AI for Humanity

(Ch)AI for Humanity

Kevin Barenblat — Thu, 26 Mar 2026 17:26:56 GMT

Remember the 2025 AI for Humanity Report? We’re kicking off research for the 2026 installation and would love your organization’s perspective. If you’re a nonprofit that uses AI, fill out the survey interest form. And grantmakers, please forward it to your grantees.

Last month, India hosted the AI Impact Summit in New Delhi. If you followed the online coverage, you might think the main takeaway involved a certain CEO duo’s very public refusal to hold hands. Fair enough. But that was hardly the real story.

India may be one of the most important places in the world to look to to understand whether AI can actually work for humanity. Three of my Fast Forward colleagues and several founders in our portfolio made the journey to the Summit and came back with a lot to say.

“The first thing that struck me walking into the AI Impact Summit in New Delhi was how overdue it felt,” said Manu Chopra, co-founder of Karya. “For years, many of the most important conversations about AI have taken place in Silicon Valley. This time, the conversation had come to India.”

Nearly 600K people attended in person; another 900K joined virtually. The range of perspectives in the room was striking — frontier AI researchers sitting alongside AI-powered nonprofit leaders working on agriculture, labor, public services, and language access.

India combines massive population scale, extraordinary linguistic diversity, fast-growing digital infrastructure, and no shortage of real-world need. In other words, if you want to know whether AI can be useful, inclusive, and grounded in everyday life, this is a pretty good place to look.

Here are three reasons we should all be paying closer attention.

1. India’s Running Start

To understand part of why India matters for AI, you have to understand what India has already built. Manu helped illustrate it with the following example:

Consider something as ordinary as paying for a cup of tea. In many parts of the world, paying with a phone means services like Apple Pay or Venmo, tools built by private companies and largely designed for people who already had access to banking. Across India, however, it is common to see a QR code beside a cash register or on a street vendor’s cart. A quick scan from a phone and the payment is complete. Behind that QR code sits UPI, the Unified Payments Interface, a real-time payments network built as public infrastructure. Today, UPI processes more than 20B transactions each month, handling more daily transactions than global card networks like Visa and Mastercard.

UPI works alongside Aadhaar, India’s national digital identity system, which now covers more than 1.3B people and enables residents to verify their identity when accessing services ranging from banking to government benefits. Together these systems form a layer of digital public infrastructure supporting financial services, public programs, and everyday economic activity.

This digital ecosystem is the reason AI can spread in India in ways it simply cannot elsewhere. The infrastructure enabling payments and identity is the same infrastructure that can carry AI tools to people who want to translate a message, ask a health question, or seek agricultural advice.

“Long term, it’s good for the world that AI is not just viewed as a race between the U.S. and China, and I think that India is right now the player that most confidently says, ‘We reject this dynamic.’”- Jakob Mökander, Director of Science and Technology Policy at the Tony Blair Institute for Global Change, in NBC News

2. A Pressure Test for Inclusion

India has hundreds of languages, thousands of dialects, and nearly 200 endangered ones. AI systems trained mostly on English run straight into this reality. Ask one for breakfast recommendations in Marathi and you might get a perfectly fluent recipe for avocado toast: correct language, wrong context.

“AI systems recognize the worlds that appear in their data,” Manu says. “Entire ways of living remain invisible if they’re never documented.”

That invisibility has a human cost. If AI only understands the world as it appears in English-language data, it will only be useful to the people whose lives are reflected there. Everyone else gets a system that was never really built for them.

Manu founded Karya to change that, and they’re doing it in a way that addresses two challenges at once. The platform pays workers across rural India to complete digital tasks in their mother tongues — translating sentences, recording audio, labeling images, evaluating models — in languages that had almost no digital presence until now. That work builds richer, more contextually grounded data for AI systems. It also creates dignified, fairly paid work for communities that have historically been locked out of the modern economy. Workers own their data and earn royalties whenever it’s used. To date, 150K Karya workers have built foundational language datasets for 70+ Indian languages.

India’s linguistic diversity makes it one of the hardest places in the world to build AI that actually works at scale. That’s exactly what makes it worth watching. Per the sentiment shared in last month’s newsletter, “Build for the margins and the center will follow.” If India can get AI right at the edges, across dialects, across vastly different lived realities, we have a much better shot at getting it right everywhere else too.

3. Built for the People, By the People

Representation in data is step one. Building around real lives and local contexts is step two. India has an unusually dense ecosystem of organizations doing exactly that. Part of that may come from India’s corporate social responsibility requirements, which mandate that qualifying companies spend at least 2% of average net profits on social good. That doesn’t automatically produce great nonprofits, but it does help create the conditions for more of them to exist.

Our team saw this up close during site visits with two Fast Forward portfolio organizations working in very different sectors, both built around deep local context.

The first stop was with Rocket Learning at an Anganwadi, a government-supported early childhood center. India’s Anganwadi network is the largest community-led childcare system in the world, with 1.4M centers serving 50M children aged 3 to 6. Historically these centers focused on basics: nutrition, simple numbers, the alphabet. Meanwhile, research consistently shows that the years before age six are among the most critical for cognitive and emotional development. Anganwadi educators wanted to do more. They just didn’t have the tools.

Rocket Learning gave them some: play-based learning exercises led through the centers, an AI co-pilot to help educators build activities tailored to their kids, and short exercises sent to parents’ phones to continue at home. Critically, parents aren’t just recipients. Rocket Learning works directly with them to refine and improve the product, making sure what gets built actually reflects what families need. The mothers our team spoke with said their children were becoming more talkative, more emotionally regulated, more curious. Today, Rocket Learning works with 400K Anganwadi educators and 5M parents and children across India.

The second stop was with Noora Health at a hospital in Rohtak, where the problem looked different but the principle was the same. Family members play an enormous role in patient care, often stepping in where understaffed healthcare systems cannot. Yet those same family members rarely receive any formal training or guidance. They leave facilities anxious, confused, and ill-equipped, leading to preventable complications.

Noora Health treats caregiver education as a fundamental part of healthcare itself and delivers it in the language, format, and cultural context that resonates with the people receiving it. Their Care Companion Program is built through genuine co-creation: healthcare workers, nurses, patients, and family members all shape the educational materials, which are then prototyped and tested in real-world settings before full deployment. Our team saw nurses running ten sessions a day, sharing evidence-based practices with family caregivers and adapting to the realities of the community right outside the hospital doors. Once caregivers return home, mobile messaging continues the training and support, extending guidance beyond the hospital walls. An AI co-pilot also supports healthcare workers by helping triage questions and providing response support.

Both models work for the same reason: they meet people where they already are — already gathered, already motivated, already present.

A Funding Ecosystem Takes Root

The energy we saw at the AI Impact Summit wasn’t just about tech; it was also about the capital mobilizing behind it. At the Google.org Impact Summit APAC, held alongside the main event, we watched philanthropy leaders from across the region gather to rethink how funding flows to AI for good.

The announcements reflected that momentum. Google.org announced a $30M AI for Government Innovation Impact Challenge and a $30M AI for Science Impact Challenge. Google DeepMind launched a new partnership with Indian government bodies to unlock discoveries in science and education. According to Fortune, the entire India AI Impact Summit generated a wave of major investment commitments in the country, with Electronics Minister Ashwini Vaishnaw saying over $200B in AI and deep-tech investment is expected in the country over the next two years.

As Maggie Johnson, VP and Global Head of Google.org, noted during the Summit: “The problems we’re working on are so big that no one organization can solve them alone.” India is showing how the ecosystem — builders, funders, frontline workers, and government — can move together.

Quick Bytes

APN Opportunities and Funding News

Multilingual by Design will pair nonprofits with deep expertise in multilingual education with AI builders to co-design new tools for K-8 math and literacy. Apply by April 3, 2026.
Google.org announced the $30M Google.org Impact Challenge: AI for Government Innovation. Apply by April 3, 2026.
Applications are also open for the $30M Google.org Impact Challenge: AI for Science. Apply by April 17.
For weekly funding updates for your AI-powered nonprofit, subscribe to Funding Forward.

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Are You a Renter or an Owner?

Kevin Barenblat — Mon, 23 Feb 2026 21:11:31 GMT

My co-founder Shannon went to Davos last month, where she heard Canadian Prime Minister Mark Carney issue a call to action that stuck with her: those in the middle must come together, collaborate, and actively distribute power. Don’t wait around for the world you wish to see — take on the world as it is.

“Collective investments in resilience,” he said, “are cheaper than everyone building their own fortresses.”

A few days later, we held our own gathering: Fast Forward’s 2026 Alumni Retreat. Over two days in San Francisco, 125 nonprofit leaders came together to share what’s working, what’s not, and what it takes to build responsibly in this moment.

I had the honor of hosting the closing conversation with Raffi Krikorian, CTO of Mozilla, who gave a rallying call to these impatiently optimistic builders. His message: we're moving into a world where decisions are made for us, not with us. A world where we become renters, not owners, of our tech and data. And if we're not intentional about it, that's exactly what we'll get. The themes echoed Carney's message. If AI's future is going to benefit humanity and respond to the needs of communities, it's up to the people in that room, the “middle” players, to make it so.

After all, isn’t that the most interesting thing we can do with AI? Use our best tech not just to optimize workflows or save nominal time on tasks, but to actually solve our biggest problems?

At the Retreat, builders chose solidarity over isolation, sharing models and tooling, aligning on standards, and coordinating advocacy. Raffi's perspective stuck with them. I hope it sticks with you too.

Whose Side Is Your Tech On?

Raffi rejects the idea that tech is neutral. Design choices embed values. Every decision about who owns the data, who controls the algorithm, who takes responsibility when things go wrong—those aren’t technical questions. They’re values questions.

So he offered a framework worth keeping in your back pocket when evaluating tech:

1. Whose side is it on? Are you owning it or renting it? Are you the product, or are you using the product?

2. Do you have an exit ramp to take what you’ve built with you? Or are you locked in by design?

3. Who’s responsible when it breaks? Does the company take the blame, or do they push it onto you?

These questions matter whether you're choosing tools or building them.

Build for the Margins

Raffi’s advice for responsible building: “Build for the margins and the center will follow.”

He pointed to the curb-cut effect. Curb cuts were designed for wheelchairs, but they benefit everyone: parents with strollers, delivery workers, travelers with luggage. The same applies to AI. Design for underserved populations, low-connectivity environments, communities at the margins, and you create better tech for everyone. Mozilla lives this.

Pragmatic, Not Purist

For nonprofit builders with limited resources, Raffi gets it. His advice: “Don’t be a martyr. Use the best tools you need to do your job now.” But be clear on your values and trade-offs. Always think about exit ramps. Know what compromises you’re making so you can move when better options arrive.

His final message to the room: “Live your values and push them out” — especially when the easy path pulls you away from them.

The values of the people building AI for humanity matter. Choose the world you want to live in, then choose the tech to get there.

Setting the Pace

Kevin Barenblat — Tue, 27 Jan 2026 19:11:52 GMT

2026 is the Year of the Horse, symbolizing momentum, power, and forward motion. That seems about right for AI. The technology isn’t slowing down, but this feels like a moment where direction matters just as much as speed.

The tools are stronger. The stakes are clearer. And the social impact sector has moved past asking whether AI belongs. The real questions now are how it shows up, who it serves, and what standards it’s held to.

I asked some friends and leaders close to the work where they think AI for humanity is headed in 2026. The same word kept showing up in their answers: choice. Choices about trust and guardrails, openness and scale, and when AI should move fast versus when it really shouldn’t.

Saddle up. 2026 might be the year we find out whether we’re steering AI in the right direction — or just holding on for the ride.

+ At Fast Forward, we’re adding to our own horsepower in 2026. We’re expanding our team to support more AI-powered nonprofits doing this work — if you’re interested in joining us, check out our nine open roles.

Jared Chung, Founder, CareerVillage.org

“In 2026, the social impact and AI ecosystem will move from abstract vision to concrete proof. This will be a year defined by unified and deepened collaboration across the social sector, clearer and more cohesive definitions of success (ie: impact measurement), and a narrowing of the field as products are tested against real outcomes rather than ambition alone. We’ll start to see which tools actually earn trust because they work — for practitioners, for institutions, and most importantly for the people they’re meant to serve. At the same time, I expect growing pressure on frontier AI companies to meet the bar for quality, safety, and usefulness that social sector leaders are deliberately setting together — aligning through coalitions to establish shared guardrails and protect users in a rapidly shifting landscape.”

Afua Bruce, Co-Author, The Tech That Comes Next and Principal, ANB Advisory Group

“In 2026, institutions shape responsible AI by investing in three critical areas: teams, infrastructure, and narrative. First, institutions must fund teams with expertise in both technical development and socio-economic impact and support them in creating datasets, AI tools, and evaluation frameworks. Second, they must sustain the infrastructure — human capital and technical capacity — that allows other organizations to build on proven tools. Third, institutions must champion responsible AI through clear communication, demonstrating that well-designed AI can deliver a positive impact.

