Article 7 — The Norms We Choose
There’s a word for the second-to-last thing.
Penultimate.
This is it.
Next week I’ll be in St. Louis at PEAK2026 — and I’ll close this series with what I find there.
But before we get to the ending, there’s something we still need to name.
There’s a scene in The Matrix where Morpheus offers Neo a choice.
Red pill or blue pill.
See the system clearly — or go back to sleep.
Neo, played by Keanu Reeves in his finest moment of bewildered humanity, takes the red pill.
And the world he thought he lived in dissolves.
I think about that scene a lot right now.
Not because AI is science fiction.
Because it isn’t.
The World We Are Actually In
Let’s name it plainly.
We are not navigating AI in a neutral moment.
We are navigating AI during a democratic backslide. A surveillance infrastructure expanding faster than the laws designed to constrain it. A geopolitical landscape fracturing under authoritarian ambition and climate pressure. And a late-stage capitalist system that has already demonstrated — with lumber, with coal, with water, with data — that it will extract from communities before it protects them.
I’ve written about this before. The seeds of surveillance capitalism are not fictional. Companies harvest personal data to predict and influence behavior. Governments use mass collection for control. The line between corporate power and state power is blurring in ways that should alarm every one.
Into that world: AI.
Not as a neutral tool.
As accelerant.
The Train We Can’t Look Away From
“AI is inevitable.”
The train is leaving the station. Get on board or get left behind.
But here’s what Anil Dash said on stage in Detroit that I haven’t been able to shake:
Power is not a pyramid.
It’s a circle.
And everyone has it.
“Inevitable” is often how systems make us feel powerless.
AI may be arriving fast.
But which technologies we use, how we use them, and who they serve — those are not inevitable.
Those are choices.
And right now, those choices are still ours to make.
What Is Actually at Stake
Across the country, nonprofits defending democracy, racial justice, and civil rights are under siege.
The authoritarian framework is not abstract. It is active.
And AI does not arrive into that landscape as a helpful assistant.
It arrives as infrastructure.
Already embedded in hiring decisions. Lending algorithms. Healthcare systems. Grant assessment tools. Predictive policing networks.
In 2016, more than 117 million U.S. adults — roughly half the adult population — were included in law enforcement facial recognition databases, systems that have been shown to perform less accurately on Black faces and other marginalized groups.1
Healthcare algorithms have been documented recommending additional care for white patients while passing over equally sick Black patients.
Nonprofit leaders are already reverse-engineering the systems being used to evaluate them — not to game them, but to understand how they are being judged.2
That is not innovation.
That is opacity.
And opacity in a surveillance state is not a minor inconvenience.
It is a threat.
What We Already Know
We don’t have to guess what happens when powerful systems are built without accountability.
We do not have a strong track record in capitalist America of protecting the margins when profit and power are at stake.
Not with lumber. Not with coal. Not with water. Not with data.
Barbara Kingsolver’s Demon Copperhead shows how entire regions get hollowed out by extraction dressed as progress. Walter Tevis’ Mockingbird warns of a future where efficiency rules and people forget how to think for themselves.
Progress without protection corrodes from within.
AI will not create inequity in this sector.
It will scale what already exists.
This is not a technology question.
It is a power question.
Where This Work Started For Me
I learned this early.
As a young grants manager on the audit committee at Philanthropy New York, I was often the least senior person in the room.
The committee’s job was simple and clarifying: shine light in dark corners.
What I found there surprised me.
Risk wasn’t always where people thought it was.
It lived in the 990, if you knew how to read it. In the narrative sections most people skimmed. In policies that hadn’t been touched in a decade.
Numbers tell stories. Policies reveal priorities. And if you read closely enough, you can see exactly who decisions were made for — and who they weren’t.
I was young enough to still be asking first questions.
Why does this work this way? Who decided? What are we not looking at?
That is the committee’s job.
It is also every board’s job right now — whether they know it or not.
AI is moving through vendor contracts, staff workflows, and operational decisions across the sector.
Most boards are not in that conversation.
The dark corners are getting darker.
The people designed to shine light in them need to know where to look.
The Window We Are In
It will not last.
We have a short window to define what the norms are.
They will evolve. They will be contested.
But right now — we get the first pass.
