Carolyn Woodard covers four AI stories with real implications for nonprofits this week, starting with Meta CEO Mark Zuckerberg's sprawling new manifesto on open source AI and the release of Muse Glimmer, a lightweight model anyone can run locally. Carolyn touches on why this matters for budget conscious nonprofits weighing vendor values, and why open source still requires more technical capacity than most organizations currently have on hand.

From there, Carolyn digs into a story about Alaska Airlines using an AI tool called Flyways to suggest more efficient flight routes, saving fuel while keeping a human dispatcher in the loop on every final call. She uses it to revisit a three filter framework for thinking through AI's environmental tradeoffs: whether the benefit you are getting is worth the cost. It is a useful model for any nonprofit trying to weigh AI's real impact rather than just reacting for or against it.

Next, a refresher on agentic AI, prompted by a listener question after last week's episode. Carolyn breaks down the difference between old school recommendation engines, generative AI, and agents that can take multi step actions on their own, plus what those tools are actually called inside Microsoft, Google, OpenAI, and Anthropic products. She also unpacks two recent incidents where AI agents from OpenAI and Anthropic got loose due to human error, and what that means for how carefully nonprofits should scope permissions before saying yes to an agent, and urges you to check with your policy and your IT team if you are unsure about the parameters of anything you are allowing an AI tool to do.

Finally, Carolyn pushes back a little on the popular advice that everyone should write their own first draft before bringing in AI. She argues it really depends on your task, your learning style, and how you think best.

Resources Mentioned:

• Zuckerberg manifesto pushes an open source approach on AI as Meta releases its latest model – AP via ABC News – https://abcnews.com/Technology/wireStory/zuckerberg-manifesto-pushes-open-source-approach-ai-meta-135519669
• The FAA Wants to Reboot the Nation's Airspace. This Airline Shows How It Might Work – NPR – https://www.npr.org/2026/08/10/nx-s1-5872752/airspace-reboot-alaska-airlines-flyways
• OpenAI's Hacking Debacle Was a Human Mistake – WIRED – https://www.wired.com/story/openais-hacking-debacle-was-a-human-mistake/
• OpenAI, Anthropic AI Hacking Sprees Illegal? – WIRED – https://www.wired.com/story/openai-anthropic-ai-hacking-sprees-illegal/
• Should You Really Use AI to Write That First Draft? (And What to Do Instead) – TechSoup – https://blog.techsoup.org/en-us/posts/should-you-really-use-ai-to-write-that-first-draft-and-what-to-do-instead

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Carolyn Woodard explores why statistical analysis and evaluations are never neutral with Heather Krause, mathematical statistician and founder of We All Count.

Heather built her career doing statistical consulting, evaluation, and causal analysis in the global south, work that eventually convinced her that the widespread belief in value neutral quantitative analysis is a myth. In this conversation, she and Carolyn dig into why every statistical task, even something as simple as calculating an average, is really a series of choices, and why those choices are never neutral.

Using a deceptively simple classroom size example, Heather shows how the same data can produce two different, equally correct answers depending on whose experience you are measuring for, and why that matters far beyond the classroom. She and Carolyn also talk about a dairy cooperative project in Bangladesh, the discomfort people feel when the myth of neutrality gets challenged, and why transparency, not dumbed down science, is the real fix. 

The conversation wraps with a candid look at how AI fits into all of this: it is not value neutral either, and understanding its hidden choices may be one of the most useful data literacy skills nonprofits can build right now.

Heather and Carolyn discuss:

• Why statistics and the application of statistics are not the same thing, and how every calculation, like choosing an average's denominator, embeds a value judgment and takes a perspective.
• A classroom size example showing how measuring from a teacher's perspective versus a student's perspective produces two different, defensible answers, and why the choice matters.
• A dairy cooperative project in Bangladesh that illustrates how whose worldview gets built into a statistical model shapes what the evidence ends up being used to say.
• Why transparency about the assumptions behind a data project, explained in plain language, builds more trustworthy evidence than technical jargon or hedged science.
• Why AI models are not value neutral, how they can hide the choices they make, and how nonprofits might use AI to build more transparent, equitable data practices.

