AI For The People investigates how public systems really work. From immigration enforcement to the fine print of legislation.
Each project uses AI tools to unpack hidden complexity and make power more visible to the public.
We are analyzing official deportation records (I-213 forms) to expose the inner workings of the U.S. immigration enforcement system. We leverage cutting-edge AI language models to perform a qualitative analysis at a scale that would be impossible for human researchers alone. This allows us to identify subtle patterns in how removals are justified, what language is used, and which communities are disproportionately impacted.
Our goal is to make immigration enforcement data legible to the public—especially to the communities it affects most.
Is the U.S. tax system truly progressive? While federal income tax is designed to be, that's only a fraction of the story. Once payroll, sales, and state taxes are factored in, the picture changes dramatically, shifting the load onto low and middle-income families. We use AI to process and simplify dense economic data and legislative text.
Our current investigations are just the beginning. We are constantly researching the complex systems we all operate in, identifying areas where AI-powered analysis could shed light on their true impact.
Below are some of the critical systems we are currently considering for future projects. We haven't committed to any of these yet—our direction will be guided by data availability, potential for impact, and public input.
Legislative Transparency
Corporate Tax Avoidance
Surveillance & Predictive Policing
FOIA Process Mapping
Market Manipulation
Prosecutorial Discretion
Government Contracting
Your perspective is invaluable. Which of these issues impacts you the most? Do you have a suggestion for another topic?
Let us know: aiforthepeopleus@gmail.com
Technology is never neutral. We are committed to using AI ethically and transparently. Our work is guided by these core policies:
Human-Led, AI-Powered: We use AI as a tool to analyze data at scale, but every finding is rigorously vetted and approved by our human researchers. We are accountable for our work, not the algorithm.
Commitment to Transparency: We are open about our methods. We acknowledge the potential for bias in any analysis and are clear about the limitations of our datasets.
Data with Dignity: We believe in protecting privacy. When our work involves data about people, we are committed to anonymizing it and will never use our findings to target individuals.