in return is provide them with visibility. So nonprofits want to share their data with us because not only are they more visible on Candid's tools, both GuideStar Foundation Directory and Candid Search, but also our data is used by more than 200 partners. This includes the biggest donor advice funds, fundraising platforms, places like Facebook and PayPal. And so nonprofits want to be seen. Um, and by completing their profile, they're able to tell their own story and be seen in lots of places. In fact, we um did a study earlier, a rigorous research study earliest this year that found that funders give 62% more on average to nonprofits with a candid seal of transparency. Um, so it really being more transparent really does correlate with being able to raise more funding.

SPEAKER_01 10:22

Yeah, absolutely. And I'd love to pick up on some of what you said there about the information on demographics and things like adapting to collect data on fiscally sponsored organizations. I just wanted to pick up on you sort of saying that at the end, there's clear evidence that by having that candid seal of transparency and providing the information, it benefits the organizations that are providing that. Is that a case that you've kind of had to make initially for why it's worth the the while of these organizations to go the extra mile and kind of provide the additional data beyond the the 990? And and over time, have you seen so there's sort of less need to make that case actively because it's kind of apparent to those organizations and they they actively want to do it?

SPEAKER_02 11:00

Yeah, I think that's absolutely true. We've been collecting profile data from nonprofits for way, way longer than I've been at Candid. I don't know exactly how long, but I assume decades. And uh yeah, I think initially that that's a case that we had to make. Why, why provide your data in yet another place? But uh I think we, you know, that's one of the reasons we fielded the research report. There was an older research report that had similar findings, but it became quite dated. And so we, you know, we do think it's important to make the case. I think nonprofits are, you know, getting funding is essential for nonprofits. So nonprofits are always looking for ways they can invest their time and resources that help them raise more money. And this is a filling out a profile is a very inexpensive way to really increase your odds of raising more funding. So I think it's been a really strong case. And of course, as it becomes more and more widespread, now it's it's sort of like a LinkedIn profile. Like, you know, most nonprofits, it's just part of the do doing business as you fill in the candid profile so that people who who are looking to fund you, to partner with you, to volunteer with you, have a place to find out more about you in a richer way than just your your you know black and white 990s. So I think that case has become easier and easier over time.

SPEAKER_01 12:15

Yeah, absolutely. And and you said a bit already about how there's a whole range of different organizations using the data as well as contributing it. Maybe you could just kind of unpick a little bit more the some of the ways in which they're they're using that data. Kind of what what ways have you seen that organizations are making use of the data you provide to kind of improve their own services or to make uh funding uh either kind of more equitable or more efficient or more effective?

SPEAKER_02 12:41

And so different platforms use our data in different ways. So I think there's two broad categories of folks who use our raw data. So one is platforms and the other are researchers. On the platform side, this is often donation platforms of some form, like I mentioned, the largest donor advice funds, fundraising platforms like Network for Good, Facebook, PayPal. And what they do is use our data to provide information about nonprofits to donors that are trying to research nonprofits and decide where to give. In some cases, it includes compliance information to ensure that not you know the nonprofit that you're considering passes compliance checks. There's no government flags on it and so forth. And so that data, we make that data easy to consume by these platforms so that they don't have to collect all that data themselves and organize it. And we also provide you know taxonomies and so forth that make it easier to search that data so that if donors interested in giving to a particular cause, they can more easily identify nonprofits that serve that cause. I forgot to say also on the research side, um, we provide our raw data to academics and other researchers, researchers in foundations who are trying to understand, in most cases, a broader space, right? So they're trying to understand trends across the whole social sector, or trends in a particular geography, or trends around a particular issue area. And our data helps them understand sort of what's happening in the space that they're interested in.

SPEAKER_01 14:12

Yeah, absolutely. And in terms of the model for how that works, then because I know from sort of years of talking to people who are involved in other forms of kind of platforms or data gathering organizations, one of the challenges is your infrastructure in the non-for-profit sphere is quite people often appreciate what it does, but it can be difficult to kind of make the case for why it's something that's important to invest in. So how do you make your model sustainable at Candid so that you're able to kind of combine things that do have a direct benefit for individual organizations, but then also some of what you're saying where the provision of data meets a kind of wider public good for the sector?

