Can AI Revolutionize Nonprofits or Widen the Gap: The Double-Edged Sword of Tech for Good
As artificial intelligence (AI) transforms the way we live, work, and learn, concerns arise about its potential to alter the way we think. While its impact on education, arts, and business has garnered significant attention, the effect of AI on philanthropy remains a secondary consideration.
AI's promise to free users from mundane tasks is a major selling point. Developers tout AI as a tool for streamlining, automating, and promoting equity within the nonprofit sector, which often operates with limited budgets and small staffs. Many philanthropic leaders view AI as a game-changing investment for nonprofits, particularly small, community-focused organizations struggling to survive.
However, we're also facing a crisis of compassion, where increasing numbers of people report feelings of desperation and apathy. Does introducing human-less, digital automation into our care-giving processes exacerbate growing feelings of detachment? Furthermore, there's a parallel battle raging: a crisis of attention, where the rapidly moving images on screens have become more captivating than the slower, grittier world that creates them. Is AI the right solution to the problem of capturing the public's attention, inspiring them to care, and maintaining their investment in the cause?
Nonprofits are turning to AI to fill historical gaps – to enhance customer service, alleviate administrative burdens, and capture the attention of major donors. For many leaders in the philanthropic world, the question remains whether the benefits of AI outweigh its drawbacks.
The AI Paradox in Philanthropy
In May, Google launched Search Labs' AI Overviews, an AI-driven summarization feature designed to make searching for information even more seamless. This flagship addition amidst a flurry of dazzling AI features has sparked concerns about the role of AI in philanthropy.
Distinctive summaries appear in a separate, highlighted box below the standard Google Search bar, accompanied by a small conical beaker logo, indicating to users that the results are still in the experimental phase. This distinction is vital. The premature rollout of Summaries wasn't merely underwhelming; it was alarming. The results were unclear, often nonsensical, and became the new vessels for absurd memes and fabricated screenshots; users scrolled right past them. Internal testing revealed a mix of genuinely informative answers and glaringly inaccurate AI hallucinations. (The feature has yet to be fully implemented across all searches.)
Weeks into the launch, journalists were mobilizing a movement against the surge of misinformation and misattributed bylines spawned by the still-limited run of AI Summaries. The tool introduced a potential “catastrophe” to content visibility and online traffic, some publishers claimed, disrupting established metrics for appearing, with credit, at the top of news results. Not long after, the feature was rumored to be incorporating integrated, revenue-generating advertisements.
However, it wasn’t just the news media that was concerned, and it wasn’t just about profit. “What you’re seeing in the for-profit sector is certainly going to affect the nonprofit sector,” said Kevin Scally, chief development officer at nonprofit ratings site Charity Navigator. Just as journalists and creatives sounded the alarm to ethically dubious results, and users pointed out absurdly unhelpful responses, Scally and his colleagues saw the streamlined search summaries as a potential problem for the less discussed world of charity.
Such AI technology could potentially obscure legitimate nonprofits in favor of ambiguous summaries or outrightly false results, these advocates warned. Its search summary results prompt questions of algorithmic bias, and subsequent ones surrounding funding or visibility — the same issues already plaguing the sector, but on a synthetically enhanced scale.
If we’re getting it wrong, it’s not just a matter of a humorous screenshot. It could be a matter of the organization’s reputation and their funding.
Navigating the Charity Landscape in a Sea of Information
AI isn’t novel in the sector, but the timeline has accelerated. Dave Hollander, data science manager at nonprofit data site Candid, explained that the organization and others have invested time and resources into building discovery and audience for nonprofits over the past several years, exploring how AI can aid underserved populations in accessing resources online. Since resources like Charity Navigator and Candid work primarily with large, complex data sets, collated from federal resources and nonprofits themselves, AI tools are an incredibly valuable option to reduce the administrative burden. Other nonprofits may utilize AI to fill the gaps of staff, like site customer service bots helping donors find resources and organizations.
The pervasive integration of AI tools and their increased availability could potentially enable organizations to refine their search engine optimization, Hollander observed, "a feat that would have been unattainable for them in the past." However, discoverability through search has long been a challenge for many organizations, even prior to the advent of AI. And now, AI can also exacerbate this issue.