Institutional choices influence whose knowledge powers AI systems, which impacts matter, and what solutions receive sustained funding—ultimately deciding whether AI reinforces inequity or advances the public good.”

Raffi Krikorian, Chief Technology Officer, Mozilla

“The tipping point for open-source AI won’t come from ideology — it’ll come from economics and convenience. We’re already seeing rapid movement toward small models (1B-8B parameters) running on edge devices, API prices rising, and enterprises feeling trapped in closed ecosystems. At the same time, geopolitical pressures (e.g. export controls, regional restrictions, sovereignty demands) are pushing organizations toward self-hosted, auditable systems. 2026 is the year open-source AI stops being the principled choice and starts being the rational one. The question isn’t whether openness wins… it’s whether we build the infrastructure to make it easy before the defaults harden.”

+ Raffi expands on this thinking — and what Mozilla is building — here.

Vanessa Parli, Managing Director of Programs and External Engagement, Stanford HAI

“In 2026, I expect scientific discovery to accelerate meaningfully as researchers are increasingly augmented by AI, unlocking new breakthroughs in healthcare, sustainability and beyond. More of these advances will reach the public as companies embed the newest models in user friendly interfaces and tools like Claude for Healthcare. This shift creates real opportunity for nonprofits and mission-driven organizations to adopt powerful capabilities that were once out of reach, helping close persistent gaps in resources and expertise. Benchmarks, too, will evolve, moving away from abstract performance scores toward domain-specific evaluations that tie models to real-world outcomes in areas like healthcare, education and law. At the same time, I expect a recognition that while AI can be transformative for certain tasks and workflows, it is ill-suited for others. This clarity will drive more thoughtful deployment, focusing AI where it genuinely adds value. Finally, sovereign AI will gain momentum, as governments seek greater independence from large frontier labs by building their own models and infrastructure, with an emphasis on culturally aware design and development.”

Rey Faustino, Founder and CEO, One Degree

“In 2025, we saw a lot of experimentation using AI for eligibility and enrollment in social services and public benefits, but that also revealed massive limitations, especially around reliability, explainability, and trust given the non-deterministic nature of generative AI. When you’re enrolling someone into something as critical as public benefits, ‘close enough’ isn’t acceptable. The system has to be precise. In 2026, I expect we’ll see those challenges meaningfully addressed through better guardrails, hybrid systems that blend deterministic eligibility engines with AI to continuously improve them, and purpose-built models for government. And with that shift, I predict we’ll see the first U.S. state adopt a generative AI–powered enrollment solution (something we’re building at One Degree!), so we’ll see the move from AI being a pilot to real public infrastructure.”

Gemma Turon and Miquel Duran-Frigola, Co-Founders, Ersilia

“In 2026 we will see a new wave of agentic AI systems for medical research that go beyond task automation and accelerating routine work, becoming active contributors to scientific discovery. In the next few months, we will see breakthroughs in drug discovery not only accelerated by AI, but made possible thanks to it. Agentic AI will become a true companion for medical researchers, amplifying our horizon.”

Scott Kleper, AI Advisor, Fast Forward

“2026 will be the year that AI is front-and-center as a collaborator throughout the day. Rather than serve as a tool that is employed in specific use cases, teams will have adaptable AIs helping them map out their days, keeping projects on the rails, and serving as sounding boards when creativity strikes. The risk is using AI in a generic way that feels hollow. Nonprofit organizations that train their AI collaborators to deeply understand their mission will punch above their weight because the AI is natively speaking their language, not offering generic help.”

Caroline Spears, Executive Director, Climate Cabinet

“There’s an old saying that goes something like this: ‘You may not be interested in politics, but politics is interested in you.’ This is hitting the tech world first hand as backlash grows across the country to AI and data centers — fueled by anger over questions around rising electricity rates, water access, and double standards that carve the industry out from clean energy commitments. 2026 will be the year that AI companies will run headlong into the physical and legal constraints of the existing electricity infrastructure. In the process, they risk sparking political and voter dissent over rising rates. But there’s another path: AI could be a partner in clean energy contracts, lowering electricity prices, and a commitment to community. Advancements in LLMs and NLP could be used to solve big problems. 2026 will be a year of choice.”

Quick Bytes

APN Opportunities and Funding News

Mozilla is accepting nominations for its 2026 Fellows program, supporting up to 10 technologists, researchers, and advocates building better technology futures. Nominations close January 30.
The StepForward: Essential Innovation Challenge is seeking practical solutions helping young people build the skills and pathways needed for an AI-powered future. Selected projects will share a $1.2M prize pool to expand AI literacy and connect learning to real career opportunities. Apply by February 6.

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The AI for Humanity Gift Guide

Kevin Barenblat — Tue, 09 Dec 2025 19:39:49 GMT

Welcome to the AI for Humanity Gift Guide, where every gift comes with impact instead of a return policy. This list features the kind of gifts that stay with people long after the holidays: food security for a family, mental health support for a teen in crisis, math tutoring for a student halfway around the world.

Whether you’re treating yourself to a year-end donation or looking to allocate remaining philanthropic funds, you’re sure to find an AI-powered nonprofit — or two, or seven — worth supporting. Happy holidays and happy giving!

❣️ Love them all? Donate here with the payment description “AI for Humanity,” and we will distribute your donation evenly among each team.

$3 - Connect a family to food resources for a full year

One in eight Americans needs help with food. Making ends meet is hard enough, but getting help shouldn’t be. Lemontree pairs AI with real human support to match families with the closest and best food resources, from fresh produce to SNAP benefits. Lemontree helps 18K families put food on the table every single day.

For less than your morning coffee, you can help one family access food for an entire year. And here’s the cherry (lemon?) on top: every dollar you give will be matched through the end of 2025. Your $3 becomes $6, and one family helped becomes two.

Support Lemontree

$5 - Deliver proven mental-health support to one young person exactly when it matters

When a young person is struggling online at 2 a.m., they need help now, not an appointment three weeks from Tuesday. Koko meets young people where they already are: online. Their AI tools help identify when someone’s in crisis and instantly helps connect them with free, short, evidence-based mental health support. And it resonates — 88% of users find Koko’s service helpful.

Koko has helped more than 6M young people. Your $5 helps them reach another.

Support Koko

$10 - Give 10 students a personal math tutor for a year

Millions of students don’t have access to quality math tutoring. What do most have? Access to a mobile phone. Darsel turns that phone into a personal math tutor. Their AI chatbot texts students practice problems through messaging platforms like WhatsApp and helps when they get stuck. It’s simple text-based learning designed for maximum accessibility.

Since 2022, Darsel has reached 330K students who’ve answered 347M math questions. For $10, you can support 10 more students for an entire school year.

Support Darsel

$30 - Enable 30 hours of AI-powered literacy tutoring

When students receive timely feedback on their writing, their skills grow fast. Quill.org makes that possible with free tools that use AI to deliver instant guidance and personalized practice. Through short, targeted activities, the platform helps elementary through high school students become stronger writers, readers, and critical thinkers.

So far, 12M students have written 3B sentences on Quill. For $30, you can enable 30 hours of literacy tutoring for the next student who needs it.

Support Quill (Write “Quill” as the payment description)

$57 - Support one worker crisis conversation

Job loss is spiking right now, and people need help navigating what comes next. Empower Work connects people facing work crises with trained peer counselors through free, confidential text-based support. Their platform pairs human counselors with an AI assistant that helps guide next steps, from résumé advice to emotional support.

The tool is so helpful that USA Today shared it in their list of job loss survival tips. For $57, you can power support for one person in a work crisis that could change their trajectory.

Support Empower Work

$317 - Help restore a vote

Millions of Americans with criminal records want to vote but face a maze of confusing laws and fines that make exercising their constitutional right feel impossible. Free Our Vote cuts through that maze. Their AI-powered tool identifies eligible voters, then they launch targeted outreach, navigate the restoration process, and ultimately help them vote.

Since 2020, they’ve reached over 1M eligible people and driven a 26% increase in voter turnout. For $317, you can support a net new vote cast and restore one more voice to our democracy.

Support Free Our Vote

$5,000 - Cover trucking school tuition for a returning citizen

68% of people released from prison are rearrested within three years, largely due to unemployment and poverty. Breaking that cycle requires a clear path to economic stability. FreeWorld provides that through full CDL training, an AI-powered coach, and five years of career support for people with criminal histories.

FreeWorld maintains a less than 5% recidivism rate for over 2.3K graduates. For $5,000, you can cover trucking school tuition and help one person build a stable future.

Support FreeWorld

Quick Bytes

A Few of My Favorite 2025 Things

And the best chart award goes to…this chart. It captures the vibe of most AI conferences I attended this year: AI could END SCARCITY, END HUMANITY, or...boost trend growth by 0.2%. A crystal ball would sure save a lot of headaches. Adding one to my wishlist.
Watching the sector put Fast Forward’s report to use has been one of the highlights of my year. Some recent examples: Mashable featured our data alongside AI Equity Project’s to highlight what’s emerging in the field. Tech To The Rescue’s co-founder drew on our findings in a Fast Company piece arguing that AI readiness is philanthropy’s hidden multiplier. And All Tech Is Human included it in their Responsible AI Impact Report, which maps the risks, safeguards, and solutions defining 2026.
A state with a well-known bay might have pulled off one of the coolest AI initiatives this year — and no, it’s not California. Maryland forged a novel partnership with a frontier AI company (Anthropic), a major foundation (Rockefeller), and a digital transformation firm (Percepta) to modernize government services. Governor Wes Moore, who has previously supported SIRUM, will lead on using Claude to help residents access benefits, navigate housing permits, and get the support they need. This will be a use case worth watching.

APN Opportunities and Funding News

The WIN AI Challenge will award up to eight solutions $2.5M or $5M each to help women thrive and build a better workplace for all. Register by December 11.
The Chat for Learning & AI Accelerator, led by Turn.io with support from the Gates Foundation and Anthropic, is accepting applications. Participants will refine their learning models, test real-world chat solutions, and generate evidence of impact. Apply by December 12.
Applications for the Activate AI: Economic Opportunity Challenge are open. The challenge, led by data.org and Zoom, is a global call for innovative AI applications that empower people and communities, and that unlock economic opportunity for a resilient future. Apply by January 8.
The Mozilla Data Collective is rebuilding the AI data ecosystem with communities at the center. Access over 300 high-quality global datasets, built by and for the community in a transparent and ethical way.
Center for Civic Futures and partners committed $8.5M for AI solutions that improve safety net program delivery.
Bezos Earth Fund announced $30M in AI Grand Challenge Awards. The award went to fifteen global teams to deploy artificial intelligence to protect climate and nature.
The OpenAI Foundation shared the first recipients from the People-First AI Fund, a multi-million dollar investment in community-based nonprofits working to strengthen local communities and expand the opportunity of AI.

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Striking a Chord

Kevin Barenblat — Wed, 05 Nov 2025 18:27:47 GMT

Prelude

You may know me as the AI for Humanity guy. But long before Fast Forward, I was playing a different tune as the co-founder of SpotDJ. Back when iTunes ruled our screens, I built a platform for people to DJ their music libraries — rating songs, sharing commentary, curating the perfect playlist.

These days, my beat is a little different, but what hasn’t changed is my instinct to curate and share what resonates. So consider this a return to form: I’m putting together a mixtape, except this time the tracks are my favorite quotes from Fund.AI.

Over 100 philanthropic leaders gathered in San Francisco this October for the second annual convening hosted by the Patrick J. McGovern Foundation and Fast Forward. For two days, the air buzzed with genuine momentum. Vilas Dhar, President of the Patrick J. McGovern Foundation, and Former Vice President Al Gore, co-founder of Climate TRACE, took the stage. So did Maggie Johnson, Global Head of Google.org, and leaders from OpenAI, Google DeepMind, and Anthropic.

Between the talks, workshops, and demos, certain ideas lodged themselves in our brains and refused to leave. If these ideas are going to live rent-free in my head, they’re going to have to take up space in yours too.

Here’s your Fund.AI mixtape — the hits that capture what this moment in AI philanthropy feels like.

Track #1

“To have machines do what humans can already do is not nearly as interesting as having them do what we could never do.“ - Baratunde Thurston

Writer and commentator Baratunde Thurston really underscored what I’m most excited about for AI and social impact. AI-powered nonprofits are solving some of our biggest problems — problems that feel impossible to solve precisely because, until now, they might have been.

We heard this firsthand during the Lightning Learn session. Lemontree‘s Kasumi Quinlan shared how they’re reaching a scale that would be impossible otherwise. To get food to people who need it, their AI considers requirements, travel preferences, and real-time reviews to make recommendations the way a social worker would — but for nearly 20K households daily. And it’s powered by just two engineers and the same frontline staff. It frees up support specialists to offer the genuine warmth and empathy this work demands, while serving more families than any traditional model could reach.

Materiom‘s Liz Corbin and Alysia Garmulewicz showed us how they’re compressing two decades of material science trial-and-error into two years. Their AI co-inventor helps companies develop bio-based materials: plastics made from seaweed, food waste, and mushrooms that compost back into the soil. AI is helping them fast forward the future we need.