SPEAKER_02 14:47

Yeah, um we as with many nonprofits, we have a diversified funding stream. Um we're about 80% earned revenue and about 20% contributed revenue. So the vast majority of um our you know financial picture comes from earned revenue, and that's places like Facebook paying to use our data, for example, you know, the various platforms that use our data. We also charge to access our products by end users, but we really try to be thoughtful about how we charge for our products. So we really try to make sure that cost is never a barrier to access. So, for example, we have a you know a standard price for our products that is um offered to foundations, um, for-profit companies that are prospecting for nonprofits and so forth. But then we give a very steep discount for nonprofits because we recognize that nonprofits are going to have fewer financial resources, and we also make our product available for free for the smallest nonprofits who have less than a million dollars in revenue so that they're able to identify source of funding that allow them to grow to a point that they are able to afford ours and other products. So we really try to both be financially sustainable in the tools that we provide, but do so in a way that is thoughtful about making sure that people who want to access our products are able to.

SPEAKER_01 16:08

Yeah, absolutely. And do you also um collect data on federal funding for nonprofits? Because um, I guess one of the areas at the moment where I know there's a lot of challenges in the in the US, but also I mean here in the UK and other places, is in the kind of changing nature of funding that comes from governmental sources. And and so, you know, do you collect that information and provide it? And and how does that help the sector kind of navigate some of those challenges?

SPEAKER_02 16:33

Yeah, we collect um federal and other government funding of nonprofits through the 990s. So um nonprofits report their sources of funding. And the data we have about government funding allows us to paint a broader picture, especially in the US, there's been a lot of change in the ways that funding is flowing from government. And so we've been working with advocacy groups, with media, and with the general public to provide data to help them understand sort of what the impact is or would be of various different policy changes that are have been made or are being proposed. So, for example, one of the things that we found when there was a there was an announcement of a potential freeze in federal funding earlier this year is that you know we we did our research team dug into the data and found that 30% of nonprofits receive government funding. So a lot of nonprofits could be affected, and that if government funding, federal government funding was completely pulled, that um it'd be very extremely difficult for foundations to make up that gap. In fact, it would um every single foundation would have to increase their payout by 3x, so triple their payout in order to make up the gap of federal funding. And so um, of course, that's not possible. Um, and so it just really highlights the um the importance of federal funding in providing a lot of the um services to our communities that people have um that nonprofits do that that we all learn to rely on.

SPEAKER_01 18:09

Um and when it comes to that that sort of work, which obviously is kind of informing sector-level advocacy in a way, or kind of highlighting it, is do you is your role at Candid to use the data you have and kind of provide that for others then to work with? So do you kind of see that as your role in relation to advocacy or or are you yourselves to some extent, you know, positioned as an advocate organization for the sector?

SPEAKER_02 18:32

Yeah, we we primarily see our role as the the data provider for the advocate. So we work very closely with all the leading advocates to equip them with the data that they need to make a fact-based case for um whatever policies um that they are discussing. Um the one place we do advocate on directly, and and I think it's important to say that like I think it's important for nonprofits to collaborate with each other. So we have you know, we have partner organizations who have you know much deeper connections and much more expertise in advocacy, so we really defer to them to lead that charge, whereas we have the expertise in data. Um, but the place where we do do our um advocacy directly ourselves is is around the issue of uh data transparency. So we you know work in coalition with others who are interested in this issue, for example, to talk with the IRS about ways to ensure the data can continues to be transparent and to continue to improve transparent and accessibility of data about the work of the social sector.

SPEAKER_01 19:33

Yeah, and I'd love to pick up on that question around transparency because I know this is kind of a big, big question and a big topic of discussion in the sector more broadly. Um, and I guess it ties into some of the issues around um public trust in institutions and particularly in nonprofits and the concern that maybe there's been a kind of general decline in trust in institutions and a particular challenges for the nonprofit sector. How do you kind of see that relationship between transparency and public trust? Is that kind of an important part of what drives that bit of your work?