A straightforward example illustrates this point: How would an AI-enhanced search differentiate between organizations with confusingly similar names? In 2020, for instance, as the global community rallied in support of racial justice advocates and police abolitionists, millions of dollars in donations were channeled to activist organizations. Unscrupulous individuals using SEO-gaming names that incorporated the phrase “Black Lives Matter” managed to divert thousands from well-intentioned donors.
Disambiguations like these are already a problem, a natural consequence of an overloaded internet and a scarcity of unique names. Other issues arise from the repeated recommendation of prominent organizations (such as the Bill and Melinda Gates Foundation) over smaller, localized nonprofits performing similar work.
Furthermore, organizations already compete for visibility in a charitable ecosystem shifting toward less frequent, reactionary giving. “The risk associated with AI Overviews is that, if we’re getting it wrong, it’s not just a matter of an amusing screenshot,” Scally cautioned. “It could be a matter of the organization’s reputation and their funding. Then you extrapolate that forward. If that’s happening on a large scale, where information about those organizations is getting distorted, it has real consequences for the programs they serve.”
Recently, Google announced new updates to AI Overviews aimed at alleviating publishers’ concerns, including prioritizing direct links to sources — but they’re still being tested. Other information-gathering sites, like TikTok, are facing similar misinformation issues with AI-supported searches.
AI excels in specificity only to the extent of the prompt it’s given, limited by the data it’s fed. Search Overviews summarize populated results and prioritize high-ranking links. If a smaller nonprofit isn’t active online and isn’t already surfacing in Google results, it has little chance of becoming AI’s recommended click.
Deciphering the Core of a Nonprofit’s Mission
Within the realm of AI, the intricacies of nonprofit objectives and the methods by which they are achieved are often sacrificed for the convenience of a simplified response. Google itself touted the service with: “Google will do the Googling for you.” However, AI lacks the human brain’s capacity to incorporate the subtleties involved in the processes of helping our fellow humans.
A burgeoning array of media and AI literacy concerns must be tackled initially. In an AI-driven future, how will individuals acquire the skills to proficiently search, vet, and align their charitable endeavors independently, with and without the assistance of an AI bot? What do we sacrifice when we cease performing the "laborious" task of searching for ourselves?
The hypothetical solution lies in nonprofits providing even more data to AI tools' developers — data from nonprofits, data from organizations like Charity Navigator, and personalized behavioral data from donors (read: internet users) that can resolve the specificity conundrum. AI's proponents are enamored with personalization. However, this would stir up even more problems.
“I think that there’s inherently risks with that. Does technology truly comprehend the authentic me? How comfortable am I having Meta and Google and Microsoft essentially build profiles about me?” Scally said.
AI's insatiable appetite for data has raised concerns among many privacy advocates and proponents of data autonomy — a trend also permeating the world of nonprofits. Making such moves with people's personal data contradicts the values of many of the world's most effective social sector actors, those who avoid overlapping their work with Big Tech, who cannot feasibly gather such data (or choose not to among their communities), and especially those who are trying to decolonize their work from historic power holders.
As a wave of new perspectives on charitable giving emerges — including the concept of unrestricted, community-driven funding that intentionally eschews traceable nonprofit data — many nonprofits have already made AI safety commitments that would block deeper personalization. Candid, and its acquired GuideStar rating database, doesn’t allow its data for training third-party models, and only uses a nonprofit’s publicly accessible tax data for internal projects.
AI Risks Reducing Charity to a Cold, Calculated Investment, Devoid of the “Warm Glow of Giving”
The issue with AI implementation is that it’s unfolding at an alarming rate. This speed, with AI designed by large tech industry leaders to streamline people’s digital lives and implemented without input, can just as easily strip people of one of the core purposes of charitable giving: human-to-human connection.