Beyond the nonprofit space, we’re seeing AI achieve what seemed impossible. Just last month, C2S-Scale generated a novel hypothesis about cancer cellular behavior, and researchers confirmed its prediction with experimental validation in living cells. This isn’t about replacing what humans can do. It’s about expanding what humanity can achieve.

Track #2

“We all face the same choice over and over again, and it’s between the hard right and the easy wrong.” - Al Gore

Al Gore wasn’t there to sugarcoat the climate crisis. He was there to talk about what happens when you give people the data they need to make the hard right choice.

Climate TRACE, the coalition Gore co-founded, uses satellites, AI, and remote sensing to track emissions from over 660M individual sources worldwide — not just power plants, but also ships, planes, landfills, and rice fields. Gore walked us through “Cancer Alley,” an 85-mile stretch of Louisiana where some communities face 50 times the cancer risk. Climate TRACE can show you the plumes using visualizations that connect the dots between emissions and human health in ways raw numbers never could. When people can see the problem this clearly, they’re motivated to act.

And action is happening. Last year, 93% of all new electricity generation installed worldwide was renewable. This year, renewables overtook coal as the world’s biggest source of electricity. Gore reminded us that it’s going to be hard to accelerate this transition away from fossil fuels, but hard is not the same as impossible.

For funders, the question becomes: Are we backing the organizations that make it impossible to look away and easier to take action?

Track #3

“There’s absolutely misuse of these technologies. But there’s also missed use.” - Shannon Farley

In her conversation with Maggie Johnson, my co-founder Shannon hit on the notion that we spend a lot of time worrying about AI being misused — and we should. But what about all the ways we’re missing the use entirely?

If funders can’t experiment with these technologies, how can we expect to support the communities we care about in doing the same? It’s hard to evaluate an AI proposal or understand what responsible AI looks like if you’ve never prompted a model.

This isn’t about funders becoming AI experts overnight. It’s about getting comfortable with experimentation: trying tools, learning what works. The organizations we fund are already doing this messy work of innovation. It’s time we did it alongside them.

Quick Bytes

APN Opportunities and Funding News

Humanity AI committed $500M to build a people-centered future for AI. The coalition is made up of the Doris Duke Foundation, Ford Foundation, Lumina Foundation, Kapor Foundation, John D. and Catherine T. MacArthur Foundation, Mellon Foundation, Mozilla Foundation, Omidyar Network, David and Lucile Packard Foundation, and Siegel Family Endowment.
The WIN AI Challenge will award up to eight solutions at $2.5M or $5M each to help women thrive and build a better workplace for all.
data.org and Zoom launched The Activate AI: Economic Opportunity Challenge, a global call for applications of AI to empower people and communities to unlock economic opportunity for a resilient future.
Bezos Earth Fund awarded $30M for AI Grand Challenge for Climate and Nature.

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I am living and breathing AI for humanity these days. If you are too, let’s talk!

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84% of AI-Powered Nonprofits Agree on One Thing

Kevin Barenblat — Thu, 02 Oct 2025 21:12:17 GMT

I recently said something that stopped my colleagues in their tracks: “We don’t really care about AI.”

They looked at me strangely. And fair enough. At Fast Forward, we’ve staked a lot of our strategy on AI. We write talks, playbooks, case studies — this newsletter — all with the purpose of showcasing how nonprofits are using AI to progress their mission.

But AI isn’t the point. It’s not the endgame. The endgame is kids learning, families thriving, communities stronger than they were yesterday. AI just happens to be one way to get there.

That’s why we set out to create the 2025 AI for Humanity Report. We wanted to understand if and how AI was helping nonprofits improve their key metrics. What we found was a diverse landscape of organizations already putting it to work: some building AI into the heart of their solutions (AI-powered nonprofits), others using it behind the scenes to run faster and leaner (AI-assisted nonprofits).

Download the 2025 AI For Humanity Report

Chronicle of Philanthropy’s Eden Stiffman highlighted the rapid transformation of the sector: “Fast Forward has supported tech nonprofits for a decade, and data from its accelerator program shows just how quickly AI is transforming the field. In 2024, only 13 of 247 applicants identified as AI-powered. By 2025 that number jumped to nearly half, and in 2026 it more than doubled again, to 379 of 782. Today, more than half of Fast Forward’s alumni describe themselves as AI-powered nonprofits.” It’s true. AI has infiltrated the tech nonprofit sector.

We heard stories of exponential reach and hours of time won back for mission-critical work. But we also heard about the steep costs, the missing technical talent, and the urgent need for responsible guardrails. If AI is going to deliver real, lasting impact, nonprofits and funders alike will have to make sure the momentum continues in the right direction.

We hope the 2025 AI for Humanity Report helps funders see where and how to lean in on AI for humanity, and helps nonprofits see what’s possible. Below, the top takeaways for both at a glance.

“Typically philanthropists have wanted to fund a program where we hire someone and we screen a thousand patients. Now without the need for additional capital, we can screen a million patients. AI has really unlocked potential for scale and has allowed us to think about our impact in orders of magnitude larger.” - Jordan Shuff, Co-Founder, Visilant, in the Chronicle of Philanthropy

Funders: Support the Messy Middle

One thing came through loud and clear: 84% of surveyed AI-powered nonprofits said funding would most help them develop and scale their AI work. But funding alone isn’t enough. AI-powered nonprofits need flexible, early-stage support that covers the costly, invisible work, like preparing data, testing, and validation, that makes breakthroughs possible.

We boiled down the key lessons for funders in the Funder Takeaways section of the report. Philanthropy has a once-in-a-generation opportunity to shape how AI is deployed for social good. By backing nonprofits early, funding technical talent, and supporting responsible practices, funders can accelerate the sector’s momentum while ensuring AI is developed with equity and ethics at the core.

To build on this data, we released a companion whitepaper, The Philanthropic Reset: How Philanthropy Can Lead in the Age of AI, co-written with our partners at Google, Maggie Johnson, Brigitte Hoyer Gosselink, and Stuart McLaughlin. It’s a roadmap for funders who don’t just want to watch this moment — they want to lead it.

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“We’ve seen how nonprofits are already using AI to transform lives. Imagine what’s possible if more funders joined forces to give these solutions the scale they deserve.” - Maggie Johnson, Global Head, Google.org

Nonprofits: Starting Small, Reaching Big

AI isn’t just for Silicon Valley — it’s for you too, nonprofits. Across the sector, we’re seeing two tracks emerge. AI-assisted nonprofits are weaving AI into operations to reclaim time and stretch resources. Meanwhile, AI-powered nonprofits are putting AI at the heart of their programs, unlocking entirely new ways to serve communities. And some organizations are putting AI to use in both ways.

What’s striking is how fast this movement is growing. Nearly 40% of surveyed AI-powered nonprofits have been using AI for a year or less, yet they’re already reaching people at scale. One of my favorite findings: the majority are actively incorporating community feedback into system updates, making sure their tools reflect the needs and values of the people they serve. Check out the Nonprofit Takeaways section of the report for more learning.

To help nonprofits take the next step in their AI journey, we refreshed the Playbook on AI for Humanity. It’s full of practical guidance from nonprofit leaders who’ve been there, plus tips on building responsibly and ideas you can put into practice right away.

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“This is the way the sector will have to go. In these dynamic times, we all have to do more with less, and AI can unlock efficiencies and impact … There’s a huge opportunity for philanthropists to set the stage for AI that we deserve.” - Shannon Farley, Co-Founder, Fast Forward, in the Chronicle of Philanthropy

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APN Opportunities and Funding News

OpenAI’s People-First AI Fund provides unrestricted grants to organizations advancing AI literacy, community innovation, and economic opportunity. Apply by October 8.

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Sigmund Droid

Kevin Barenblat — Thu, 21 Aug 2025 17:33:33 GMT

A recent Harvard Business Review study revealed the most common use of AI in 2025 is for therapy. Which means that somewhere out there, ChatGPT is probably asking someone "And how does that make you feel?"

But here's a thought: maybe it's time we ask how people feel about AI.

The Collective Intelligence Project (CIP) has been doing exactly that. Since 2021, CIP has partnered with major AI companies and governments to test what happens when you ask the public what they want from AI. They’ve worked with Anthropic to train Claude on one of the first collectively-designed constitutions, and alongside Audrey Tang and Taiwan's Ministry of Digital Affairs to pilot democratic processes for AI policy.

Every two months, their Global Dialogues survey takes the pulse of thousands of people across 70+ countries. The latest round focused on AI consciousness attribution. How do these results make you feel?

Trust in AI chatbots (58%) is now more than double the trust in elected representatives (28%)
36.3% felt an AI truly understood their emotions or seemed conscious
11% would consider a romantic relationship with AI, and 17% wouldn’t mind if their partner did

No wonder people were holding actual funerals for deprecated Claude models and mourning their preferred AI companions when GPT-5 rolled out.

“Every time people participate in [Global Dialogues surveys], around 70% of them say, ‘I have never felt listened to before.’ And this is a problem we want to solve. I think we can move from a future of artificial general intelligence to a future of augmented collective intelligence.” - Divya Siddarth, co-founder of the Collective Intelligence Project, on Reid Hoffman and Aria Finger’s podcast Possible

Cultural Intelligence Agency

So, what do you do with insights like these? If you're CIP, you open them up to the world and see what people create. This spring, CIP hosted the Global Dialogues Challenge, inviting anyone to turn their survey data into something new. Over 500 people responded with films, research papers, video games, and more.

The winner was the AI Cultural Intelligence Agency, a detective game where kids discover how different cultures think about AI and figure out how to bridge those perspectives. It's designed to train the next generation of technologists to build inclusive systems from the start.

Creator Saranyan Vigraham explained: “We’re teaching our children the ‘how’ of AI brilliantly — coding, algorithms, technical skills. But we’re forgetting the ‘why’ and the ‘for whom.’ The children playing detective today become the leaders building inclusive AI tomorrow. Let's make sure they're ready to make it work for everyone, and not just people who look and think like them.”

All the winners can be viewed at cip.org/challenge.

"Tech revolutions don’t automatically create shared power and prosperity. That balance emerges when people recognize their collective agency in shaping how tech impacts their lives and demand shared governance models that expand the range of stakeholders included in shaping those decisions." - Michelle Barsa, Principal, AI x Human Connection at Omidyar Network, a partner of Global Dialogues

From Feedback to Frameworks

The Global Dialogues data is making one thing clear: there’s a growing gap between how AI is being developed and how people actually experience it. CIP’s next move is to close that gap by continuing to turn public input into tools that can shape the future of AI.

Weval: Think Wikipedia, but for AI safety. This open-source project lets anyone build custom evaluations that test what actually matters in real-world deployment. One recent Weval, built in Sri Lanka, checked whether models could handle local history and context. Most struggled without heavy prompting, a reminder that “global” AI often isn’t.
Global Dialogues Digital Twins Evaluation Framework [in progress]: If you’re going to delegate decisions to an AI, shouldn’t it reflect who you are? Your values and behaviors? CIP is experimenting with ways to measure how well AI agents can act as stand-ins for real people.
First Contact Assembly [in progress]: Partnering with the Earth Species Project, CIP is exploring how governance might change if we can understand non-human animal communications.

If CIP has anything to say about it, AI won’t write the future. We will — hopefully with better prompts.

"Every perspective excluded from AI development — whether human or from another species — is a future we'll never see, a solution we'll never find, and a harm we'll never anticipate." - Aza Raskin, co-founder of the Center for Humane Technology and Earth Species Project

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APN Opportunities and Funding News

Building an AI-powered nonprofit? Apply to Fast Forward’s Accelerator by September 8. The hybrid program, which runs from February to May 2026, provides $25K, training from seasoned tech nonprofit founders, and mentorship from tech experts.
The Salesforce Accelerator – Agents for Impact equips nonprofits with funding, tech, and pro bono expertise to confidently create customized AI agent solutions. Submit your interest by September 10, 2025 to be considered for the next cohort.

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Prime Time

Kevin Barenblat — Wed, 18 Jun 2025 16:48:39 GMT

I’ve spent a lot of time reading about AI breakthroughs that promise to change the world "someday." The bad news: we can’t wait. The (desperately needed) good news: we don’t have to.

At Fast Forward's Demo Day, builders shared how they’re already using today's AI to create plastic alternatives, eliminate preventable blindness, and tackle challenges that affect billions of people worldwide. Change isn't coming — it's happening right now. Meet the AI-powered nonprofits from Fast Forward's 2025 Accelerator cohort.

Bayes Impact

[Pitch]

Social workers manage staggering caseloads and rely on outdated tools, limiting their ability to support clients. Now, Bayes Impact's CaseAI is giving social workers superpowers. Their AI integrates with case management systems and frees up to ten hours a week by drafting care plans, suggesting actions, and tracking follow-ups. Co-founded by data scientist Paul Duan with Jérémie Doucy and Élodie Juan-Julia, Bayes Impact is giving social services the tech boost they need.