SPEAKER_02 20:04

Absolutely. Um, trust in the nonprofit sector is essential. Um, without trust, people won't donate to nonprofits, they won't volunteer at nonprofits, they won't necessarily be comfortable receiving services from nonprofits. So trust is very essential to the core functioning of nonprofits. I um also serve on the Independent Sector Board, and independent sector each year puts out a report called Trust in Civil Society in conjunction with Edelman, and they track the metrics of trust that the public has in the nonprofit sector. And trust in all institutions, as you mentioned, has been declining, including the nonprofit sector. Fortunately, for the nonprofit sector, it is there's still the most trust in the nonprofit sector of um across all the different sectors in the United States at least. And so we're doing better than others, but trust is still declining. And um, in their report a few years ago, um independent sector found that um when they asked about what would create more trust in nonprofits, they found that more information, greater transparency, and demonstrable results were the things that would really drive greater trust, right? Because and it makes logical sense that if you know it's hard to trust something that's alien that you don't know about, seems like a black box. It's much easier to trust whether it's a person or an institution, it's much easier to trust when you have more information, more transparency. You understand who they are, you understand what they do, you understand the finances, um, you understand the results they've they've delivered. That really breeds trust, and then I think um thereby I think will open up the door for more folks to want to engage with those nonprofits.

SPEAKER_01 21:45

Yeah, absolutely. Um and and in terms of kind of what it's trying I guess what it's ideally transparency about. What you said there, it's kind of what people want to know that the you know the money is being spent uh efficiently and that it's got an impact um and this kind of thing. So is the important uh information that's been provided when organisations are transparent, what should they ideally be kind of looking to provide? Because I know there are kind of concerns that sometimes when some information is provided but not the full picture, it's easy then for you know the public or others to kind of latch on to particular aspects of what nonprofits do without necessarily a full understanding, and obviously, particularly around things like overheads, that's been an issue in the past. So, what do you think it would ideally encompass to for nonprofits to be fully transparent?

SPEAKER_02 22:30

This is something that we continue to iterate on um, you know, with the candid profile. Um, we we don't I don't think there's one right answer. So on the candid profile, we have a subset of our fields that we require to earn seals of transparency that are the ones that we think are the most important, the ones that we hear most from funders and other users that they most want to know about nonprofits, you know, what their programs are, what their results are, what their financials are, what their organization looks like in terms of staff. Those are the core things that people want to know about. But then we also give nonprofits the option to share a lot more information, and that will vary based on the type of work that they do. So some may want to show videos, for example, to really, you know, kind of tell a more vivid story of the work they do. So, uh like I said, I don't think there's one right answer. It depends on the space a nonprofit is in, what the types of information their donors or partners are looking for. And I would also say transparency is important on the foundation side as well. Um we're not only we're um we're also seeing a lot of attacks on foundations and the legitimacy of foundations um this year. And uh I don't know if you know, but Foundation Center was actually founded decades ago in the wake of the McCarthy era in the United States, where uh philanthropy was under a lot of scrutiny as it is now. Um and the reason it was founded was to build trust in the work of foundations by increasing transparency, because when it's a black box, people can ascribe all sorts of nefarious purposes. But when you're transparent about this, is this is actually how we've been investing our funds that can sort of pierce the bubble of that that um that that black box and allow um there to be more trust from the public.

SPEAKER_01 24:16

Yeah, absolutely. And I I think uh absolutely that kind of greater transparency for for foundations, particularly something you know we hear uh in the UK quite a lot. I suppose the the qu the question I'd ask in follow-up, just because it's something we've heard a little bit about uh over here from and I know from talking to organizations involved around transparency and open data is a sense that then it's possible that the drive towards transparency might bring additional risks in some cases in a sort of more polarized political climate, because in providing that information, there is the danger that you then sort of open up further avenues for attack. So if organizations are able to identify, for instance, that certain funders are funding in particular cause areas that they politically disagree with. Do you ever sort of have conversations internally about whether there may need to be kind of limits on transparency in some cases?