Recent data from Giving USA reveals a 2.1 percent decline in charitable giving in the U.S. in 2023, following a record high in 2021 driven by social and public health initiatives. However, one area that experienced growth in 2023 was donor-advised funds, a philanthropic approach favored by the wealthy elite that has sparked controversy. These funds, managed and sponsored by public charities and nonprofits, pool low-taxed investor money into high-value charity payouts. As Scally explained, the funds essentially write grants to organizations, but individual donors remain detached and potentially emotionally uninvested. Consequently, the actual work of giving is being relinquished.
{"tool_calls":[ {"id": "call_vm3geymzf9w1rx3jyou2ay8k", "type": "function", "function": {"name": "p", "arguments": "q>Meaningful human connection demands dedication and perseverance, qualities that AI's pursuit of efficiency is attempting to render obsolete.
Scally highlights a striking correlation between these trends and tools like AI Overviews: individuals are becoming increasingly detached from the tangible act of donating their resources to those in need, often opting for intermediaries (or even automated systems) to dictate their philanthropic decisions. This shift occurs despite a growing enthusiasm for collective community giving and the concept of mutual support.
"If you're conducting a search, discovering an organization through an AI Overview, and then making a grant through your donor-advised fund… What personal connection do you have to that organization?" Scally inquires. "How invested are you in continuing to support that organization when you don't experience the emotional satisfaction of giving?"
In a recent New Yorker article, speculative fiction author and AI commentator Ted Chiang posits that the fear of AI's takeover of art is misplaced, even as developers attempt to dominate creative fields. "The companies promoting generative-AI programs claim that they will unleash creativity. In essence, they are saying that art can be all inspiration and no effort — but these things cannot be easily separated," Chiang writes. According to the writer, AI strips humans of self-assurance, not drudgery, and devalues the importance of human attention in favor of technological processing power.
Art and philanthropy share a common thread — the need for human intention and creativity. Meaningful human connection requires dedication and perseverance, qualities that AI's efficiency goals are working to eradicate. As Chiang wrote, "It is a mistake to equate 'large-scale' with 'important' when it comes to the choices made when creating art; the interrelationship between the large scale and the small scale is where the artistry lies." And it is at the small scale, where humanity is most present, that charity yields its greatest impact.
Unlocking AI's Potential: Balancing Benefits and Drawbacks for the Greater Good
Individual nonprofits, along with their supporters, such as Candid and Charity Navigator, are not shying away from AI entirely. In fact, Scally dismisses the notion of an evil AI takeover, instead asking, "How can we harness this technology for the betterment of society, and strike a balance between its benefits and drawbacks?"
Candid has been experimenting with AI since Hollander joined the organization in 2015. The nonprofit has continued to explore the potential of generative AI in addressing the challenges faced by smaller organizations, including the drafting of documents like grant proposals and letters of intent.
Notwithstanding the controversy surrounding Google's artificial intelligence technologies, the tech giant has been pouring substantial resources into harnessing AI for social betterment. In April, Google unveiled a $20 million injection into its "AI for Good" accelerator program, which channels funds into high-impact nonprofits like the World Bank, Justicia Lab, and Climate Policy Radar, to expedite the integration of AI within their operations. Google has since scaled up the initiative.
Charity Navigator, backed by Google, is exploring the potential of natural language processing and is internally piloting AI-powered assistance for site visitors. The organization draws inspiration from successful integrations among fellow nonprofits, such as the Trevor Project's Crisis Contact Simulator (also backed by Google).
“I don’t think it’s fair to dismiss AI and claim it will never be able to acquire the intelligence it needs to truly navigate complex areas of social good,” Scally reflected. “I believe things are evolving — AI six months ago looks very different than it does now.” It comes down to more data, casting a wider net, and doing a better job at eliminating bias, Scally said.
Social sector guardians, then, could form a symbiotic relationship with Big Tech’s AI investments, enabling the work of these organizations while keeping things like recommendations in the hands of human professionals. This is already happening: Instead of overwhelming search overviews with advertising, AI could offer more context, more links, and more information.
Still, questions persist. Can AI truly bridge equity gaps? Could its widespread adoption make it easier for full participation of all? The answers have yet to reveal themselves. But that doesn’t mean we can’t formulate a more compassionate plan as it advances. While we seek to add “humans in the loop,” a sense of humanity must remain at the forefront.
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