Collective Intelligence Project

[Pitch]

A handful of people make the most important decisions about AI, yet these decisions shape the lives of billions. The Collective Intelligence Project (CIP) ensures it’s not just the powerful who have a say. By surveying tens of thousands of global voices bi-monthly, their research informs frontier AI development, shapes national policy, and pushes for a future where AI serves everyone. Founded by Divya Siddarth, a TIME100 AI-named leader, CIP is putting collective flourishing at the center of the AI conversation.

+ Their newly launched Global Dialogues Challenge invites you to get creative — write stories, generate insights, or build tools — with their global dataset.

“Nonprofit leaders bring bold ideas and deep commitment to the work. With 70% of this year's Fast Forward Accelerator cohort using tools like AI, they’re building even more powerful, human-centered solutions to complex global challenges — and we’re proud to support these leaders as they work to solve our toughest problems.” - Natrina Gandana, Senior Manager of Philanthropy, Salesforce

Materiom

[Pitch]

Plastic creates forever waste, harming human health and the planet. While sustainable alternatives exist, they can take up to 20 years to bring to market. Materiom’s AI accelerates the discovery of bio-based materials 10x faster, helping companies swap out plastics for sustainable alternatives. Co-founded by Dr. Alysia Garmulewicz and Liz Corbin, Materiom blends cutting-edge research with a commitment to turning packaging into plant food, not pollution.

Scrutinize

[Pitch]

Judges hold immense power, but the data on their decisions is buried in long records that are hard to navigate. Scrutinize uses AI to analyze thousands of New York court rulings, surfacing patterns and performance metrics that reveal how judges actually serve the public. The clear, accessible data can then help inform judicial reappointments. Founded by Oded Oren, a former Bronx public defender, Scrutinize is bringing data to the bench so that fairness can follow.

VectorCam

[Pitch]

Half of all humans who have ever lived have died because of a mosquito-borne illness, yet malaria control still relies on analog methods in many countries. Now, VectorCam is turning smartphones into field-ready tools for malaria elimination. Their 3D-printed lightboxes attach to phones and capture high-quality images of mosquitos, then their AI identifies species in seconds instead of months. Co-founded by Marina Rincon Torroella, Dr. Soumyadipta Acharya, and Sunny Patel, VectorCam is giving frontline workers the data they need to fight malaria faster and smarter.

“It’s so energizing to hear from nonprofit leaders who understand that the true power of AI lies in its ability to elevate human potential. This technology can accelerate our progress on today’s most complex challenges, while unlocking time and opportunity for more human connection and collaborative innovation.” - Carrie Varoquiers, Chief Philanthropy Officer, Workday

Violetta

[Pitch]

70% of women in Latin America experience relationship-based violence, but few seek help. Violetta is an AI chatbot and resource library that serves as a digital confidant, offering free, culturally relevant guidance, psychoeducation, and referrals to those in need. So far, Violetta has supported over 250K users. Co-founded by Floretta Mayerson and Sara Kalach, they’re creating a safe space for people across Latin America to build healthy relationships.

Visilant

[Pitch]

One billion people live with preventable vision loss, often because access to quality eye care is out of reach. Visilant’s hardware and AI turn any smartphone into a powerful diagnostic tool, instantly identifying conditions like cataracts with 95% accuracy. Co-founded by Jordan Shuff, Dr. Kunal Parikh, and Dr. Nakul Shekhawat, Visilant’s bringing sight-saving care to rural patients — and helping patients see a clearer future.

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APN Opportunities and Funding News

Applications are open for Fast Forward’s AI and Data Bootcamps. Come for AI, data, or both. Apply by June 30.
Google.org announced the next cohort of the Google.org Accelerator: Generative AI. Each organization will receive a share of $30M along with six months of technical training, pro bono support from Google’s AI experts, and access to Google Cloud credits.
The United Nations' International Telecommunication Union and Tech To The Rescue selected 12 finalists for the 2025 AI for Good Impact Awards.
AlleyCorp’s Nonprofit ENG(INE) is looking for the next cohort of builders. This program matches selected nonprofits with a free, dedicated AI engineering team. Apply by July 30.

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Top of the Class

Kevin Barenblat — Wed, 21 May 2025 15:01:07 GMT

With graduation season in full swing, I’m attending my fair share of graduation parties. There’s cake, “Graduation (Friends Forever)” by Vitamin C on repeat, and a whole lot of talk — from kids and parents alike — about what comes next. Whether you’re 18 or 48, transitions are tough, and the questions keep getting bigger: Should I go to college? Which path fits my passions? Am I happy at my job?

This month, I’m spotlighting AI-powered nonprofits (APNs) helping people navigate those turning points, whether it’s applying to college, making it through, or facing a make-or-break moment at work. The future of work isn’t just about skills or tech. It’s about helping people move forward with more clarity, confidence, and support.

P.S. In three weeks, our 2025 Accelerator cohort will have their version of a graduation: Demo Day! Register for the 90-minute virtual program here. You won’t want to miss it.

Rooting for the Future

Most high schoolers receive just 45 minutes of guidance counseling across their entire four years — less time than an episode of Severance to discuss their future. That short window can make a long-term impact. Uprooted Academy was built to change that. The organization pairs AI with personalized human support to help students prepare for the future. Each student starts with an assessment that maps their goals. The platform then creates a tailored action plan, whether they’re aiming for a four-year university, community college, or straight-to-workforce success. If a student is experiencing high stress while executing their plan, the platform's AI intervenes with targeted activities like breathwork and mindfulness exercises in a digital wellness room. So far, Uprooted has helped over 11,000 students, and it’s only just taking root.

"Much of the conversation focuses on AI replacing jobs, but that’s only part of the story. AI is also equipping us to build radically more personalized, responsive workforce and education systems to meet this evolving labor market. For the first time, we can offer every student a world-class mentor, enable true skill-based hiring without degrees, deliver hyper-personalized coaching, match benefits proactively, and much more." - Matt Zieger, Chief Programs & Partnerships Officer, GitLab Foundation

Beyond Ready

Beyond 12 helps first-gen college students stay the course to graduation by combining human coaching with AI-powered insight. Their app, MyCoach, turns college success into bite-sized nudges and timely reminders, while near-peer coaches offer the kind of I’ve been there support that builds confidence and momentum. Behind the scenes, an AI engine flags when students may be struggling and prescribes targeted outreach so schools can step in when needed. It’s a model that’s working: students coached by Beyond 12 are twice as likely to earn their degrees. Now, as a winner of the Robin Hood AI Poverty Challenge, they’re scaling their model to deliver even more support. With Beyond 12 in their corner, more students are turning tassels — not turning back.

"When we think about [AI], we need to put human dignity, human well-being — human jobs — in the center of consideration." - Dr. Fei-Fei Li

When Work Doesn’t Work

Work stress is everywhere, but support? Not so much. Empower Work is a nonprofit textline helping people navigate the hardest moments on the job, from toxic managers to ethical dilemmas to career crises. Their platform combines trained peer counselors with an AI assistant that guides users through their next steps, offering summaries, resource suggestions, and skill-aligned advice. It’s confidential, free, and designed with equity at its core. Empower Work has supported over 450K workers so far, with 91% reporting improved mental health. When the workplace feels like too much, Empower Work is there to lighten the load.

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APN Funding News

Collective Intelligence Project announced its Global Dialogues Challenge, an open call for responses to a new dataset on global perspectives on AI. Submit benchmarks, visualizations, artistic work, or analysis. Apply by July 11.
AWS opened its AWS Imagine Grants, which includes The Pathfinder – Generative AI award. The award will provide support for a highly innovative, mission-critical project that leverages generative AI. Apply by June 2.
There’s still time to apply to New Rising Ventures’ Responsible AI Funding Cycle, offering $50K grants to early-stage nonprofits using AI to serve the public interest. Apply by June 13.

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Funders, Start Your Prompt Engines

Kevin Barenblat — Tue, 06 May 2025 15:00:58 GMT

New research confirms what many of us in the sector have felt: philanthropy isn't sure where to steer when it comes to AI in the social sector.

Nonprofits are actively scaling their impact with AI, but funders are still unsure how to evaluate or fuel that work. Alethea Hannemann (Board.Dev) and Chantal Forster (Annenberg Foundation) shared a piece in The Chronicle of Philanthropy, where nonprofits expressed frustration that funders often stall — not from lack of interest, but from a lack of confidence. Project Evident’s Funding the Future report echoes the growing disconnect.

In my work at Fast Forward, I’m a connector between grantmakers and AI-powered nonprofits. We’ve seen both the promise and the paralysis. For this edition, we compiled advice for how funders can confidently engage with AI grantmaking with insights from Nick Cain (Vice President of Strategy & Innovation at the Patrick J. McGovern Foundation), Shannon Farley (Co-founder and Executive Director at Fast Forward), and Aras Jizan (Senior Program Officer at the Gates Foundation).

Fast Forward is also working on a report on how nonprofits are evaluating and building AI. The goal: help funders move from questions to clarity. If you’re a nonprofit using AI, we’d love your input. And if you know one, please pass the survey along.

You don’t have to floor it — but it’s time to shift out of neutral. Here’s how funders can get into gear and steer towards what’s already working.

What’s your most valuable piece of advice for other funders just beginning to evaluate AI-focused nonprofit proposals?

Before you fund your first AI-powered nonprofit, begin with this advice from people already in the driver’s seat.

Nick says it starts with trusting your instincts. “Strong tech strategy usually mirrors strong overall strategy,” he explains. “You don't need to be an expert to spot a strong AI proposal; you just need to stay curious and ask good questions.”

Shannon pays close attention to the process behind the proposal. “Don’t just evaluate the technology, evaluate the practices behind it. The strongest AI proposals are grounded in good data, bias testing, and real community feedback,” she says. “Fund nonprofits that are building responsibly and can show how they’re learning and improving over time.”

For Aras, the focus is on real-world relevance. One use case he looks for is what he calls “navigation technology” — tools that help people make critical decisions in high-stakes moments, like what to do after receiving an eviction notice or losing your job. “The key is asking: Who's going to use this? In what context? And how will we know if it works?” he says. The best proposals, in his view, are targeted interventions, grounded in user research and built to learn as they go, not solutions in search of a problem.

The message is clear: you don’t need to be an AI expert to know what good looks like. Smart proposals solve real problems, center real users, and show their work along the way.

“Narratives about the future of AI are coming primarily out of big tech; we need to ensure they’re also coming out of civil society. Philanthropic funders serve as crucial catalysts by providing flexible capital and de-risking innovative AI projects that can transform the social sector through solutions designed with and for the communities they serve.” - Laura Maher, Chief of Staff; Director of External Engagement, Siegel Family Endowment

What single question has proven most revealing when evaluating a nonprofit’s AI proposal?

Philanthropy doesn’t need to have all the answers when it comes to AI, but it does help to ask the right questions. A quick diagnostic can save you from a bumpy ride.

Nick shared a simple but necessary question: Why? “Why this tool? Why now? Why do you believe your community wants or needs it?” he said. “Challenging yourself to ask ‘why’ — many times if you need to — uncovers the assumptions baked into a proposal. It helps ensure the project is solving a real, clearly defined problem, not just using AI for its own sake.”

Shannon agreed: “Asking why is the right question. Just ask my toddler.” She also keeps a close eye on safety. One question she often asks: How are you building your AI solution to avoid bias and unintended harm? It’s a powerful way to understand whether a team is building responsibly. “You can go a step further by asking if they have an AI policy. If they don’t, I point them to our Nonprofit AI Policy Builder.”

Aras asks: How quickly will you know if your approach is working, and how will you know? “To meaningfully develop and deploy AI in the social sector, we need to bridge the gap between software’s fast feedback loops and impact evaluation’s slower pace,” he said. “Strong teams can point to specific signals they’ll track within weeks, not months. They understand success isn't about perfect deployment but iterative, systematic learning. And they’re thoughtful about testing responsibly, monitoring for unintended consequences and putting guardrails in place to catch issues before they scale.”

For more questions worth asking — and the thinking behind them — check out The Philanthropist’s Guide to Nonprofit AI Investments. It’s a practical starting point for any funder looking to evaluate proposals with more clarity, confidence, and care.

“As a funder focused on empowering people with the skills and tools to succeed in tomorrow’s economy, we support nonprofits that thoughtfully expand access to personalized learning and are focused on teaching young people how to leverage AI for their own future jobs. By investing in these innovations, we can strengthen people's capacity and unlock a wider array of future opportunities for everyone. As AI continues to evolve, philanthropy has a powerful role to play in shaping it for positive social impact.” - Stephanie Lo, Head of Philanthropy, Endless Network

What resources or networks have been most valuable to you in building your own AI funding literacy?

There’s no manual for funding AI in the social sector, but there is a growing community of people learning by doing.

For Nick, the most valuable insights have come from spending time with the people who actually build technology. “Engineers, product managers, data scientists — understanding how tech gets built has given me a clearer sense of what's realistic, what's risky, and what good execution really looks like.”