And that is a powerful proposition for a sector built on values.
Because once norms are set, they are hard to unwind.
Once infrastructure is built, it shapes everything that runs on top of it.
The question is not whether philanthropy and nonprofits will be shaped by AI.
They already are.
The question is whether they will shape it in return.
Four Ways to Lead in This Moment
Across my work with fellows, funders, and nonprofit leaders, I’ve been using four metaphors to make sense of what AI actually is — and what leadership it demands.
AI as a mirror. It reflects back our systems, assumptions, and inequities. What you see tells you something true about what you built before it arrived.
AI as a bicycle. It accelerates what you are already doing — for better or worse. Sloppy processes move faster. Strong ones scale. Bias travels further.
AI as an intern. It can support the work. But it requires supervision and accountability. Left alone, it makes confident mistakes no one catches.
AI as a bridge. At its best, it connects systems and people in ways that expand access and reduce burden. That version requires intentional design.
These are not just metaphors.
They are leadership choices.
The Choice in Front of Philanthropy
Philanthropy still has the option to step back.
Nonprofits do not.
They are already inside the system. Inside the pressure. Inside the expectations.
Stepping back is not neutrality.
It is an abdication of responsibility.
Philanthropy can observe. Delay. Wait for clearer answers.
Or it can step forward.
Fund the infrastructure. Support governance. Reduce burden. Share learning. Stand with grantees who are being watched.
The sector that exists to protect communities is the same sector that can shape how AI moves through them. That is not a small thing.
What Leadership Looks Like Now
Taking the red pill doesn’t mean despair.
It means clarity.
Seeing the system as it is — and choosing, deliberately, how to move inside it.
Good leadership in this moment does not look like certainty.
It looks like listening. Learning. Trying. Building.
And doing it in public.
It looks like aligning technology with mission. Stewarding risk with care. Staying human — relational, reflective, and accountable — in a moment when systems are being designed to replace all three.
What Comes Next
This spring I’m convening a small cohort for COOs and senior operational leaders in nonprofit and philanthropic organizations, presented in collaboration with Philanthropy New York and Community Resource Exchange.
Not to deliver answers.
To build the room where the right people establish shared norms together, across the power divide, before someone else establishes them for us.
Who holds decision-making power over these systems. Who is included in the design. Who is listened to when harm occurs.
Seats are filling. The cohort is capped at 8 leaders and opens May 5, 2026.
Email me at rachel@fullcircleimpact.org for more information.
Closing
If we are predictable, the systems win.
They will follow our patterns, reinforce our assumptions, and scale what we have already built.
That is how inequity becomes infrastructure.
That is how surveillance becomes normal.
That is how the train wreck we can’t look away from becomes the world we live in.
But if we stay human — relational, reflective, and accountable — we create space to interrupt those patterns.
To question what is being optimized. To decide what actually matters. To build systems that reflect our values, not just our habits.
Neo took the red pill.
He didn’t do it alone.
He did it inside a network of people who had already chosen to see clearly — and were building something different in the spaces the system hadn’t reached yet.
That network exists in this sector.
It is you.
The future of AI in this work is not prewritten.
It will be shaped by the decisions we make next.
Next week: reporting out from PEAK2026 in St. Louis. The final piece in this series.
Resources
Garvie, Clare; Bedoya, Alvaro; Frankle, Jonathan. The Perpetual Line-Up: Unregulated Police Face Recognition in America. Georgetown Law Center on Privacy & Technology, 2016. https://www.perpetuallineup.org
• Shoshana Zuboff
The Age of Surveillance Capitalism
• Dr. Joy Buolamwini — Algorithmic Justice League
https://www.ajl.org
• Coded Bias (documentary)
https://www.netflix.com/title/81328723
• Amy Edmondson — Psychological Safety
https://www.hbs.edu/faculty/Pages/profile.aspx?facId=6451
• AI Now Institute — AI Governance & Harms Research
https://ainowinstitute.org
• Barry Johnson — Polarity Thinking
https://www.polaritypartnerships.com
• PEAK Grantmaking
https://www.peakgrantmaking.org
• Technology Association of Grantmakers — AI Risk Framing (Slides 22–23)
Many of these databases were built from driver’s license and other government records, meaning millions of people were included without consent or suspicion of wrongdoing.