AI for Skills-First Hiring: Removing Barriers Hidden in Public-Sector Rules — Citizens Foundation

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Blog（https://citizens.is/blog/） · June 13, 2026 · Artificial Intelligence, Policy Synth, Economic Opportunity

AI for Skills-First Hiring: Removing Barriers Hidden in Public-Sector Rules

The last story in this series showed how Policy Synth can help turn public input into policy proposals. This one shows the next step: using AI to help governments implement change inside the rules, job descriptions, and legal language that shape real decisions.

The skills-first hiring project is led by Northeastern University's Burnes Center for Social Change（https://burnes.northeastern.edu/）. Citizens Foundation has partnered with the Burnes Center from the start, helping co-fund and develop the Policy Synth work behind it. The goal is practical: help states find and remove unnecessary degree requirements that block qualified workers from public-sector jobs.

The project is led by Seth Harris（https://burnes.northeastern.edu/people/seth-harris/）, Distinguished Professor of Practice at Northeastern University and Senior Fellow at the Burnes Center. Harris brings deep labor and workforce policy experience, including service as Acting U.S. Secretary of Labor and Deputy U.S. Secretary of Labor. Under his leadership, the project focuses on a concrete problem: many government hiring barriers are not only in policy statements. They are hidden across thousands of job descriptions, civil-service rules, statutes, regulations, and licensing requirements.

That is where Policy Synth becomes useful.

The Barrier Is Often in the Details

Skills-first hiring starts from a simple idea: public employers should focus on the skills needed to do the job, not default to college degree requirements when a degree is not necessary. That matters because unnecessary degree requirements exclude many capable workers, especially people from lower-income backgrounds and communities that have had less access to higher education.

But changing the policy is only the first step. A governor, agency, or civil service commission can commit to skills-first hiring and still run into hundreds of buried constraints. A job posting may say a degree is required. A classification rule may imply it. A licensing requirement may be relevant for some roles but not others. A statute may appear to create a barrier, but only after legal review can the state know whether it actually does.

The Burnes Center's skills-first workforce hiring initiative（https://burnes.northeastern.edu/skills-first-workforce-hiring-creating-more-equitable-and-inclusive-state-employment-opportunities-using-ai/） addresses that implementation problem directly. Working with New Jersey's Civil Service Commission, the project uses Policy Synth to analyze more than 3,000 job descriptions for readability, degree requirements, and legal barriers to skills-based hiring.

Reading Thousands of Job Descriptions

Policy Synth agents help review job descriptions at a scale that would be difficult for a human team to sustain manually. The system identifies whether a posting requires a college degree, quotes the relevant evidence, distinguishes mandatory language from softer preferences, checks for professional license requirements, and flags barriers that may exclude otherwise qualified applicants without degrees.

That analysis is not the end of the process. It creates structured evidence for human review.

A companion rewriter agent then drafts skills-first versions of problematic job descriptions.