United States of AI Ethical Policy - Fairness at the Speed of Code: Fiscal Reform in the Age of AI

A Civic Brief from Future in Common

Part of the series: “The United States of AI: An Ethical Policy Platform for American Workers”

Suggested Price: Pay What You Can ($5+ recommended)

What This Brief Covers:

As artificial intelligence reshapes the economy, our outdated tax and fiscal systems are falling behind. Who benefits from AI-driven productivity—and who’s left out? What happens when billion-dollar AI companies rely on public infrastructure but contribute little back?

This timely civic brief makes the case for modernizing our tax system to meet the speed, scale, and inequality of the AI economy. It introduces bold, practical ideas for ensuring shared prosperity—from data dividends and robot taxes to corporate accountability and civic reinvestment.

What You’ll Learn:

• How AI is transforming value creation and disrupting traditional revenue sources

• Why our current tax system is ill-equipped for the post-labor economy

• Creative, justice-centered proposals for updating fiscal policy in an AI age

• How we can fund public goods—education, care, democracy—by ensuring tech pays its share

Who It’s For:

• Concerned voters, educators, and organizers

• Policy professionals, economists, and civic leaders

• Advocates for equity, public investment, and tax justice

• Anyone asking, “Where is all this AI money going—and who decides?”

Why It Matters:

Without reform, AI could supercharge inequality and starve our public systems. But with smart, ethical fiscal policy, we can make sure innovation fuels dignity—not austerity. This isn’t just about taxes—it’s about fairness, freedom, and the future we share.

Download includes:

PDF of the full civic brief formatted for easy sharing.

License & Use

This brief is copyrighted © 2025 by Deion Lemelle / Future in Common.

The ideas are meant to be shared, adapted, and built upon.

Please do not republish the full document without permission.

You’re welcome to cite, quote, or use the concepts with attribution.