SPEAKER_02 25:03

Yeah, that's been a subject of much conversation this year for the exact reasons that you sh that you shared. Um, you know, transparency um for for most of candidates' um existence has felt like an unvarnished good, right? Like we want to be as transparent as possible. And and I think that that some of that transparency has resulted in uh folks being more scrutinized because of um what they share. And so um the the the way that we approach this is that we believe that this is there's no right answer for this. There's a this is a decision that each organization needs to make based on their circumstances. And so the way that we've approached this is that we first want to make sure that all organizations are informed. So when they come to our site and they are sharing data with us, we are very clear to let them know that the data they share with us will be public, and so that they can make an informed choice about whether they want to share that data. Uh the second thing we do is that we give them choice. So you um we have, as I mentioned earlier, certain fields that you need to fill out in a profile in order to earn a seal of transparency. Nonprofits want to earn that seal to demonstrate their willingness to be transparent. But at the same time, some of those fields may, there may be information that they would share there that would they feel put them at risk. And so we for the for anything that seems like it might be remotely risky, we have a decline to state option. So you can still be transparent, but choose not to answer some you know some questions or fill out some fields. And the third um thing that we've done is that we've added the ability to suppress your profile. So if you feel that you are under some scrutiny and you don't want to go through and delete every single field, you can just ask us to suppress your profile for a period of time or indefinitely and um have your data essentially taken down until a point in time where you feel more comfortable sharing it again. So what we're trying to do is really, you know, get put the power in the hands of the nonprofits to be able to make those decisions for themselves.

SPEAKER_01 27:09

Yeah, that's that sounds really exactly right. And have you seen, has there been any kind of notable trends in terms of organizations taking up those those capabilities or any kind of shifts towards them maybe rowing back a little bit on some aspects of transparency?

SPEAKER_02 27:24

You know, interestingly enough, there there hasn't it's been very, very limited. For you know, for example, the the ability to suppress your profile. I think there's been less than 10 organizations, or you know, certainly not gotten the number most recently, but a very small number that have asked to do that. And so I think there's a lot of concern about and fear, certainly, that we hear across the sector, but we have not yet seen that translate significantly into um people changing their behavior.

SPEAKER_01 27:54

Yeah, that's really reassuring to hear, I think, because it's as you say, it can be uh sometimes almost a kind of perception of the the issue can then start creating the issue itself. So it's probably good if that isn't happening. Um you you mentioned before that kind of as well as the information on the work that nonprofits uh are doing, you also collect demographic information on the nonprofit sector itself. I'd love to sort of hear a bit more about that and kind of why the organization felt that was important and what you've learned and how you've used some of that information.

SPEAKER_02 28:24

Yeah, so um we started collecting demographic data, I think like around 2018-2019. And as with all the data we collect, we collect data that is being asked for, um that funders are looking for. And um, I think especially in 2020 with the racial reckoning in the US, there was a surge of interest from funders who wanted to understand not only what they were funding, but who they were funding. You know, are we really being equitable in the portfolio that we've we've created? And so um the demographic fields in the candid profile allow nonprofits to share that data one time in a standardized way that then foundations are able to make use of. We have a campaign called Demographics via Candid that has, I think, almost 200 partners now, where funders are basically signing up to partner with us and agreeing to, rather than using their own custom survey or questions, to use the standard that we've set at Candid in consultation with the sector so that nonprofits can share that data one time in a way that can be reused by anybody who needs it. And so that data at the foundation level is giving foundations the ability to benchmark their portfolios to understand sort of what the makeup is of their portfolio as a whole. They can then benchmark that against industry standards, against their peers, and so forth, and help them make more informed decisions and help them recognize where there may be parts of their portfolio that are skewed in ways that they didn't intend, and therefore make better decisions. Um we also that demographic data can be used in aggregate across not just a foundation but across the whole sector to understand some broader trends. And so last year we issued a report called the State of Diversity in the US nonprofit sector that analyzed the demographic data we had collected up till then, which represented about 60,000 nonprofits, by far the most comprehensive data set available. I think now it's closer to 80,000. And that allowed us to get gain insights about the sector that we've all suspected but never had hard data behind. So just a couple data points. Um, one is that we found that the nonprofit sector as a whole is very racially diverse. But what um when we consider all staff, but when we look at leadership, it's not so much. So for example, 47% of all staff identify as white, so less than half of all staff of nonprofits identify as white. However, 70% of CEOs and 66% of board members identify as white, right? So there's a real difference between the leadership of nonprofits and the staff of nonprofits. Another thing we found is that nonprofits that are um majority led by people of color have fewer financial resources. So for um nonprofits that are majority white-led, their financial resources are 54% higher than they are for ones that are majority led by people of color. And so that's a significant delta. So these kinds of data points really help us identify where there are um places in the sector where funding is not necessarily being equally distributed and there may be other factors at play.