Resources Mentioned:

• We All Count - Heather Krause - https://weallcount.com/
• Bangladesh Women Milking Example and Equity in Evaluations - YouTube - https://youtu.be/8gYtTYc2M0U?si=AryCMmUsNTYq7YoW

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Carolyn Woodard covers why deliberate, thoughtful implementation is actually your nonprofit's competitive advantage, not a liability.

The commercial AI sector is in a "move fast and break things" sprint. Tech companies are pouring billions into AI, racing to scale, pushing toward the edge of the market. Today's AI race feels similar. Nonprofits tend to think differently. You ask hard questions. You think about theory of change, root causes, impacts on your communities, unforeseen consequences, and alignment with your values. You don't adopt trends just because everyone else is.

Concerned about climate impacts of your AI use? Carolyn covers her recent blog post on three filters to use as you make daily decisions about using AI: What are you using the AI to do (text is lighter than producing video), where are you (how stressed is your grid and your water supply in your location), and what are the benefits to consider as you consider the environmental impacts? 

Carolyn also walks through a practical framework for any AI adoption decision: Do you need it? Can you contain it? Do you understand what it might do? If you can't confidently answer yes to all three, then waiting isn't falling behind—it's being strategic.

Key Takeaways:

Nonprofit instincts to think deeply about change, impact, and ethics are strategically prescient, not conservative.

When commercial AI implementations encounter consequences, organizations with inclusive adoption processes and clear policies will have a genuine competitive advantage.

AI agents represent a new risk category; don't create an agent just because the tool offers the option. Understand what you're deploying.

Experimentation is valuable for nonprofits, but human oversight and clear policies are essential, especially with agentic systems.

Resources Mentioned:

What Is an AI Agent?

An AI agent is a program designed to operate independently toward a specific goal, rather than simply responding to individual prompts. Unlike a chatbot that waits for you to ask questions, an agent reasons about how to achieve its objective and takes actions on its own—such as reading files, sending emails, or accessing systems. You can program checkpoints where the agent asks for your permission before taking certain actions, but the agent itself decides the steps and sequences needed to reach its goal. This autonomy is what makes agents powerful for automating complex tasks, but it's also why they require careful oversight: because they're goal-directed and adaptive, they may find unexpected paths to achieve their objectives, which can create risks if not properly contained and monitored.

What Is an AI Agent? – Build Consulting – https://buildconsulting.com/resources/podcast-rise-of-the-ai-agents/

Three Filters for Values-Aligned AI Decision-Making – Community IT Innovators – https://communityit.com/blog-values-aligned-ai-decision-making/

Claude Cybersecurity Incidents Disclosure – Anthropic – https://www.anthropic.com/news/investigating-incidents-cybersecurity-evals

Fortune (mainstream): https://fortune.com/2026/07/31/anthropic-claude-escaped-test-hacked-three-companies-openai/ (paywall)

TechCrunch (tech-focused): https://techcrunch.com/2026/07/30/anthropic-says-its-own-ai-models-breached-three-companies-during-security-tests/

Open AI Cybersecurity Incidents Disclosure - OpenAI - https://openai.com/index/hugging-face-model-evaluation-security-incident/ 

CNN (mainstream reporting): https://www.cnn.com/2026/07/22/tech/openai-hugging-face-ai-cybersecurity

Malwarebytes (technical deep-dive): https://www.malwarebytes.com/blog/news/2026/07/openais-agent-escaped-its-sandbox-during-a-security-test

Women in Climate Tech Cohort – Climate Collective – https://climate-collective.circle.so/cliematecollective

Electricity Maps https://app.electricitymaps.com/map/live/fifteen_minutes

Nonprofit IT Management Community – Reddit – https://www.reddit.com/r/nonprofitITmanagement/

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Carolyn Woodard talks with Joe Robbins, Chief Product Officer at Food Rescue US, about a real-world AI project built from the ground up: a predictive model that flags volunteer pickups at high risk of a last-minute cancellation.