Shannon takes a similar approach, rooted in proximity to the work. “I have the advantage of working with AI-powered nonprofit leaders every day,” she says. “I find it most productive to sit down with them and ask what’s worked, what’s failed, what it really costs, and what they would do differently. Then, I talk to funders and ask those same questions.” She also makes time to read, from general AI coverage to sector resources and peer perspectives, like those from the Technology Association of Grantmakers, Tristan Harris, and Raffi Krikorian. “It’s worth the time investment.”

To Shannon’s point, it’s important that the community is transparent about how it’s going — funders and nonprofits alike. Jonathan Petts (Upsolve) and Steven Lee (SkillUp Coalition) shared an article on what didn’t work in their early chatbot deployments, and how they’re now evolving their AI strategies to better meet users’ real needs. In their words: “We don’t have all the answers. But we wanted to share our early learnings in case they’re helpful. We’re sharing our honest assessments to open a conversation.”

That’s the kind of leadership that moves the field forward. No one has the full roadmap — but if we share what we’re learning, we’ll all get better at navigating the curves ahead.

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APN Funding News

New Rising Ventures launched its Responsible AI Funding Cycle, offering $50K grants to early-stage nonprofits using AI to serve the public interest. Applications are open through May 22.
LinkedIn announced a $3M fund to support nonprofits around the world that are harnessing AI to drive economic inclusion.
The Schultz Family Foundation committed $3M to AI-powered career tools for overlooked young adults, backing groups like CareerVillage.org and CodePath.
Robin Hood’s AI Poverty Challenge awarded nearly $4M to nine nonprofits using AI to tackle poverty, including Beyond 12 and Unlocked Labs.

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Model Behavior

Kevin Barenblat — Thu, 27 Mar 2025 17:06:22 GMT

The open source community is once again doing what it does best: disrupting the status quo. From DeepSeek-R1 to Meta's Llama to Ai2's OLMo 2 32B, open models are now outperforming and undercutting the costs of some proprietary AI alternatives. As a result, Hugging Face recently made the case to the White House that open-source development may be America's strongest competitive advantage in AI. This sentiment was echoed in a recent study by McKinsey, Mozilla, and the Patrick J. McGovern Foundation, which found that 75% of surveyed organizations plan to increase their use of open-source AI.

In the midst of these headline-grabbing developments, I connected with Stephen Hood, Principle Lead for Open Source AI at Mozilla, to learn more about open-source AI and Mozilla's role in this movement. Through initiatives like Robust Open Online Safety Tools (ROOST) and the Builders Accelerator, they're bringing decades of open-web expertise to ensure the future of AI is built by the people. It might be their most important battle yet.

Why Should We Care About Open-Source AI?

Stephen drew a striking parallel between today's AI landscape and a pivotal moment in tech history: the browser wars of the late 90’s and early 2000’s. "Microsoft tried to turn the web into a feature of Windows and very nearly succeeded," Stephen explains. "It was really open source that prevented that.” One company could have very likely controlled our entire online experience. Instead, open alternatives like Mozilla Firefox rose up and championed user choice — and prevented a future that might have looked something like this.

But history seems to be repeating itself with AI. "We feel a certain sense of déjà vu," said Stephen. "This is another transformative technology change that we are currently on path to have controlled by a few for-profit corporations."

Open-source AI is more than just a technical approach — it's a philosophy about who gets to shape our digital future. The collaborative nature of open-source creates a powerful innovation cycle where ideas and improvements compound. Democratization of access, as Stephen hit on above, means researchers, startups, and developers worldwide can build upon these technologies rather than just a few powerful companies.

Open source also offers tremendous educational value. People can study real systems rather than simplified examples, accelerating skill development for the next generation of AI builders. And when communities can adapt models for underrepresented languages and needs that might not be commercial priorities for large companies, AI becomes more inclusive and equitable.

The list goes on and on, but here’s the bottom line: when AI is open, the code gets better, the community gets stronger, and the technology serves more people.

“History shows us the best knowledge systems, like science and open-source software, work because many different people improve them. When we build AI the same way, we get better results, and we’re more likely to be able to break the concentration of economic power that we’re heading towards with frontier models. Diverse contributors solve problems for their own communities, creating systems that work across contexts and can distribute value broadly. Collective input isn’t just theoretical — it’s practical.” - Divya Siddarth, Executive Director of the Collective Intelligence Project

The Open Source Identity Crisis

Perhaps the most highly debated question in open-source AI right now is the most basic: what exactly is “open-source AI?”

"Traditionally, it was a little simpler to draw a distinction about what is and is not open source because it was about software," Stephen explains. "Open-source AI is different because it's not just about source code anymore, it's also about the AI models themselves." Beyond source code, there are weights, parameters, training data, and more — all important ingredients in AI systems.

As the industry grappled with these questions, established institutions stepped forward to create official guidelines. The Open Source Initiative (OSI), the organization that wrote the most widely accepted standard for open-source software, spent nearly two years developing a definition for open-source AI. They established criteria that require transparent model weights and architecture…but not open training data. Rather than full disclosure of training data, OSI requires describing the data thoroughly enough that similar datasets could be replicated. Their approach balances transparency with practical considerations like copyright and private medical data; for example, it's nearly impossible to obtain rights to massive datasets.

But some open source purists – who believe that open source should mean everything is open – weren’t happy. They argued that without open data, the "open source" label loses its meaning. This ideologically split the open source community. The Allen Institute for Artificial Intelligence (Ai2), for example, set a different benchmark for what transparency can look like — all data, code, weights, and details are freely available.

The definition isn't perfect or permanent. But at the very least, having a baseline definition gives the community something to rally around — or argue about — while the field continues its rapid evolution.

Mozilla’s Open Sourcery

Mozilla's magic lies in its transparency and collaboration. Take Robust Open Online Safety Tools (ROOST), a community effort led in partnership by Mozilla, Google, OpenAI, Project Liberty, and more. ROOST is dedicated to making the internet safer by providing free, open-source tools that help detect and prevent harmful online content. These tools are especially crucial for smaller organizations like startups, nonprofits, and governments that may not have access to advanced safety resources.

Plus, Mozilla’s Llamafile is an open-source product which compiles complex LLMs into a single file that runs directly on your computer. Perfect for organizations in low-connectivity areas or those handling sensitive data, it makes open LLMs usable on everyday consumer hardware, without any specialized knowledge or skill.

Beyond tech tools, Mozilla supports open AI development through its Builders Accelerator, which funds orgs and projects filling technical gaps in the open AI ecosystem. One standout is Ersilia, an AI-powered nonprofit using AI to accelerate biomedical research, particularly for neglected diseases in the Global South.

The Prescription for Global Health

Ersilia was founded on the belief that AI and data science should benefit all countries, not just those with well-funded research institutions. Their tool, the Ersilia Model Hub, is the largest collection of ready-to-use, open-source AI/ML models for infectious and neglected disease research. By focusing on diseases that disproportionately affect the Global South, Ersilia is helping researchers in resource-limited settings gain access to AI tools that can speed up experiments and reduce the cost of developing new drugs.

This open approach has created a flourishing ecosystem where researchers across the Global South are now fine-tuning, extending, and deploying these models in ways the founders never imagined. In one example, a researcher from South Africa built an AI model to predict antimalarial activity in molecules after attending an Ersilia workshop. When she shared it through the Ersilia Model Hub, another scientist in Cameroon discovered and applied it to his medicinal plant research — finding promising hits that advanced his work. Open-source AI enabled knowledge to flow across the continent, connecting researchers who might never have collaborated otherwise.

"The future of scientific innovation lies not in isolation but in the powerful combination of cutting-edge technology and open scientific collaboration." – Miquel Duran-Frigola, Chief Scientific Officer and Co-Founder of Ersilia, in his op-ed Community, Code, and Chemistry

What Nonprofits Can Learn from Mozilla

In his article "The Hyperspace Bypass," Stephen called on AI builders to prevent centralized control, protect privacy, augment humans rather than replace them, and fight bias — concerns that resonate deeply with nonprofits. His advice for organizations navigating this terrain is straightforward: "Decide what values matter to you. You have to actually decide where you're going to stand and what things you're going to prioritize." (Shameless plug: Fast Forward just released a Nonprofit AI Policy Builder that can help you put your values into writing.)

These choices may involve trade-offs. "You might decide, even though there’s a model that more consistently delivers the functionality you need today, that because of your concerns about user privacy, you're not going to use it," Stephen suggests. Instead, you might "commit to using local or open models... and have faith that we'll get there as an open source community in the longer term."

I’ve always admired how Mozilla, a nonprofit-backed tech company, has remained influential in rooms filled by tech giants. "It's all about the power of community," Stephen reveals. "What has always allowed Mozilla to punch above its weight has been the community of people who've shared our values and mission."

Building such a community "takes work... it requires trust that must be earned and clarity of purpose." For organizations seeking to shape AI's future, this community-centered approach offers a powerful blueprint.

Quick Bytes

APN Funding News

AI for Good and Tech to the Rescue announced the AI for Good Impact Awards Programme, which celebrates impactful AI solutions that contribute to global progress. Submissions are due May 15.
MIT Solve is still accepting solutions for their 2025 Global Challenges and Indigenous Communities Fellowship. Apply by April 17.

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AI Think We're Onto Something

Kevin Barenblat — Tue, 25 Feb 2025 17:50:25 GMT

Fast Forward just wrapped its second annual Alumni Retreat, an unconference-style gathering that trades stuffy stage talks for attendee-driven content. We welcomed 115 leaders from our portfolio organizations, alongside experts from The New York Times, Bloomberg Beta, Bridgespan, and more. During a week of frenzied headlines and predictions, this communal space felt like finding solid ground. NYT journalist Kevin Roose cut right to the heart of it: "We need tech nonprofits. We need organizations that are pursuing innovation and technological excellence without the drumbeat of shareholder value in their ears at all times."

At a gathering dedicated to solving complex challenges, one topic was at the center of many passionate discussions: AI. We dove into questions keeping nonprofit builders up at night. From ethical frameworks to favorite tools, here's what we learned about building AI for humanity — straight from the people doing the work.

+ Last month, I wrote about agentic AI with Jared Chung. When Jared presented on this technology at the Retreat, jaws were almost literally on the floor. It's crucial that nonprofits understand and help shape these emerging technologies. In a recent interview with Vox, I got to share how Digital Green is already putting these tools to work in remarkable ways.

1. How do we ensure AI is used ethically and responsibly in nonprofit work?

For nonprofits, whose currency is credibility, threading the needle between technological advancement and ethical responsibility demands extraordinary vigilance. Our founders shared their tips:

Koko founder Rob Morris recommends assembling an external board of AI experts for ethical oversight. His organization partners with Compass Ethics to provide independent review on AI, research, safety, and privacy.
AI needs guardrails, and those guardrails need guards. Natalie Dunn, Director of Product at CareerVillage.org, explained their dual approach. Their system is built with guardrails to prevent harmful or misleading content, while also using an automated system to flag conversations that might indicate self-harm or other risk factors. When such risks are detected, the system immediately brings humans into the loop.
As Empower Work’s CTO Rajiv Puranik put it, "Most people want human support, not AI support — but AI can be used to help train and assist human counselors." Empower Work has found their sweet spot with a human-in-the-loop model, placing trained volunteers between users and AI.

Takeaway: The most responsible AI isn't about replacing humans, but empowering them: creating systems with robust ethical frameworks, external expertise, and critical human intervention.

2. How should organizations evaluate and select AI models?

Building foundational models requires massive resources, making them an unrealistic option for most nonprofits. The real question is how to choose and customize existing models — and whether you need AI at all.

Oliver Hurst-Hiller, CTO & Head of Product at DonorsChoose, shared a big AI learning: small teams should favor off-the-shelf tools over building custom in-house models, whenever possible, even if the off-the-shelf tool doesn't do 100% of what you need. It's most valuable to your org to more quickly validate demand, drive social impact, and maintain the agility crucial for mission-driven work. If you find product-market fit with your AI product, you can always build something bespoke later. Then, it'll be based on an even deeper understanding of your users and scenarios.
Learning Equality stressed how critical it is to establish evaluation frameworks before diving into optimization. The team, led by Jamie Alexandre, Lauren Lichtman, and Navya Akkinepally, compared the outputs of five different models through human expert review. They’re now using that feedback to develop rigorous testing benchmarks to measure model performance objectively, ensuring they can track when changes actually improve results.
And before diving into any of these decisions about buying or customizing, consider this wisdom from an attendee: "Maybe AI isn't the best solution for the given challenge you're trying to solve. That's a successful conclusion too."

Here's the bottom line: Start by evaluating whether AI is truly the right solution for your needs. If it is, explore the spectrum of existing solutions — and crucially, establish clear evaluation frameworks and benchmarks before diving into implementation. Consider customization and fine-tuning if AI is central to your work, or stick with off-the-shelf models if it's more peripheral. Rigorous testing and performance metrics will help ensure your chosen approach delivers the intended impact.

+ In ’s Technically Optimistic, Joshua Essex, CTO of Recidiviz, presents a framework for organizations to thoughtfully evaluate generative AI adoption, especially given the current rush to implement it. His piece emphasizes that while AI offers exciting possibilities, hasty implementation without proper evaluation could harm organizations and the people they serve.