SPEAKER_01 31:46

Yeah, absolutely. And uh, I mean, really striking figures, I think pressingly in some ways unsurprising, I think the disparity between the overall picture in terms of racial diversity and and what it looks like in kind of leadership positions. I'm really interested in whether you, within that research, also you distinguished between non-profits kind of operating organizations and funding organizations or foundations as well. Because I know from previous conversations I've had with people in the foundation sector in the US that that some of them are kind of keenly aware that the issues around lack of racial diversity are much more stark on on that side of the equation, um, and whether you'd seen any kind of foundations use some of the data you provide to kind of shine the lens on their own part of the sector in particular and ask questions about that.

SPEAKER_02 32:29

Yeah, I don't recall if we had uh data broken out by foundations in that report. Um, but uh I I do know that we've talked to many foundations that have used our data to um look at themselves and look at um, you know, the the makeup of their own organizations as well as organizations that they fund.

SPEAKER_01 32:49

Yeah, yeah, well that's that's good to know because again, as you say, it's kind of starting from a point of being informed, whereas I guess you know people would have a sense that this is the case just based on their own experience and on anecdote, but actually having the the figures to back that sense up is really important. One thing I I really wanted to ask you about, because obviously the the context for the work that you do around gathering and providing information and and data, you know, that has been uh important for decades now. And I think you know there's still plenty more work to do in terms of kind of building up uh that nonprofit um data supply. But people, I guess, are kind of increasingly aware that there's an additional angle to this, which is the fact that this data potentially provides the raw material for some of the emerging technologies, particularly AI, that we're kind of only really starting to see have an impact on the nonprofit sector. I'd just be really interested, both in kind of how you understand your role as a provider of data in relation to AI in the sector, and also whether as an organization you yourselves have started to make use of some of those tools.

SPEAKER_02 33:50

Yeah, absolutely. So, you know, we've always been a data organization, um, and uh and I think that in the age of AI, data has become even more important because data is the fuel that makes it, you know, the AI runs on AI can't do anything without data. So we think that good, accurate data is going to be ever more important in this in our world, in the world of AI. We've had a data science team for over a decade that has used machine learning techniques to gather data, clean data, um, categorize data, and so forth. Um, and so we've had a long-standing tradition of using AI and machine learning techniques within the organization. Um, I was really excited earlier this week, I think just two days ago, we uh announced a partnership with Anthropic for their new Claude for Nonprofits initiative that we are integrating candid data through an MCP to with Claude so that users of Claude are able to access candid trusted nonprofit data through the Claude interface, right? That we're kind of integrating with them. And so I think that's one example of how like data can really, the data we have can really help power the AI engines that are coming out. Um, we're also looking at ways that we can leverage AI within our own products. So we're doing things with our new product that's just rolling out on Canada.org. Um we have um we're using AI to offer um funder recommendations to nonprofits based on the nature of their work that we are able to identify based on the type of work they do, the places that they work, and the size of organization, which might be the best funders for them. Um and we also um are uh have rolled out a letter of intent um writer or letter of inquiry writer. This is a first um uh entry point into a funder where if you do see a potential match where you can send, you know, like a one pager to a foundation to tell them about your work and um and ask for a conversation. And so um we have a new mechanism now that uses generative AI that to be able to create that letter of inquiry for you that is appropriate for a particular foundation that you think may be a match. So we're constantly experimenting with um AI. There's actually uh a lab site that we have. If you go to Canada.org slash labs, that has a number of other um uh AI experiments that we are continuing to play with and uh integrate into our products as they mature.

SPEAKER_01 36:32

Yeah, really interesting, and certainly around the funder recommendation um bit, I think that's absolutely fascinating. Um I wonder it just made me think actually when we were talking right up front about some of the data sources that you collect and where it kind of goes beyond 990 forms, and you mentioned about drawing on things like kind of wider media reports and information that's available. Obviously, that's largely kind of unstructured data. Have you been using machine learning tools um there to kind of allow you to access some of that data at scale? Because obviously the challenge, otherwise, if a human being's got to read through all of this stuff, it's completely untenable. Um, but actually being able to automate it so that you can do it at scale and give it a bit of structure makes it possible. Is that something that you've uh you've done?

SPEAKER_02 37:17

Exactly. That that's part of what our data science team does is both pulls in and um sorts through and makes sense of all that unstructured data. So for example, news stories are um even though they're unstructured, they're uh the the only way we have when there's an emergency crisis to be able to understand um how funding is flowing in the very mediate term. 990s can take a couple of years to come out. Um so we are able our data science team takes those news stories and is able to discern different announcements or pledges that are being made so that we can paint a picture of what's happening around a particular crisis that's in Yeah, absolutely.