Food Rescue US connects volunteers with food donors and receiving agencies through an app similar to a delivery service, coordinating about 150,000 pickups a year across 27 states. When a volunteer cancels within 24 hours of a pickup, site coordinators scramble to cover it or risk the relationship with the donor. 

Joe and his team partnered with a supply chain researcher at Michigan State University to build an algorithm that predicts cancellation risk and flags pickups at high-risk for cancellation. Rather than automating any decisions outright, the AI triggers an alert to the site coordinator, who checks with the volunteer about confirming the pickup or cancelling early. During the pilot and rollout the AI tool  flagged thousands of rescues that would have been last minute cancellations. 

Joe shares the practical lessons from a project that took a full year to scope, pilot, and improve: why good data capture has to come before any AI project, how a tightly scoped pilot funded through a grant reduced risk, and why keeping a human in the loop kept the tool trustworthy for staff and volunteers alike. 

He also offers a framework for nonprofits without an in-house AI researcher or technical staff to get started using AI for more than productivity tools.

Joe and Carolyn discuss:

• How a predictive model helps Food Rescue US flag volunteer pickups at high risk of last-minute cancellation, giving site coordinators three to eight days of notice instead of a same-day scramble.
• Why the project deliberately keeps a human in the loop: the algorithm surfaces a risk score, but a site coordinator decides whether to act on it.
• Why clean, well-understood data capture has to happen before any AI project, and how to audit what data your organization already has.
• How building a pilot into a grant proposal made it easier to test small before rolling out more broadly.
• A framework for nonprofits without an in-house AI researcher: start with free assistant tools, learn what context AI needs to be useful, then look for a tightly scoped, well-documented problem to solve where you already have the data to use.
• What's next for Food Rescue US: using AI to take logistical pressure off site coordinators so they can focus on building community relationships.

Resources Mentioned:

• Food Rescue US: https://foodrescue.us
• Tech Soup AI Impact Hour interview with Joe: https://engage.techsoup.org/c/upcoming-events/ai-impact-hour-for-nonprofits

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This week Carolyn Woodard covers how to get AI literate, moving from the big-picture policy questions she's been focused on lately back to a practical roundup: how do you and your staff build AI literacy, and do you need a certificate to prove it?

She starts with free and low-cost nonprofit-specific options: PoliSync's four-module Certificate in Applied AI for Social Good, and Tim Lockie's hands-on AI for Anyone course through The Human Stack ($99). She also points to more general platforms like LinkedIn Learning, plus certifications straight from the source: Anthropic's free AI Fluency for Nonprofits course and paid Claude Certified Associate exam, Microsoft's AI Business Professional Certificate for Copilot users, and Google's Gemini certifications (for general knowledge, no previous experience necessary.) For a deeper resource, she recommends Cheryl Contee's book AI for Nonprofits and its companion AI4NP.org knowledge hub.

Carolyn's take: if you like structured learning and taking a class, or need a credential for a job or your own development plan, get one; if you're a self-directed learner already experimenting hands-on, you can decide if you need that credential too. 

Either way, AI literacy is what lets you and your organization make informed, values-driven decisions about how, or whether, to use these tools. She closes on a bright note: data center moratoriums are gaining momentum in cities and counties nationwide, proof that community advocacy is having a real effect.

This episode covers:

• Free and low-cost AI literacy courses for nonprofit staff.
• Certification options straight from Anthropic, Microsoft, and Google for teams already using Claude, Copilot, or Gemini.
• How to decide whether you actually need a certificate, based on your learning style and goals.
• A recommended book and knowledge hub for going deeper on AI at nonprofits.