3. What AI tools are organizations loving right now?

Our founders and tech leaders shared their current favorites. Open-source AI, tools that empower non-technical staff, and AI for fundraising efficiency were major themes at the retreat.

Llamafile: Want to run AI locally without internet dependency? Mozilla’s Llamafile lets you run models on your own machine instead of relying on cloud services. This keeps sensitive data private, reduces computing costs, and ensures reliability in low-connectivity areas.
Retool: This data visualization and internal tool builder empowers non-technical team members to query databases and build dashboards using AI-assisted SQL. It's particularly valuable for tracking impact metrics and automating reporting, freeing up technical teams for dev work.
Google NotebookLM: Create custom AI chatbots based on your internal documents. Train it on past materials to generate new content faster, quickly summarize reports, and provide a cost-effective alternative to expanding research capacity.
Claude: Need help with structured writing? Claude excels at organizing content to meet specific requirements. Some Alumni Retreat attendees reported saving up to 25% of their time on applications and formal documents with Claude.
Perplexity AI: This research tool efficiently finds high-quality information and cites trustworthy sources, moving beyond generic AI-generated text. It's especially useful for legal aid, policy advocacy, and research-heavy work.
Get Time Back: Google’s Get Time Back hub hosts free AI tools that can help your organization with everything from sparking creativity to boosting productivity.
Granola: This notetaking assistant transcribes meeting notes and generates summaries and action items. Users praise its accuracy in capturing key points and next steps — particularly useful for reporting and stakeholder updates.
Browser Use: This open-source framework allows you to create agents that control web browsers autonomously. Similar to Operator, it opens up new possibilities for automating complex web-based tasks and workflows.

Quick Bytes

APN Funding News

MIT Solve opened its 2025 Global Challenges and Indigenous Communities Fellowship, calling on innovators worldwide to submit tech-driven solutions to some of the planet's most pressing and persistent problems. Prizes include The AI for Humanity Prize, open to solutions leveraging data science, AI, and/or ML to benefit humanity.
France and major funders launched Current AI, with $400M to help nonprofits and other public interest organizations access the data, tools, and computing power they need to harness AI for social good.
Public Benefit Innovation Fund, backed by the Gates Foundation, Ballmer Group, and Renaissance Philanthropy, announced a $20M AI initiative to expand access to social services.

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Agent of Change

Kevin Barenblat — Tue, 28 Jan 2025 15:30:55 GMT

CEOs, researchers, and tech journalists alike predict 2025 will be the year of AI agents. From what we're seeing in the AI-powered nonprofit space, it's hard to disagree. What is agentic AI, exactly? Think of it like AI graduating from taking orders to taking initiative. Rather than just responding to requests, agentic AI can independently pursue goals and make decisions.

To better understand this shift, I caught up with Jared Chung, founder of CareerVillage.org and author of The Agentic Era newsletter. As someone leading a nonprofit focused on the future of work, Jared has a unique perspective on where this technology might take us.

Out: Traditional AI Chatbots, In: AI Agents

Last week, OpenAI announced Operator, meaning all three of the major frontier AI model companies have released general purpose research demos of AI agents. Why is agentic AI suddenly blowing up? As Jared explains, “LLMs were the wick, and the first pile of dynamite is agents.” It's not that agentic systems are new; we've had them for years. What's changed is their recent increase in capability, reliability, and autonomy. Today's agents are leveling up in three key ways: they're tackling complex goals instead of just following scripts, executing multi-step tasks with less hand-holding, and managing a broader range of work. “These capabilities are undoubtedly being accelerated by the maturity of LLMs, and the results of huge investments into custom models purpose-built for agentic workflows,” Jared said in The Agentic Era.

“Because AI has the capacity to be agentic itself…you can leverage AI in two distinct ways. In some instances, you might want to work closely with an AI — such as when you’re learning a new language or practicing mindfulness skills. In others, such as optimizing your home’s energy consumption based on real-time energy prices, you might prefer to let an AI handle that by itself. Either way, the AI is increasing your agency, because it’s helping you take actions designed to lead to outcomes you desire.” - Reid Hoffman, Superagency, which was released today.

Who's Building?

The usual tech giants are leading the charge, each with their own flavor of AI agent. But Jared notes that the AI agents that are expected to change the fabric of our society don’t exactly exist yet. He test-drove Anthropic's general purpose AI agent and aptly called it "a glimpse into what might be possible." The agent completed his tasks, albeit with the pace and precision of an intern's first day: slow, supervised, and with a few creative interpretations along the way.

While most of us are waiting to see when these high-quality agents will become widely available, nonprofits aren't just watching from the wings. Jared's team at CareerVillage.org is taking a proactive approach: building services that don't scale. This might sound like startup heresy, but Jared's playing the long game. CareerVillage.org is developing high-touch career coaching programs that are too labor-intensive to offer widely right now — sort of like a chef perfecting recipes before writing a cookbook. When AI agents mature enough to replicate processes, they'll already have the winning playbook ready to roll out at scale.

At the same time, nonprofits are expected to do more with less. But with properly leveraged AI agents, “a 20-person nonprofit might be able to do what it used to take a 2000-person nonprofit to do,” Jared noted. Suzanne DiBianca, EVP and chief impact officer at Salesforce, agrees. In Forbes, she highlighted how nonprofits are already scaling impact with AI agents. When your mission is fighting climate change or providing disaster relief, that kind of multiplication matters.

Field Operatives

Take, for example, Digital Green. Since 2008, Digital Green has been helping farmers cultivate success from the ground up, and now agentic AI is taking their mission to new heights. In 2023, they launched Farmer.Chat, an AI-powered chatbot that quickly proved its value to farmers, even in its early pilot stage. To deepen impact, they went further to find real-time solutions to dynamic, unique farmer challenges. When weather patterns shift suddenly, new pests emerge, or diseases strike, farmers need actionable advice that's current and locally relevant. That's where agentic AI comes in.

Unlike traditional AI that relies on static information, agentic AI can actively pull data from multiple live sources — like current weather data, local market prices, and recent pest reports. When a farmer asks why their crops are struggling, Farmer.Chat can connect the dots: through a conversation with the farmer, it might notice they're using fertilizer that isn’t ideal for current soil conditions, recommend a better option, and even show them where to buy it locally at the best price. What might have taken IRL extension agents hours of research and travel is done in seconds by the AI agent. While the team continues to iterate and improve based on farmer feedback and rapid AI advancements, they're already growing a future where tech helps farmers work more efficiently and effectively.

New Year, New Agency

As we step into 2025, the rise of agentic AI presents both an opportunity and a responsibility for the social sector. "The first step," as Jared emphasizes, "is to make sure that the social impact sector is an informed and active voice in shaping how this tech develops.” Nonprofits aren't just potential users of AI agents — they're representatives of their communities and causes.

The key isn't waiting for perfect AI agents to arrive. It's preparing now so we can harness their potential for maximum social impact. Organizations like CareerVillage.org and Digital Green are showing us how to approach agents thoughtfully: start building the frameworks today that agents can power tomorrow, keep our beneficiaries' needs at the center, and imagine bigger than our current constraints. As Jared puts it, we need to "keep our eyes open" and track how agentic AI evolves, especially in the sectors that matter most to our missions. The future of AI isn't just about tech becoming more capable — it's about ensuring those capabilities serve everyone. To stay on top of the fast-moving agentic AI discussion, subscribe to Jared’s The Agentic Era newsletter.

Quick Bytes

APN Funding News

Google.org opened applications for the second cohort of the Generative AI Accelerator.
The Patrick J. McGovern Foundation announced $73.5M toward AI for Humanity.
Renaissance Philanthropy launched the AI for Math Fund, a new grant program supporting projects that apply AI and machine learning to mathematics.

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AI for Humanity's Greatest Hits

Kevin Barenblat — Wed, 18 Dec 2024 16:01:26 GMT

Spotify Wrapped has become an end-of-year staple, but let’s be honest — this year’s recap left many feeling a bit flat. So, I’ve curated a different list of hits for you. While your music roundup might have missed the beat, the AI-powered nonprofit (APN) world has been hitting all the right notes.

The numbers speak volumes: we are now tracking over 250 organizations deploying AI for good across 40+ countries. And just like any great playlist, a few breakthrough tracks stood out. Ready to press play on this year’s greatest hits?

Track 1: Adalat AI

After a decade of working with tech nonprofits, I can say this with confidence: Adalat AI's first-year impact is off the charts. What began as AI speech-to-text transcription software for Indian courtrooms has evolved into a complete justice tech stack, with live case management tools, mobile apps, and document scanning capabilities. Their software understands the nuances of legal language and local dialects, ensuring nothing gets lost in transcription.

Adalat AI started with one pilot state at the beginning of the year. They’re now in eight states covering approximately 15% of India's courtrooms — bringing hope to millions waiting for justice in a system backlogged by 50M cases — and expanding to Ghana. The tech world is taking notice too. Fast Company named them one of the four best international tech innovations of the year, and they garnered prestigious awards and fellowships globally. Adalat AI is setting a powerful precedent for the future of legal tech.

Track 2: Ersilia

In the world of drug discovery, Ersilia is creating tools everyone can sample. Their AI-powered Model Hub democratizes access to cutting-edge drug discovery tools, emphasizing the importance of in-country research. Through this platform, researchers in low-resource settings can develop treatments for neglected diseases affecting millions.

2024 brought major validation. The UN designated Ersilia's platform as a Digital Public Good. Their novel AI methods generated highly potent antimalarial drug candidates, with over 50% proving effective in laboratory studies. Co-founders Gemma Turon and Miquel Duran-Frigola published in Nature. Most recently, through the Mozilla Builders Accelerator, they developed an LLM-powered lab assistant to make their tools even more accessible. As the platform evolves, so too does its ability to empower researchers worldwide.

Track 3: Climate TRACE

Climate TRACE just turned up the volume on turning down emissions. The coalition of over 100 organizations has created Earth's most comprehensive emissions monitoring system using satellites and AI. This data empowers governments and organizations to take targeted, effective action against climate change and harmful pollution.

This year, Climate TRACE accomplished the unprecedented: creating emissions inventories for over 70K local governments worldwide. That’s every state, province, and county in the world, plus the largest 9K cities. For 80% of these places, it's their first-ever glimpse into their carbon footprint. Climate TRACE co-founders Gavin McCormick and Al Gore presented their findings at COP29, showing the world what's possible when we dream big and measure bigger.

Quick Bytes

Builder Resources

Fast Forward launched the The Playbook on AI-Powered Nonprofits! The playbook explores the vast world of AI through a nonprofit lens. Which off-the-shelf models should your organization use? How are other nonprofits using AI? What does AI even mean for nonprofits? Check it out to find the answers to all your burning nonprofit-related AI questions.
Want to avoid walking the plank of AI hype? Tech Matters CEO Jim Fruchterman's new Nonprofit AI Treasure Map is gold. His key advice: start with admin tasks, be cautious with programs, and always pilot first.
Decoded Futures' AI Adoption in Nonprofits report maps the state of AI adoption in NYC nonprofits and shares useful learnings. And, in true experiment-with-AI fashion, you can engage with the report content as a podcast, as an interactive chatbot, or even as a playlist of AI-generated music.
The Eras Tour has ended, but The Agentic Era has just begun. CareerVillage founder Jared Chung’s new newsletter explores how autonomous AI agents will reshape the workforce. Understanding this next wave of AI innovation could reshape how you serve your communities. Subscribe to The Agentic Era here.

APN Funding News

Tech to the Rescue has opened applications for their latest AI for Changemakers cohort, focusing specifically on education nonprofits.
Dell is accepting applications to their AI Readiness for Nonprofits Pro Bono Consulting Workshop. The workshop aims to empower nonprofits to adopt AI solutions.
AWS committed $100M to tech nonprofits helping underserved students gain skills in AI, cloud computing, literacy, and more.

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Are AI and Democracy on the Same Ticket?

Kevin Barenblat — Thu, 17 Oct 2024 17:09:52 GMT

It’s the biggest election year in human history. Half of the world's population — 3.7 billion people — has the opportunity to head to the polls across 72 countries. With our own election right around the corner, it's the perfect time to dig into the intersection of AI, nonprofits, and democracy. And I knew I couldn't do it alone.

I elected to bring in a friend who's been navigating this intersection for years: Aria Finger. She's a prime candidate for this discussion. Aria led DoSomething.org for over a decade, mobilizing millions of young people to take action and registering over 350,000 young voters. Currently, she serves as Chief of Staff for Reid Hoffman, the co-founder of LinkedIn and Inflection AI. She also co-hosts Possible, a podcast that explores the bright side of AI. She's seen firsthand how tech can amplify voices, streamline civic processes, and, yes, sometimes complicate our democratic landscape.

Kevin Barenblat: Hi Aria! Thanks for helping us navigate this strange new world. Your career spans leadership roles in tech-driven social impact. Given your expertise and strong focus on democracy, how do you view the intersection of AI and our democratic processes?

