The Giving Review: Watching grantmakers more closely, intelligently

This article first appeared in the Giving Review.

Philanthropy is entering an era of increasingly sophisticated observation and analysis of it. While it, and the nonprofit sector of which it is a part, may not welcome the era, it is upon us.

Artificial intelligence is going to allow more new, and enhance already-existing, tools to help better track its funding flows. These revelatory tools may—likely, will—enable closer testing of those public-relations narratives it’s going to try constructing to defend and promote itself and its many policy and cultural prerogatives. These tests will only compound the already-bothersome scrutiny being brought to bear on it by those uncomfortable or discontent with the way in which it’s been exercising power with those prerogatives.

The American Enterprise Institute’s Center for the Future of the American University’s (CFAU’s) helpful new SOURCE tool is just a harbinger of the new era. Developed by CFAU affiliate Tao Tan and publicly unveiled last week, SOURCE is an interactive database of “Searchable Open University Records of Charitable Expenditures.” It includes basic information about more than one million grants from over 57,000 U.S. private foundations to nearly 5,300 colleges and universities since 2008—though the data are more robust beginning in 2020. It is accessible for free.

The data show, according to Tan, that higher-ed giving is highly concentrated among a relatively small number of foundations and its growth is driven by the largest funders. Plus, a large share of foundation dollars is characterized in IRS reporting as general or unrestricted institutional support.

In addition to being helpful, SOURCE is also replicable, of course. Additional contexts in which there could be similar efforts might include foundation support of, say, nonprofit public-policy research institutions, medical-research organizations, museums and cultural groups, K-12 schools and reform outfits, journalism and opinion publications, energy and environmental entities, and community foundations and any of a number of other types of local civic entities. Add your own, whether out of intellectual interest (and/?)or fretful fear.

Other databases, and AI’s additions

SOURCE is not entirely without precedent, though it appears to extend earlier efforts in important ways. Another, arguably similar, recently unveiled database is the Quincy Institute’s Think Tank Funding Tracker, which tracks funding from foreign governments, the U.S. government, and defense contractors—rather than trying to capture all philanthropy. Developed by Quincy’s Nick Cleveland-Stout and compiled largely from self-disclosed donor lists and annual reports, its emphasis is on exposing conflicts of interest and fostering transparency.

First released as a research paper 2022 and later published in ’24, moreover, the “Mapping Philanthropic Support of Science” project surveyed hundreds of thousands of grant relationships between foundations and universities and research institutions; it was primarily a research dataset rather than a public-browsing interface.

Candid’s useful database, which would be considered the giant in the field, is meant to connect nonprofits’ fundraisers with existing and potential funders on an ongoing basis. It is not really organized around institutional networks of influence or thematic categories per se.

SOURCE appears to be more than simply a subject-specific “Candid-plus-AI.” It seems to go quite a long way toward resolving problems presented by manual attempts to compile and distill data about giving, principally including reconciling the many different legal names of a grantee in filed records. It also seems as if it will be much more systematically updatable moving forward.

There are limitations to note. SOURCE-like use of AI cannot do anything to de-obscure Big Philanthropy’s use of donor-advised funds and fiscal sponsorship, for example.

Cautions and concerns, portents and promise

There are also cautions and concerns to be raised—about the AI future in general, of course, including in philanthropy and nonprofitdom specifically. Elite progressive reliance on only supposedly neutral, scientific, data-driven methods is not entirely without precedent either, and AI may extend its earlier efforts in harmful ways, in philanthropy and many other areas, as well. Scientific methods have never fully mastered social complexity. They aren’t very good at it; they can’t do it. If AI ends up arrogantly “doing” grantmaking, that would not portend well for charity, or American democracy.

We cannot risk making AI, or let it become, a god. Nor should it be a foundation program officer, either. It wouldn’t be very good at it anyway.

More humbly and intelligently, however, if AI can substantially reduce the cost of building and maintaining usable databases of philanthropic funding flows and activity, then higher ed will not be the only area mappable in SOURCE’s way—and there’d be great benefit in expanding application of its concept, and thus of knowledge. In line with Martin Gurri’s thinking in his prescient 2014 book The Revolt of the Public and the Crisis of Authority in the New Millenium, in fact, the more broadly this capacity for scrutiny is distributed, the more healthily democratizing it is. To this extent, it’s a good and promising portent.

Philanthropy has long enjoyed operating in an environment where assembling and presenting even basic, raw information about itself required extraordinary time, labor, and thus financial resources for even that limited purpose. SOURCE gives us an early glimpse into a time when the comfort and latitude provided to grantmakers by that permissive environment is appreciably diminished. We should appreciate and encourage it, and its forthcoming progeny.

Source: https://capitalresearch.org/article/the-giving-review-watching-grantmakers-more-closely-intelligently/