Resources Mentioned:

• Certificate in Applied AI for Social Good – PoliSync – https://www.polisync.org/ai-certificate
• AI for Anyone – The Human Stack – https://thehumanstack.com/academy/aiforanyone
• AI for Nonprofits Cohort (currently closed, see AI4NP.org below) – NTEN – https://www.nten.org/learn/nonprofit-tech-readiness/ai-for-nonprofits
• Career Essentials in Generative AI – LinkedIn Learning / LinkedIn for Nonprofit https://www.linkedin.com/learning/showcase/artificial-intelligence-22747885
• Udemy Nonprofit Plan FAQ – Udemy Business – https://business-support.udemy.com/hc/en-us/articles/115016125628-Nonprofit-Plan-FAQ
• AI Fluency for Nonprofits – Anthropic Academy – https://anthropic.skilljar.com/ai-fluency-for-nonprofits
• Claude Certification Program – Anthropic / Pearson VUE – https://www.pearsonvue.com/us/en/anthropic.html
• AI Business Professional Certificate – Microsoft Learn – https://learn.microsoft.com/en-us/credentials/certifications/ai-business-professional/
• Google AI Professional Certification - Google - https://grow.google/enroll-certificates/ai-professional-certificate-mid/
• Gemini Certifications – Google for Education – https://edu.google.com/intl/ALL_us/learning-center/certifications/
• AI for Nonprofits (book and knowledge hub) – AI4NP.org – https://www.ai4np.org/about
• Data Center Reporting Tracker – Erin Brockovich – https://www.brockovichdatacenter.com

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In Part 2 of the AI Maturity Model for Nonprofits webinar, Carolyn Woodard and Mimi Yeh, Engagement Director at PTKO, and George Danilovics, VP of Technology at AHIP, pick up where Part 1 left off, moving from the framework itself to the harder question of what it takes to make AI adoption become quiet, boring, and everywhere.

Mimi and George walk through what it looks like when AI stops being an initiative and becomes infrastructure, pointing to the moment when people stop announcing they used it, the way no one says "I used Outlook to send this email." The session closes with a candid Q&A on tool volatility, vendor risk, and how to address genuine ethical concerns about AI when your colleagues or community have serious reservations.

Haven't listened to Part 1 yet? Find it in your podcast feed.

This episode covers:

• Why you should map each team separately against the five maturity stages rather than assigning your organization a single score, and how that map becomes a diagnostic you can actually act on.
• Why AI competency training deserves the same recurring, role-based architecture as security awareness training, not a one-time brown bag.
• Action items you can start this week and this quarter to move one team forward one stage at a time.
• How to think about vendor risk and tool volatility when planning for long-term AI integration, and why documenting your strategy matters more than committing to any one tool, and lets you move between vendors more easily down the road.
• Practical guidance on addressing ethical and social concerns about AI, including when those conversations belong at the board level.

Resources Mentioned:

• AI Maturity Model for Nonprofits Webinar – Community IT Innovators – https://communityit.com/webinar-ai-maturity-model-for-nonprofits/?utm_source=podcast&utm_medium=referral&utm_campaign=friday-tech-topics
• AI Journey Guide and Supplemental Resources – PTKO – https://ptko.io/ai-toolkit/
• Using AI to Build a Data Lake for Nonprofits Webinar (August 19) – Community IT Innovators – https://communityit.com/webinar-ai-in-practice-for-nonprofits/?utm_source=podcast&utm_medium=referral&utm_campaign=friday-tech-topics
• Nonprofit IT Management Community – Reddit – https://www.reddit.com/r/nonprofitITmanagement

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Carolyn Woodard covers a growing counter-movement to concentrated AI power  and what it means for nonprofits thinking about data sovereignty, open-source models, and their own agency in a moment that can feel overwhelming.

Mozilla's recent State of Open Source AI Report frames this shift as a "Rebel Alliance" against winner-take-all AI development. Mozilla is deploying $1.4 billion to seed an open, trustworthy AI ecosystem, joined by more than 55 organizations. The report makes the case that open-source models are closing the capability gap with closed commercial systems, and that communities, not just corporations, can own and control their AI.