Aria Finger: In general, I am very excited about the prospect of AI being a force for good in so many sectors — from healthcare to education to…yes…even democracy. The way I see it, part of people's faith in democracy stems from believing their elected leaders can actually improve their lives. AI has enormous potential to enhance government effectiveness, from custom chatbots for tax assistance to streamlined Medicare procedures to improved communications with local public schools. However, we can't ignore the short-term risks. AI can increase misinformation and intensify the erosion of trust in institutions like democracy that started long before LLMs came on the scene.

KB: You’re right — AI presents some potential risks to our democratic processes. How can we best counter these risks as we approach the 2024 election and beyond?

AF: There are many, many things that need to be done, and I certainly don't have all the answers. Here's the thing: many of these threats to democracy existed before AI. But AI does supercharge people's ability to make content, so it can amplify some of our existing problems.

Platforms need to step up their efforts to combat misinformation, AI-generated or otherwise. The good news is that while AI-created photos are quite convincing now, deepfake videos aren't yet sophisticated enough to fool most people. The real challenge is twofold: stopping the spread of false information and rebuilding trust in our democratic institutions. As AI ramps up content creation, we need to focus equally on helping people spot misinformation and strengthening their faith in legitimate sources of information.

KB: It's clear we've got our work cut out for us. Now, since this is the AI for Humanity newsletter, I'm curious — what's an AI-powered nonprofit that really excites you?

AF: There are so many! I absolutely can't choose just one (and frankly, Fast Forward supports so many amazing ones that there are just too many to list). Earth Species Project is an incredible nonprofit using AI to decode animal communication. I love Recidiviz and their work to use tech, data, and now AI to sustainably reduce the prison population. Opportunity@Work is moving us toward a skills-based economy, which will be especially important in our AI future, where skills should be paramount and degrees shouldn't unnecessarily hold people back.

KB: Borrowing a question you ask at the end of every Possible episode: Where do you see progress outside of your industry that inspires you?

AF: I can't stop learning and reading about all the amazing innovations AI will unlock in healthcare, biology, and drug discovery. What's possible now and in the near future probably sounded like science fiction not long ago. I'm excited about the potential to cure various forms of cancer and neglected tropical diseases, provide more accurate medical diagnoses, reduce healthcare costs, improve bedside manner, free up doctors and nurses from unnecessary paperwork, and so much more.

KB: Thank you, Aria, for illuminating AI's role in our democracy and future. Readers, to explore the bright side of AI, hit play on Possible. And to create a brighter future, hit the polls.

Quick Bytes

APN Funding News

The GitLab Foundation, Ballmer Group, and OpenAI have partnered to continue and expand the AI for Economic Opportunity Fund. The organizations will work together to provide millions in funding, mentorship, and technical support to up to 14 demonstration projects.
Mozilla announced their inaugural Mozilla Builders Accelerator cohort. The program funds and supports impactful projects that are vital to the open source AI ecosystem — including Fast Forward alum Ersilia’s Model Hub.
Salesforce awarded $23M in new grants to global education nonprofits and U.S. school districts to equip students with the skills needed for future success. Grantees included CareerVillage, aiEDU, Fast Forward, and other nonprofits focused on AI skilling and literacy.

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Assembly Required

Kevin Barenblat — Thu, 19 Sep 2024 15:30:50 GMT

Nonprofits are at a crossroads: embrace AI or risk falling behind. But for many organizations, adopting AI feels like assembling IKEA furniture — you know it's a great solution, but where are the dang instructions?

Here's the good news: you don't need to be a tech wizard to harness the power of AI. Existing AI tools can help every nonprofit do more with less, freeing up time for what really matters — your mission. At Fast Forward, we are continually testing a wide array of tools to find what works for us. (Want to try a fun one? Turn your existing content into a podcast, like we did to this newsletter with the help of Google’s NotebookLM. Be surprised here.)

We've compiled some useful resources to help you get started. Consider it the missing manual for your nonprofit AI adoption journey.

Survey Says: Assessing Readiness

Before diving into the AI deep end, it's helpful to know where you stand. Enter GivingTuesday's new AI Readiness and Adoption in the Nonprofit Sector survey. The report maps out the current landscape, showing how organizations like yours are navigating the AI waters and where nonprofits fall on the adoption spectrum. Filled with actionable insights and resources, this survey is your first step in charting an AI course that's right for your mission.

+ TLDR: Don’t underestimate nonprofits when it comes to tech adoption. Twilio.org’s 2024 State of Nonprofit Digital Engagement Report found that 58% of nonprofits use AI in their digital communications, surpassing the 47% of B2C businesses.

“We should be thinking about back office efficiency. I think it’s super un-sexy to say that, but if we can unlock time, we can effectively unlock capital in a lot of ways … If we can make our organizations a single percentage point more efficient using these generative tools, I think that could be really beneficial.”

- Raffi Krikorian, CTO of Emerson Collective, at the Federal Reserve Bank of San Francisco’s GenAI for Economic Opportunity

Covering Your Ethical Bases

Learning new tools is one thing, but implementing AI ethically? That's a whole other ball game. We partnered with Jared Chung, founder of CareerVillage, for our blog post on responsible AI implementation. We asked him heavy hitters, like “Who is responsible when an AI system makes a mistake?” and “How can you ensure that AI doesn’t reinforce existing biases?” We also shared our favorite ways to use AI to boost our work. Balancing powerful tools with thoughtful implementation is how you'll truly knock it out of the park.

+ Remember those AI questions for grantmakers? Plot twist: nonprofits, they're for you too. Ask yourselves these questions to ensure thoughtful implementation and challenge your own AI plans.

“AI presents a lot of opportunities to automate repetitive or time-consuming tasks and free up time for you to focus on more creative or high-value work. The important thing is that we take the energy we’ve put into developing that groundbreaking technology and match it with efforts to ensure those breakthroughs are being used for good and benefiting communities in need.”

- Brigitte Hoyer Gosselink, Director of Product Impact at Google.org, in Authority Magazine

The Hidden Gem(ini) of Time-Saving Tools

AI-powered nonprofits aren’t building a time machine (yet), but Google.org's Get Time Back campaign might be the next best thing. Unveiled at Google.org’s first-ever Impact Summit earlier this month, the resource hub instructs nonprofits on how to use their free AI tools. My favorite part? The Gemini prompt library tailored specifically to nonprofit needs. It's packed with ready-to-use prompts for tasks like grant writing, content creation, and volunteer management. I recommend you prompt-ly check it out.

+ Looking for additional resources? Check out our AI for Humanity Resource Hub for recommended reads, listens, and watches to get up to speed on all things AI. NTEN’s Artificial Intelligence Framework includes helpful guidelines for ethical implementation. TechSoup’s AI Learning Center has an array of webinars, videos, and guides.

Quick Bytes

APN Funding News

Kyndryl Foundation invites proposals from organizations dedicated to cybersecurity and AI skills development, with a focus on job placement for underrepresented learners and job seekers. Apply by October 11.
The Google.org Accelerator: Generative AI is back for round two. Submit the interest form to stay up-to-date on program details and application timing.
The Climate Change AI Innovation Grants program is currently accepting applications for projects using AI and machine learning to tackle climate change challenges.

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Make It Make Cents

Kevin Barenblat — Thu, 22 Aug 2024 16:30:26 GMT

In 2011, a song on the Billboard Hot 100 claimed, “It's not about the money, money, money.” But in 2024, it seems we’re singing a different tune. As we find ourselves in the midst of another election season, Americans are voting with their wallets. A recent survey showed that the most important issue for 25% of Americans was inflation and prices, and a further 10% were most concerned about jobs and the economy.

As candidates pitch their economic plans, AI-powered nonprofits (APNs) are quietly forging new pathways to prosperity around the globe. How? Let’s dive in.

(I'll be further exploring the intersection of AI and economic opportunity in a few weeks at an event hosted by the Federal Reserve Bank of San Francisco. from Emerson Collective, Nick Arevalo from Tipping Point, Lili Gangas from Kapor Foundation, and I are discussing how philanthropy and nonprofit organizations are navigating GenAI's role in shaping economic opportunities for low-income communities. Join us virtually for the GenAI for Economic Opportunity panel.)

Data to Dollars

Picture this: A teacher in Karnataka, India earns her monthly salary in just six hours. A college student outearns his field labor wages while sitting at home. The secret? Their smartphones, mother tongues, and AI. Karya pays rural Indians to teach AI their native languages through simple tasks like reading aloud or transcribing text. At $5 per hour – 20x the local minimum wage – it's redefining ethical AI data work. Most recently, Karya used Gemini to create tools that help partners worldwide set up similar projects in local languages. In the language of progress, Karya's proving fluency in both tech and fairness.

+ The verdict is in: Karya and Adalat AI are raising the bar in legal tech. These Fast Forward alums are partnering to develop AI training data specifically tailored for legal settings in Indian accents and languages. By merging Adalat AI's legal tech savvy with Karya's grassroots data collection, they're setting a new precedent for accessible legal AI.

“I believe our civilization stands on the cusp of a technological revolution with the power to reshape life as we know it. To ignore the millennia of human struggle that serves as our society’s foundation, however—to merely ‘disrupt,’ with the blitheness that has accompanied so much of this century’s innovation—would be an intolerable mistake. This revolution must build on that foundation, faithfully. It must respect the collective dignity of a global community.” - Dr. Fei-Fei Li, in her memoir The Worlds I See

It Takes a CareerVillage

The future of work is changing. Shouldn't career guidance change, too? Enter Coach, CareerVillage's AI-powered solution to democratize career development. Due to systemic underinvestment in career preparation resources nationwide, personalized guidance is a luxury many can't access. The chat-based platform aims to fill the gap, offering 24/7 tailored support from resume writing to job hunting. Coach isn't just about finding jobs — it's about empowering individuals to make informed decisions about their futures, a crucial step in breaking the cycle of poverty.

+ While CareerVillage guides U.S. career seekers, Tabiya charts a global course for youth employment. This nonprofit is building an open-source AI tool called Compass to help young job seekers in low- and middle-income countries identify their skills and match with suitable jobs. By emphasizing skills over credentials, Tabiya is using tech to create opportunities for talent to thrive regardless of background.

“The idea that technology alone can solve social and political problems is a dangerous delusion. But the idea that they can be solved without technology is also wrongheaded.” - Mustafa Suleyman, The Coming Wave

Engineering Equitable Futures in Tech

CodePath is investing in tech's future with AI as a prime asset. The organization is on a mission to create the most diverse generation of engineers, CTOs, and future founders. CodePath offers students cutting-edge computer science courses, career support, and job placement at no cost through partnerships with top universities and tech companies. Its adaptive learning courses personalize the classroom experience, and its AI-powered chatbot for career readiness ensures graduates are ready to hit the ground coding. With an 80% boost in job placements, it's clear: when it comes to reprogramming the tech talent pipeline, CodePath has cracked the code.

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APN Funding News

Fast Forward's 2025 Startup Accelerator application is live! Selected orgs gain 12 weeks of mentorship, a tight-knit community, and $25K. Last year saw a 6x boom in AI-powered nonprofit applicants. Know one that should apply? Send the application their way.
Future of Life Institute is offering up to $4M grants for AI projects focused on developing safe, distributed AI systems that empower humanity to use AI to solve the most pressing problems of our time.
Meta is accepting proposals from organizations worldwide with an idea for how to use Llama 3.1 to address social challenges in their communities. Selected recipients will receive up to $500K.

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I am living and breathing AI for humanity these days. If you are too, let’s talk!

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A Landscape of Good

Kevin Barenblat — Thu, 18 Jul 2024 16:41:22 GMT

I originally posted these thoughts in Stanford Social Innovation Review with Google.org's Brigitte Hoyer Gosselink.

If you're a regular reader of this newsletter, you know it’s all about spotlighting nonprofits using AI for social good. Each month, I share exciting stories (and the occasional pun) about AI-powered nonprofit builders. But lately, my team and I have noticed something bigger growing. We're not just seeing isolated peaks of innovation; we're witnessing the formation of a vast new landscape of AI-powered social impact. We found ourselves wondering how all these solutions fit together in this terrain. Our goal was to understand not just what kind of AI tools nonprofits were using, but how they were deploying them to drive impact. While plenty of private sector AI landscapes exist, the nonprofit sector has remained uncharted territory. So, we set out to map this exciting new ground ourselves.

The result is a growing AI-powered nonprofit (APN) landscape. After diving into nearly 100 use cases, picking the brains of tech-for-good leaders, and chatting with dozens of builders, we've identified four main categories of nonprofit AI use for impact: Advising, Structuring Data, Translating, and Platform. Each category contains sub-branches, which you can explore in our Stanford Social Innovation Review (SSIR) series. We also spoke with The Chronicle of Philanthropy about it. Over the next month, we'll publish three more SSIR articles on APNs’ impact in climate, health, and education. But for now, let's tour these categories:

Advising

This category is all about AI that scales human-to-human experiences. It’s the friendly, user-facing AI we chat with daily — think Gemini and ChatGPT. It's like having a wise mentor in your pocket, minus the lint. What sets AI-powered nonprofits apart in this space is their focus on creating products for highly specific, often overlooked audiences.

