Can We Reclaim Our Humanity With AI?
AI isn't the question. We are.
I didn’t expect AI to change my work as much as it has.
At first, it was a curiosity — a tool I used to brainstorm or speed up formatting. But over time, I've integrated it deeper into my process. I'm building a small consulting firm, Anthralytic, focused on strategy, evaluation, and systems-level impact for social-impact organizations. I don’t have a dev team. I’m not backed by venture capital. Yet in the past year, AI has reshaped how I work so profoundly that I’ve reimagined my entire business model.
AI is helping me build accessible tools for social impact-driven organizations — from drafting strategies and cleaning messy datasets to generating visuals, building apps, and synthesizing research. These are tools that used to require a developer or a full team.
It’s a strange and humbling position to be in. On one hand, these AI platforms are allowing me to fulfill my mission — making strategy more accessible to small, social-impact organizations. On the other, I have to confront the paradox of this progress: what happens to the jobs, including consultants like me, that this technology can replace through efficiency?
For many careers, this isn't a theoretical dilemma; it's a present reality. A recent Goldman Sachs report estimated that generative AI could automate the equivalent of 300 million full-time jobs1. The warnings from top economists, technologists, and policy thinkers are growing louder and more frequent. The CEO of Anthropic, a leading AI lab, recently stated they expect AI to replace a large fraction of cognitive labor2. MIT economist Daron Acemoglu has warned that without proactive policy, AI could “exacerbate inequality and create a class of displaced workers.”3
The companies and individuals who learn how to harness it will be the winners. What will happen to the rest of us?
History Rhymes
This isn't the first time new tools have upended how people live and work.
Here’s an example of how history rhymes: In the early 1800s, the Luddites — skilled English textile workers — protested against the mechanized looms that were replacing their craft. Contrary to the myth, they weren't anti-technology; they were anti-exploitation. They destroyed machines not because they hated innovation, but because factory owners were using that innovation to devalue labor, drive down wages, and hoard profits in a way that threatened their livelihoods and communities.
The same pattern has repeated through the Industrial Revolution, the rise of the assembly line, and the introduction of personal computers. Each wave of technology brought progress, but its gains were only shared when paired with deliberate choices about equity, ownership, and protection.
Today, AI is that wave. And the stakes are even higher.
So what do we do now that AI is already eliminating jobs?
The ship has left the harbor. There's no point in trying to steer back to an outdated model — but we can correct our course and sail with intention to a new destination.
We must shape our world in response to this technology before it reshapes our society in ways we can’t undo.
Reclaiming Our Time, Reclaiming Our Humanity
Perhaps the biggest challenge is cultural, not economic. Americans have a deep attachment to work as a source of moral virtue and meaning.
"What do you do?" is often the first question we ask a stranger. I’ve stopped asking this question because I believe it's fundamentally unfair. Not everyone defines themselves by their job; some may dislike their work, others may have recently lost it, and many care more about other parts of their lives. We need to rethink how we value a human being — shifting from what they produce or consume to recognizing their intrinsic worth simply for being human.
What if we reshape the purpose of this great disruption not to make things faster, but to make us more human?
A couple of years ago, I asked my children to describe me in one word. Their answer was a gut punch: "busy."
Here’s a hard truth: a lot of jobs are padded with busywork. We spend hours replying to emails that don’t matter, sitting in meetings that go nowhere, and managing systems that only exist to justify themselves — and our roles. If we stop clinging to tasks just because they’re “ours,” we might finally open up time for the things that actually make our human lives rich.
What if we stopped pretending that our jobs need us every minute of every day?
What if that wasn’t the measure of our worth?
What if we don’t need to participate in the rat race?
What if we could let the robots do what they can do better than us so we can do what they can’t — enjoy life?
Freed from the tyranny of tasks that can be automated, we could finally have time.
Time to have long, unhurried dinners with our families, filled with laughter instead of deadlines. Time to show up for our neighbors, to coach the local kids’ team, to learn the name of the person who makes our morning coffee. Time for the messy, joyful act of creation — to plant a garden, to write the novel we’ve always talked about, to pick up a guitar for the first time in twenty years. Time to make community. Time to really feel alive.
This isn’t about idleness; it’s about the essential work of building a life.
It is the work of connection, of care, of curiosity.
It is the work of being human.
But this more human future is not a guarantee.
It is a choice.
Without deliberate action, the productivity gains of this new age will flow to the few, leaving behind not just economic insecurity, but a crisis of purpose for the many.
A Potential Solution: Universal Basic Income
The question is — how will we earn our livelihoods?
This is where the idea of a Universal Basic Income (UBI) comes in.
The concept is simple: every adult citizen receives a regular, unconditional payment — a guaranteed income floor just for being alive. It won’t replace all income immediately, but it provides a foundation of economic security that recognizes each person’s intrinsic worth, independent of their job.