SPEAKER_01 37:56

Um and the other thing I wanted to ask as well, actually, I guess, you know, as an organization that ha that is kind of firmly rooted in in the collection and provision of data, one of the interesting things I think about AI is it's made people, society as a whole, kind of more aware of some of the challenges that come around data and the ways in which data isn't always necessarily neutral. There are questions about which data you collect and why and how you provide it, and obviously concerns about bias developing within an AI systems. As an organization that is taking that role of collecting the data and providing it, do you see that you have a role in kind of safeguarding against some of those issues and kind of countering bias in the collection of data?

SPEAKER_02 38:36

Yeah, absolutely. And that's um, you know, something we're always very thoughtful about. You know, we we hold our responsibility as an objective data provider very seriously. So, for example, you know, one of the ways that that and the data we collect is about organizations, not individuals. So it's a little different from that standpoint. But even about organizations, one of the things that you can imagine is that that we might end up collecting data more about organizations that are already more privileged, right? That might more likely hear about us, have the time to fill out a profile, and so forth. And so, as I mentioned before, we really do a lot to reach out to the smaller nonprofits that are maybe more grassroots, that might be more likely to be led by people of color. And so we have a team that has been doing outreach to folks that might be overlooked in that way to make sure they know about our programs and partner with organizations that they might work with. And we also have an incentive for these smaller organizations to complete their profile by offering them free access to our tools if they do. So we're really trying to make sure we get a full picture of the sector, including those that may not be as likely to be represented otherwise.

SPEAKER_01 39:50

Yeah, it's really interesting. And I guess one thing I wanted to ask a sort of bigger picture question, I guess, uh that probably uh has relevance for Canada in in two ways. I guess the the last 10 years and certainly the last five years have seen an enormous amount of disruption, I guess, both politically and then with kind of unforeseen events like the pandemic. And I suppose both as an organization yourself, how you know, what are the challenges then when it comes to leading an organization through that kind of disruption and how have you navigated them? And then I guess looking at your role within the sector, how have you tried to play a role in helping others to navigate some of those challenges?

SPEAKER_02 40:27

Yeah, um, there's been a lot of disruption and a lot of change, particularly this year. It seems like change keeps coming up at us faster and faster. Um, again, in the US, a lot of that has been driven this year by political change and policy change. Um, and that's been very disruptive for the sector. But I think also AI has been a major disruptor in the sector, both not only in the ways that we may want to need to evolve the way we do our work, but also in the repercussions across the communities that we're serving and how the challenges that communities are facing are gonna evolve over time. Um and so I think that first and foremost, one of the things that we and other organizations, uh other nonprofits are contending with is how to become more nimble. Um, nonprofits historically have been more stable organizations that um have the tried to deliver consistently in a more um, you know, whatever products or services that they deliver, but we're now in a much more dynamic environment where we, you know, the needs are changing constantly. We saw this with COVID where you know the shutdown happened and a lot of the work that nonprofits were doing no longer worked, and we had to all of a sudden reinvent ourselves. So becoming more nimble, being able to be more innovative, I think, is essential in a world where change is happening faster and faster. Um, I also think that data is a really big piece of the picture. Um, when change is happening so fast, you need data to anchor yourself in reality and what the facts are. Um, and one of the ways that we do that is provide context for how funding is flowing. So if you can understand how funding flows are shifting, whether you're a funder or a nonprofit, that gives you better context to make decisions. We've also been offering um uh free trainings to nonprofits to help them look at ways to diversify their funding and find new sources of funding, especially given disruptions in federal funding. Um, and so we think that I think that data is also really critical as a tool to help inform how how to be nimble, right? Like what what you know you uh as as things are disrupted, um we need data to know where which way to go.

SPEAKER_01 42:36

Yeah, absolutely. And it just uh made me think actually, just one follow-up question when we were talking about AI uh before, and particularly, I think this was because you mentioned the work that you're uh just just launched um with uh Anthropic and and Claude. One of the concerns, I guess, that I've heard more recently from nonprofits around AI is the way in which AI is obviously having an impact on traditional methods of search and essentially kind of shifting from list-based search to answer-based search and this sense that actually people might never go to your website anymore. They'll only ever see the information on you via the results that they get from uh from a ChatGPT or another platform like that. Do you think something like the uh partnership that you're developing with Claude can kind of help to you know assuage some of those fears and kind of reassure nonprofits that the information people are getting on them will still be accurate information and kind of representative of what they do?

