About DegreeWorth

What Is DegreeWorth?

DegreeWorth provides data-driven analysis of over 24,000 college programs across nearly 1,900 schools in the United States. For every program, we calculate a comprehensive score that reflects earnings potential, student debt levels, return on investment, and — crucially — how AI automation may reshape the career landscape for graduates.

The core question we address is simple: Given what we know about AI disruption, is this degree still worth the investment?

Each program receives a DegreeWorth Score from 0 to 100, along with detailed breakdowns of earnings, debt, AI risk exposure, and projected outcomes under three different scenarios.

Three Scenarios

We model each program under three AI disruption scenarios to reflect the range of plausible futures. Rather than making a single prediction, we show how outcomes could vary:

Data Sources

• U.S. Department of Education — College Scorecard

  Program-level earnings (1-year and 5-year post-graduation), median student debt, tuition costs, and institutional data for every Title IV institution in the country.

• Bureau of Labor Statistics (BLS)

  Occupational employment data, projected job growth rates, total annual job openings, and median wages by occupation — used to map each degree to its real-world labor market.

• OpenAI GPT Exposure Research

  Research quantifying how exposed each occupation is to large language model capabilities. We use task-level GPT exposure scores to estimate which careers face the most disruption from generative AI.

• Felten et al. — AI Occupational Exposure (AIOE)

  An independent academic measure of AI exposure by occupation, based on the overlap between AI capabilities and occupational task requirements. Provides a complementary lens to GPT-specific exposure.

Methodology

DegreeWorth uses a continuous weighting function rather than hard cutoffs to blend AI risk into program scoring. Here is how it works:

AI Risk Composite

For each program, we map its associated occupations to their GPT exposure scores and AIOE values, then compute a weighted average based on how commonly graduates enter each occupation. This gives a single AI Risk Composite score that captures overall exposure to AI disruption.

Scenario Modeling

Each scenario applies different assumptions about how AI risk translates to earnings impact. The optimistic scenario dampens the effect of AI exposure, the base case applies moderate adjustments, and the pessimistic scenario amplifies it. Earnings projections are adjusted continuously — a program with 30% AI exposure sees a proportionally different adjustment than one with 70%.

DegreeWorth Score

The final score (0–100) integrates multiple factors: raw ROI (earnings vs. debt/tuition), absolute earning power, AI risk level, job market size, and projected growth. Programs that combine strong earnings, manageable debt, and low AI risk score highest.