Carolyn also introduces Current AI, a nonprofit backed by the Ford Foundation, MacArthur Foundation, and the French government, which is building what it calls a worldwide web of AI: free, public, and available to anyone the way the early internet was. One example: an offline device running AI in 22 Indian languages, built so communities own their data entirely. A Current AI grantee in Brazil is doing similar work with indigenous Amazon communities.

This episode covers:

• Why Mozilla's open-source AI report matters for nonprofits skeptical of locking into commercial platforms with opaque pricing and data practices.
• How indigenous and Global South communities are leading on data sovereignty, and what that model could mean for mission-driven organizations here.
• The case for staying informed even if you're not ready to act: understanding the landscape is itself a form of agency.
• One for-profit alternative worth knowing: Change Agent AI, built by, for, and with the social sector, on its own infrastructure without big tech servers, currently $25 per seat.

Resources Mentioned:

• State of Open Source AI Report – Mozilla – https://stateofopensource.ai
• Current AI – https://www.currentai.org/
• Nonprofit Current AI Is Racing to Build the World Wide Web of AI – TechCrunch – https://techcrunch.com/2026/07/19/nonprofit-current-ai-is-racing-to-build-the-world-wide-web-of-ai-free-for-all/
• Conference Spotlight: Data Sovereignty and the Ethics of AI – Vimeo – https://vimeo.com/1200022928/dce5a0cd1e
• NCAI Tribal AI Governance Briefing – National Congress of American Indians – https://hubs.la/Q04pD9650
• Change Agent AI – https://thechange.ai
• Generative AI Is an Engineering Disaster – The Atlantic (paywalled) – https://www.theatlantic.com/technology/2026/07/generative-ai-engineering-disaster/687901/

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In the first part of this two-part conversation, Carolyn Woodard and Mimi Yeh, Engagement Director at PTKO, and George Danilovics, Vice President of Information Technology at AHIP, walk through an AI maturity model designed to help nonprofits move from pilots and experiments to AI that is genuinely embedded in how the organization works: quiet, boring, and everywhere.

The conversation opens with a striking data point: 80% of nonprofits are already using AI in some form, yet 90% of nonprofit professionals still feel unprepared to fully leverage it. 

Mimi and George use a five-stage maturity model that moves from ad hoc, experimental, systematic, strategic, and pioneering - to help organizations find where they are now and what intentional progress looks like. The heart of the discussion is the systematic stage, where AI stops being someone else's project and starts becoming part of the organizational DNA. As George puts it, the destination is a world where AI is as unremarkable as email.

This episode covers:

• The five stages of AI maturity and how to identify where your nonprofit currently stands.
• Why the experimental stage is necessary but not the destination, and what it takes to move past it.
• What the systematic stage looks like in practice: defined goals, shared prompt libraries, documented best practices, and governance that evolves alongside your AI use.
• How strategic AI adoption shifts the question from what tool should we use to how should we organize ourselves to get the most value.
• Why reaching the pioneering stage is not the goal for most nonprofits, and why that is perfectly fine.

Resources Mentioned

• PTKO
• AHIP
• Mission-Aligned AI Adoption Model – Community IT Innovators
• Full Webinar: AI Maturity Model for Nonprofits – Community IT Innovators
• Nonprofit IT Management Community – Reddit

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Carolyn Woodard covers a cultural moment that's been building quietly, resistance to AI among workers, young people, and nonprofits, and connects it to a research framework for thinking honestly about AI's real environmental costs and benefits. Both threads come back to the same core question: who benefits from AI, and on what terms?

This episode also introduces a three-lens approach to help nonprofits think through the environmental impact of their own AI use, and suggests why "I'm just against AI" may be a values signal worth listening to rather than a training problem to fix.