SPEAKER_02 43:32

Yeah, we see the world is certainly in a moment of change given AI, the the emergence of some of the latest AI technologies. And I think the ways we consume information is likely to change dramatically, just as it has at other points in my lifetime, where we went from you know uh working on local PCs to having the web and the internet to having mobile devices. I think this is another inflection point that has yet to settle out, so we don't know exactly what that's. Going to look like, but it's going to change. And that's why I think accurate data is so important in that change. What we don't want to lose is the ability for nonprofits to be able to tell their own story in the way that they think is most appropriate and for that data to be as accurate as possible. And so I do see our partnership with Claude as um with Anthropic and um and Claude as a first step in that uh one step in that direction is to ensure that our our data is powering some of the new tools that are emerging so that nonprofits, when they're found by, you know, through using Claude are also able to reflect the accurate information about themselves.

SPEAKER_01 44:37

Yeah, absolutely. Um and and I'm aware we're sort of coming up on time. So I I want to sort of bring things to a close. And it'd be really, really interesting to talk. I just I guess as a final thought, I'd really be interested in your sense of where the the nonprofit sector is at this point in time in terms of data. I mean, do you is your sense that there's still a lot more basic work to be done just to kind of get the data that is required and to get it in the right form and to clean it so that organizations, I guess, are positioned for to take advantage of some of the capabilities of new uh AI tools and other technologies? Yeah. Or do you think that that a reasonable amount of that work has been done and we're kind of at the point where we can start to look ahead and sort of experiment with what we can do with some of that data?

SPEAKER_02 45:22

I think there's a lot of different types of data when it comes to the nonprofit sector. Um we primarily work with organizational and funding data. And uh, you know, I think that data is fairly robust. Um, it's continuing to grow. I think its importance will grow over time as AI exposes new ways to really harness that data. And I think there's uh continue that there will be more value that nonprofits can get through other types of data where there I think there's still much more opportunity to do evolve. So nonprofits have a lot of data about their work, their programs, their beneficiaries. So good data on on that front can help nonprofits both increase their impact, better target their work, and better express their results. And so um I think there's still huge opportunities for nonprofits to better harness data and that AI tools will both make it easier and and make what you can do with that data and the power that you can derive from that data ever greater over time.

SPEAKER_01 46:25

Yeah, absolutely. I mean, I think you know, when you see some of the early experiments that are out there and kind of in terms of people applying AI to their cause areas where that data is available, you get a sense of what some of the potential is. But um, yeah, it's certainly early days, but I guess watch that that space. Um Anne, it's just just uh remains to say thanks ever so much for finding the time to come on the podcast. It's been a real pleasure to talk to you and hear about the work at Candid. Um, and certainly, yeah, wish you all the best in the future.

SPEAKER_02 46:52

Thank you so much. It's been a pleasure. Um, and good luck with your podcast.

SPEAKER_01 47:05

Okay, well, my thanks again to Anne May for coming on the podcast. Great to have a chance to talk to her. I'll put links in the show notes to places where you can find more information about Candid and the work they do and some things Anne May's written about, some of the issues that we discussed in the podcast. I'll also put links to places where you can find some things I've written about, some of the stuff that we talked about. If you're interested in the kind of stuff that I uh write and talk about more broadly, do check out the website at whyphilanthropymatters.com. Lots of articles there, sort of shorter guides, all the back episodes of this podcast, lots of news updates about things that I've been doing and saying uh about all kinds of aspects of philanthropy in civil society. Also check out uh my uh social media and do follow me on LinkedIn if you're interested in that. Uh I'm also on Blue Sky a little bit, although not as active there, so LinkedIn's probably the best place to look for me. If you like the podcast and you think you know other people who might like it and find it interesting, do spread the good word. Personal recommendation does go a long way. Uh if you could also find the time to leave us a nice review wherever you get your podcasts, that would be great as it bumps us up the algorithm and every little bit helps. Other than that, tremendous to say thanks ever so much for listening and I'll see you next time. Bye.