UBI isn’t new. Thinkers from Thomas Paine to Martin Luther King Jr. have championed versions of it. In his 1967 book Where Do We Go From Here: Chaos or Community?, Dr. King wrote:
“The time has come for us to civilize ourselves by the total, direct, and immediate abolition of poverty.”
King envisioned guaranteed income not just as policy, but as a moral necessity for justice.
UBI entered mainstream U.S. politics thanks largely to Andrew Yang, whose 2020 presidential campaign proposed a $1,000/month “Freedom Dividend” for all adults. Yang argued: “Universal basic income is not a solution in search of a problem — it’s the obvious solution that’s been in front of us for years.”4 He linked it directly to automation — warning one in three workers could lose jobs to technology within years.5
UBI is more than just policy — it can become the foundation for the future we want: the freedom for a parent to care for a sick child without fear, for new passions to become viable ventures, and for DIY creativity to flourish. That freedom respects human dignity and trust.
So the question isn’t can we afford to try it?
It’s can we afford to watch a more connected, creative future slip away?
UBI Works — But We Have to Reframe Scale Thoughtfully
This urgent context is why real-world evidence for new social policies is so crucial, and we already have promising data points:
In a randomized trial in Kenya, GiveDirectly found that basic income transfers improved food security, psychological well-being, and entrepreneurship — all without reducing labor market participation.6
In the U.S., Alaska has distributed oil dividends as a kind of mini-UBI for decades, with broad bipartisan support.7
Dozens of recent U.S. pilots — from Stockton, California,8 to Saint Paul, Minnesota9 — have echoed these findings. They consistently show that a guaranteed income improves financial stability, reduces recipients' anxiety and depression, and in many cases, enables them to find better-paying, full-time employment.
This existing evidence is encouraging. However, we must be honest about what these small, temporary programs can and cannot tell us. They don't capture all the economy-wide effects, like shifts in inflation or labor markets. Giving $500 a month to 125 families for two years is a qualitatively different experiment than giving it to 200 million adults permanently.
With this framework in mind, making a basic income politically viable requires reframing the conversation for our current context:
Change the name. Language matters. "Economic Security" or "Citizen Dividends" is more palatable than "Universal Basic Income."
Start with targeted programs. Build proof of concept with groups that have strong political support, such as a Veterans' Basic Income, Rural Economic Security grants, or Caregiver Stipends.
Emphasize choice and dignity. Frame it not as replacing work, but as providing the security for people to make better choices about work, training, and family care.
The Pragmatics of Funding and the Path Forward
To build a more human future, we have to be pragmatic. That starts by addressing the elephant in the room: cost.
Providing a meaningful benefit for every American — say, $1,000 per month — would cost around $2.5 trillion annually.10 That’s a staggering portion of the federal budget. Also, a flat national payment ignores the reality that the cost of living varies dramatically by region. A smarter approach is a Federally-Funded, Locally-Adjusted Model, where the benefit scales based on local economic conditions.
While many traditional funding proposals have serious flaws11, the principle should be simple: If AI displacement is the problem, then AI-generated wealth should be part of the solution.
The revenue must come from the technology driving the disruption — and the vast wealth it creates. Leaders from AI companies like Anthropic and OpenAI have publicly acknowledged that job losses are likely and suggested they should be taxed to fund social responses.
Let’s hold them to that.
The tech titans didn’t create AI in a vacuum. They built on systems they didn’t create with data that we all generated. An aggressive digital services tax, combined with wealth taxes on those profiting most from AI, could yield hundreds of billions in new revenue — enough to begin building a real foundation and compensate us, the creators of all of the data we generated to make training these models possible.
We don’t need to fund $2.5 trillion all at once.
We can start small — by taxing the disruption itself, tailoring benefits to local needs, and scaling as we learn.
This is why we need a graduated, data-driven approach to:
Expand current pilots to larger populations and longer timeframes
Test different funding and distribution mechanisms
Refine a locally-adjusted model for equity and efficiency
Build political momentum by proving what works
Each stage builds trust. Each success makes the next step possible.
This is how we create a system worthy of the future we’re being pulled into — not with hand-waving or idealism, but with strategy, evidence, and resolve.
What’s Your Take?
Would you support a partial, locally-adjusted basic income in your community?
What funding mechanisms seem most viable to you?
How can we build broader support for economic security policies?
Let’s have this conversation now — before the choices are made for us.
To understand why that $1,000 figure is so critical, it helps to look at what Americans actually earn. According to recent U.S. Census Bureau data, the median household income is about $74,580 before taxes, but this varies from over $90,000 in Maryland to just $52,000 in Mississippi. More importantly, the median personal income — what an individual earns — is much lower, around $40,000. For someone earning that median, a $12,000 annual basic income represents a 30% raise.
Standard proposals for funding a full UBI all have severe political or economic drawbacks. These include massive and politically toxic tax hikes on income or consumption; unsustainable deficit spending that risks inflation; eliminating existing social programs like Social Security, leaving a funding gap and removing targeted support; and taxes on automation or land value that are either insufficient or could slow innovation.