+ Joy Education exemplifies this in their work reducing inequities in literacy support for low-income communities. Young readers read to an AI-enabled friend for three minutes. The AI diagnoses the reader’s areas for growth and then provides teachers and parents with a customized learning plan.

Structuring Data

AI solutions in this category supercharge what humans can do with data. Before AI tools were common, we needed a data scientist to unravel big, messy datasets. We used to have to speak binary. Now, thanks to generative AI, machines respond to our language. These accessible AI tools mean that even those without technical expertise can make sense of — and interact with — data.

+ Reboot Rx uses AI to sort through hundreds of thousands of research papers to identify generic drugs suitable for cancer treatment. It would take years to review the thousands of published studies, but their tech reduces this time to a matter of weeks.

Translating

AI in this category is used to…translate! Quality translation is key to expanding access. We’re seeing AI for translation deployed across sectors, unlocking opportunities all over the globe. And it’s more than just translating language. With generative AI, nonprofits can bridge contexts too. This especially matters for nonprofits that work across communities, cultures — and even species.

+ Earth Species Project uses deep learning to visualize semantic representations of language to unlock communication with our non-human counterparts. It has already developed AI models that emulate a variety of species, with the aim of having “conversations” with animals.

Platform

Think of this as the "teach a person to fish" approach to AI. This type of AI empowers more nonprofits to deploy their own AI tools. Rather than delivering pre-packaged solutions, these nonprofits enable people to tailor tech, like customizable chatbots or open-source platforms, to meet their own needs.

+ Take Playlab. Educators have historically relied on others to build tools for them. Playlab enables teachers to create, remix, and share their own AI edtech tools.

Have thoughts on the landscape? Know an AI-powered nonprofit that's flying under the radar? Give us a shout!

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APN Funding News

Data.org launched its Artificial Intelligence to Accelerate Inclusion Challenge (AI2AI Challenge), a global call for existing innovative AI solutions seeking scale to accelerate inclusion and economic empowerment.
Dell Technologies announced a special Pro Bono Consulting Workshop that aims to empower nonprofit organizations to adopt AI solutions.
Nonprofits creating climate solutions can express interest in the upcoming Salesforce Accelerator – AI for Impact cohort.

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I am living and breathing AI for humanity these days. If you are too, let’s talk!

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GPAs & GPTs

Kevin Barenblat — Thu, 20 Jun 2024 16:53:04 GMT

From the moment I saw the clever title, I knew I was going to enjoy reading Sal Khan's new book Brave New Words. Inside, Sal, founder of Khan Academy, makes a strong case for leveraging AI to help learners learn and teachers teach. We're short about 300,000 teachers in the U.S., with 90% of school districts reporting teacher shortages. His book brims with real-world examples illustrating how AI can improve education across subjects. The biggest surprise to me was where he said AI is showing the biggest gains — not in math or science, but in student confidence. I'm excited to shine a light on more AI-powered nonprofits (APNs) around the world that are elevating education for everyone.

I’m Just a Quill

“We got about as close to making grammar cool as we probably ever will,” said a middle school teacher in a recent The Chronicle of Philanthropy feature. No, they weren’t talking about Schoolhouse Rock; they were raving about Quill.org. Quill offers free literacy activities to boost reading comprehension, writing, and language skills for students from elementary to high school. As one of the earliest APNs, Quill has been perfecting predictive AI models since 2019. Its venture into generative AI is special for a couple of reasons. First, Quill’s AI isn’t just smart — it’s painstakingly trained, with custom rubrics showcasing up to 100 examples of good and bad writing for each prompt. Second, Quill works with hundreds of teachers to vet every learning activity, reiterating that AI is here to support teachers, not replace them. With such meticulous efforts, it's safe to say Quill is "write" on track to revolutionize literacy education.

+ Lenny Learning tackles a different but equally important kind of curriculum: student mental health. The AI-powered tool helps schools assess student needs and create custom lessons based on clinically-informed content. Lenny saves teachers up to 5 hours of lesson planning every week!

+ The newly released Coach is preparing learners for life outside the classroom. Earlier this week, CareerVillage released its free Coach learner experience. The platform harnesses generative AI to provide users with help drafting résumés and cover letters, exploring careers, staging mock interviews, and more.

“Let's use AI to create a new golden age for humanity, a time that will make today look like a dark age. From my vantage point, nothing could be more inspiring and important than that." - Sal Khan, Brave New Words

Back(pack) to the Future

Khan Academy has done more than inspire students globally — it’s also inspired new nonprofits. Jamie Alexandre was an intern at Khan Academy when he asked himself: how could we deliver Khan Academy-level education to the then 4 billion people still offline? And thus, Learning Equality was born. Today, its AI-powered platform Kolibri is like a digital backpack full of top-tier educational resources for remote communities. Kolibri’s special power is aligning its vast library of educational content with regional curriculum standards at a fraction of the time and cost. A recent example: in a remote Ugandan region, Kolibri classified 12,000 learning resources and aligned them to 2,000 local educational goals. This turned months of manual work into mere days. With Learning Equality, teachers get an A+ for alignment!

+ Teaching by example: Khan Academy sparked Learning Equality, and Learning Equality sparked O-Lab. Tania Rosas, another Fast Forward Startup Accelerator alum, founded O-Lab after her great experience using Kolibri as a teacher in Colombia.

“To realize AI's potential in global education, large-scale behavioral change is necessary. This requires deep partnerships with education systems; otherwise, the impact of AI will be limited to a minority of learners who are both able and willing to use it independently.” - Abdulhamid Haidar, Founder of Darsel

A-B-C, It’s Easy as…1’s and 0’s?

Learning the alphabet at an early age isn’t always a given, and Rocket Learning is on a mission to change that. Rocket Learning is building the largest repository of play-based learning activities and utilizing AI-powered content to educate millions of preschool-aged children in India. It does this in partnership with Anganwadi centers — government-sponsored community centers that are a lifeline for families. The curriculum is delivered via WhatsApp to both Anganwadi workers and parents, making it a powerful tool for reducing gaps in early childhood education. Rocket Learning truly understood the assignment.

+ Family engagement in education is important. TalkingPoints is built on this fact. Similar to Rocket Learning, TalkingPoints is building a feature that generates personalized activities to help families engage their children at home around what they are learning in school. Founder Heejae Lim joined the Overdeck Family Foundation’s Spotlight On Growth podcast to discuss how they’re tapping into the power of AI to personalize communication.

+ Pop quiz! How are APNs accelerating progress on the SDGs? Google.org’s Research Brief highlights APNs and hyperlocal initiatives that are moving us forward on SDGs, including SDG 4 (Quality Education).

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APN Funding News

KPMG launched its "AI Impact Initiative” to bring AI to nonprofits. The efforts include funding, skills-based volunteering, and pro-bono work in the nonprofit sector.
Kapor Foundation, Omidyar Network, and the San Francisco Foundation committed $25M to accelerate responsible, equitable, and ethical AI in California.
The Bezos Earth Fund opened applications for its AI for Climate and Nature Grand Challenge, announcing up to $100 million in grants.

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I am living and breathing AI for humanity these days. If you are too, let’s talk!

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AI-natomy 101

Kevin Barenblat — Thu, 16 May 2024 19:14:41 GMT

Lately, my inbox has been a trove of breakthroughs in AI for healthcare. We’re seeing AI-powered advances for Parkinson’s disease, Alzheimer’s disease, ophthalmological conditions, mental illness – even triaging emergency room patients.

These leaps hint at a reality where healthcare is not only better but also more accessible. Eager to explore deeper, I connected with a few doctors-turned-founders of healthcare AI-powered nonprofits in our network and took their temperature on the state of medical AI. Their responses shed light on real-world applications and challenges. Ready to feast your A-eyes on the future?

The Remedy for the Data Divide

Ersilia was founded on the belief that 1) data science offers an unprecedented opportunity in biomedical research, and 2) all countries must benefit from it. Their tool, Ersilia Model Hub, is the largest collection of ready-to-use AI/ML models for infectious and neglected disease research, especially in the Global South. A recent Nature article co-authored by Ersilia's founders highlights a glaring data issue: most clinical trials have taken place in the Global North, creating a critical gap in our understanding of African genetics. Use of AI can indeed bridge this gap. However, the real focus should be on building the infrastructure, skills, and policies that empower local scientists to lead this transformation. When it comes to research, homegrown data is the best medicine.

+ The scarcity of unbiased, labeled data in low- and middle-income areas is one of the biggest topics in AI right now. There are many great resources and initiatives, including Tech Matters’ Better Deal for Data and Lacuna Fund.

"We know people are proximate to their problems, and for some reason, we’re okay with it. But we also know that we don’t do very much to help them be proximate to their solutions." - Vilas Dhar, President, Patrick J. McGovern Foundation

Swapping the Sterile for the Sincere

At the heart of HERA Digital Health’s current efforts is their Predictive Care Navigator, an AI-powered chatbot to converse with refugee women about their sexual and reproductive health needs. Named Amti, which means “aunty” in Arabic, HERA's chatbot is conversational, caring, and culturally appropriate — something that is missing in many healthcare chatbots. The research-backed tool integrates into WhatsApp, meeting users where they are and making it highly cost effective. Plus, the software engineer who coded and trained Amti is a refugee themself. HERA’s blend of medical accuracy, cultural empathy, and lived experience ensures every conversation feels more heart-to-heart than heart-to-hard drive.

"Medicine used to be the art of intuition, but now it's the science of information." - Eric Topol, Deep Medicine: How Artificial Intelligence Can Make Healthcare Human Again

Healthcare Workers’ Right-hand Bot

Intelehealth is an open-source telemedicine platform connecting patients and frontline health providers in rural communities with remote doctors to deliver affordable healthcare. Powered by the AI digital assistant Ayu, the platform uses evidence-based protocols to improve patient outcomes. Ayu helps shift tasks from doctors to frontline health workers by recording patient history in the local language, translating it for the provider, and compiling it into a clinical summary. It also generates likely diagnoses, treatment pathways, and triage decisions, then translates this information back to the patient. Built on GPT-4 Turbo, Ayu has shown high diagnostic accuracy in controlled settings. Intelehealth is now refining Ayu to ensure its effectiveness in diverse environments. High-quality, affordable medical care for rural populations is just what the doctor ordered.

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APN Funding News

Google.org committed $75 million to the AI Opportunity Fund, which will make grants to workforce development and education orgs to provide skills training in AI to 1M Americans.
Salesforce launched its Salesforce Accelerator – AI for Impact, which focuses on climate action, and welcomed a cohort of 5 nonprofits.
Tech to the Rescue opened registration for AI for Changemakers, a global accelerator program for AI innovators and leading nonprofit organizations.

Let’s Talk

I am living and breathing AI for humanity these days. If you are too, let’s talk!

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AI for Humanity

(Ch)AI for Humanity

1. India’s Running Start

2. A Pressure Test for Inclusion

3. Built for the People, By the People

A Funding Ecosystem Takes Root

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Are You a Renter or an Owner?

Whose Side Is Your Tech On?

Build for the Margins

Pragmatic, Not Purist

Setting the Pace

Jared Chung, Founder, CareerVillage.org

Afua Bruce, Co-Author, The Tech That Comes Next and Principal, ANB Advisory Group

Raffi Krikorian, Chief Technology Officer, Mozilla

Vanessa Parli, Managing Director of Programs and External Engagement, Stanford HAI

Rey Faustino, Founder and CEO, One Degree

Gemma Turon and Miquel Duran-Frigola, Co-Founders, Ersilia

Scott Kleper, AI Advisor, Fast Forward

Caroline Spears, Executive Director, Climate Cabinet

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The AI for Humanity Gift Guide

$3 - Connect a family to food resources for a full year

$5 - Deliver proven mental-health support to one young person exactly when it matters

$10 - Give 10 students a personal math tutor for a year

$30 - Enable 30 hours of AI-powered literacy tutoring

$57 - Support one worker crisis conversation

$317 - Help restore a vote

$5,000 - Cover trucking school tuition for a returning citizen

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A Few of My Favorite 2025 Things

APN Opportunities and Funding News

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Striking a Chord

Prelude

Track #1

“To have machines do what humans can already do is not nearly as interesting as having them do what we could never do.“ - Baratunde Thurston

Track #2

“We all face the same choice over and over again, and it’s between the hard right and the easy wrong.” - Al Gore

Track #3

“There’s absolutely misuse of these technologies. But there’s also missed use.” - Shannon Farley

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84% of AI-Powered Nonprofits Agree on One Thing

Funders: Support the Messy Middle

Nonprofits: Starting Small, Reaching Big

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Sigmund Droid

Cultural Intelligence Agency

From Feedback to Frameworks

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Prime Time

Bayes Impact

[Pitch]

Collective Intelligence Project

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Materiom

[Pitch]

Scrutinize

[Pitch]

VectorCam