Enabling Data-Driven Policymaking Using Broadband-Plan Querying Tool (BQT+)

2025-11-08

AI Summary

Current broadband coverage and affordability data rely heavily on self-reported information from Internet Service Providers (ISPs), leading to systematic overestimation of coverage and speeds and underestimation of pricing—thereby misallocating policy funding and exacerbating the digital divide. To address this, we propose BQT+—an AI agent platform that introduces browser-based automation for address-level data collection. Our AI agents emulate real user interactions by autonomously navigating ISP websites to extract structured, address-specific data on service availability, downstream/upstream speeds, and monthly pricing. This approach overcomes the limitations of passive reporting by enabling high-frequency, fine-grained, and verifiable empirical measurement. Deployed in support of multiple policy evaluations, BQT+ has generated independent, transparent, and reproducible broadband coverage maps, speed-tier classifications, and affordability analyses for the U.S. $42.45 billion Broadband Equity, Access, and Deployment (BEAD) Program—significantly strengthening the evidentiary foundation and equity of digital infrastructure decision-making.

Technology Category

• Philosophy and Ethics of AI: Bias, Fairness & Equity
• Humans and AI: Planning and Decision Support for Human-Machine Teams
• Application Domains: Internet of Things, Sensor Networks & Smart Cities

Application Category

• Responsible Web: Data and user privacy-enhancing technologies for the Web
• Economics, Online Markets and Human Computation: Data quality aspects of human-annotated datasets
• Systems and Infrastructure for Web, Mobile and WoT: Web performance, measurement, and characterization

Abstract

Poor broadband access undermines civic and economic life, a challenge exacerbated by the fact that millions of Americans still lack reliable high-speed connectivity. Federal broadband funding initiatives aim to address these gaps, but their success depends on accurate availability and affordability data. Existing data, often based on self-reported ISP information, can overstate coverage and speeds, risking misallocation of funds and leaving unserved communities behind. We present BQT+, an AI-agent data collection platform that queries ISP web interfaces by inputting residential street addresses and extracting data on service availability, quality, and pricing. BQT+ has been used in policy evaluation studies, including an independent assessment of broadband availability, speed tiers, and affordability in areas targeted by the $42.45 billion BEAD program.

Problem

• Millions lack reliable broadband access despite federal funding initiatives
• Inaccurate ISP-reported data risks misallocating funds to unserved communities
• Existing broadband data overstates coverage and speeds for policymaking

Innovation

• AI-agent queries ISP web interfaces for data
• Extracts service availability, quality, and pricing
• Inputs residential addresses to collect broadband information