This episode covers:

• The Summer of Ludd, an 8-day festival in New York City, and what the original Luddite movement was actually about: skilled workers organizing against technology being used to enrich owners at workers' expense.
• Why some nonprofit staff, especially younger workers, are pushing back on AI, and why it's worth asking what's behind that resistance before trying to fix it.
• Researcher Jennifer Turliuk's net climate impact framework, and her core observation: AI harms are measurable now, but most benefits are still speculative. Including as full a picture of the cons and pros will help organizations make thoughtful AI use decisions.
• Three lenses for evaluating your own AI use: what you're asking AI to do, where you are, and how you will benefit from using the AI.
• DC Public Library's free in-person "AI & Us" series focusing on "invisible" communities and AI.

Resources Mentioned:

• Summer of Ludd — Quartz — https://qz.com/anti-tech-movement-ai-offline-rebellion
• Luddite as political insult — NPR — https://www.npr.org/2026/06/19/nx-s1-5853589/luddite-meaning-history-ai
• Blood in the Machine — Brian Merchant — https://www.hachettebookgroup.com/titles/brian-merchant/blood-in-the-machine/9780316487740/ or at your library or local bookstore!
• Blood in the Machine Substack — Brian Merchant — https://www.bloodinthemachine.com
• AI & Us series — DC Public Library — https://dclibrary.libnet.info/event/16823630
• Responding to the Climate Impact of Generative AI — MIT Sustainability — https://sustainability.mit.edu/article/responding-climate-impact-generative-ai
• Harnessing the Power of AI to Accelerate Climate Solutions — MIT Sloan — https://mitsloan.mit.edu/centers-initiatives/sustainability-initiative/harnessing-power-ai-to-accelerate-climate-solutions
• Sustainable AI cohort — Jennifer Turliuk / Maven — 10% off discount with code NONPROFIT. Here is a direct link: https://maven.com/jennifer-turliuk/sustainableai?promoCode=NONPROFIT
• AI Acceptable Use Policy Template — Community IT Innovators — https://communityit.com/template-acceptable-use-of-ai-tools-in-the-nonprofit-workplace/
• Webinar: AI Maturity Model for Nonprofits — Community IT Innovators — https://communityit.com/webinar-ai-maturity-model-for-nonprofits/

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Carolyn Woodard explores voice AI in the social services sector with Chip Kennedy, founder and CEO of CivicReach, a technology company building AI-powered communication tools for nonprofits and government agencies delivering human services. Chip brings a rare dual perspective: years as a technologist and startup founder alongside his role and experience running a nonprofit serving families experiencing homelessness.

When people we serve need information, how can we get it to them? When our nonprofits free up employee time by using technology - in this case Voice AI to answer simple questions in incoming calls - what else can those staff members do with that time? Can emerging technology help staff up government agencies and nonprofits who are chronically understaffed and under resourced, without losing the trust of the communities they care about? 

The conversation digs into how voice AI is helping under-resourced social services organizations close the gap between people asking for help and the staff trying to reach them. Chip is candid that voice AI is not the right fit for every organization, and he shares how to evaluate whether it is right for yours. 

He also makes a compelling case that AI-driven phone intake is not a job displacement risk in human services – a sector so chronically understaffed that organizations are more likely to redeploy freed-up staff capacity than lose positions.

Carolyn and Chip discuss:

• Why human services is one sector where job displacement fears around AI largely don't apply – and what freed-up staff capacity actually looks like in practice.
• How to evaluate whether voice AI is a good fit for your organization before committing to a vendor. What are the questions to ask about their business model, their data policy, and their understanding of your nonprofit mission.
• The value of running a structured technology pilot, why more nonprofits should be asking vendors for one, and how to ask.
• How to build internal champions and skeptics into your pilot team so you get honest feedback at the end.
• Three questions every nonprofit should ask any AI vendor: where does your data go, how will our organization have to change, and how do you plan to stay sustainable?

Resources Mentioned:

• CivicReach – https://civicreach.ai

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