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Toward Inclusive Emergency Alerting: A Conceptual Framework for Accessibility and Equity in AI-Driven Public Safety Systems
Subject area: Science,Engineering and Technology · Area of research: AI-Driven Public Safety Systems
Abstract
Emergency alerting in the United States has historically assumed a recipient who reads English, perceives both sound and image, processes dense information under stress, owns a capable connected device, and trusts the issuing authority. Tens of millions of residents fall outside that profile, and they are disproportionately exposed to preventable harm. Artificial intelligence (AI) is increasingly proposed to close the gap, but technology does not produce equity on its own; deployed uncritically, AI can entrench exclusion behind the authority of automation. This article develops a conceptual framework that treats accessibility and equity as first-order design principles rather than accommodations added to a finished system. Grounded in universal design, the social model of disability, intersectionality, and a health-equity and capability orientation, the framework specifies six dimensions an AI-driven alerting system must satisfy to reach every resident: multimodal delivery; linguistic inclusion; cognitive and literacy accessibility; digital equity and reach; algorithmic fairness and anti-discrimination governance; and participatory design and community trust. Each dimension is defined, theorized, and connected to design practice. The framework is translated into six design principles and a maturity-based evaluation model that assesses systems dimension by dimension against an outcome standard drawn from the capability approach: not that alerts are sent to all, but that all residents can genuinely receive, understand, and act on them. Applied to the U.S. alerting landscape, the framework functions as both diagnosis and design specification, and it frames an agenda for research, governance, and implementation centered on the populations current systems most often fail.
Keywords
accessibility, equity, emergency alerts, universal design, disability, intersectionality, artificial intelligence, public safety, inclusive design
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How to cite this paper
@article{1722366,
author = {Gbemisola Simbiat Odejide},
title = {Toward Inclusive Emergency Alerting: A Conceptual Framework for Accessibility and Equity in AI-Driven Public Safety Systems},
journal = {Iconic Research And Engineering Journals},
year = {2025},
volume = {9},
number = {5},
pages = {2880-2912},
issn = {2456-8880},
url = {https://www.irejournals.com/formatedpaper/1722366.pdf},
abstract = {Emergency alerting in the United States has historically assumed a recipient who reads English, perceives both sound and image, processes dense information under stress, owns a capable connected device, and trusts the issuing authority. Tens of millions of residents fall outside that profile, and they are disproportionately exposed to preventable harm. Artificial intelligence (AI) is increasingly proposed to close the gap, but technology does not produce equity on its own; deployed uncritically, AI can entrench exclusion behind the authority of automation. This article develops a conceptual framework that treats accessibility and equity as first-order design principles rather than accommodations added to a finished system. Grounded in universal design, the social model of disability, intersectionality, and a health-equity and capability orientation, the framework specifies six dimensions an AI-driven alerting system must satisfy to reach every resident: multimodal delivery; linguistic inclusion; cognitive and literacy accessibility; digital equity and reach; algorithmic fairness and anti-discrimination governance; and participatory design and community trust. Each dimension is defined, theorized, and connected to design practice. The framework is translated into six design principles and a maturity-based evaluation model that assesses systems dimension by dimension against an outcome standard drawn from the capability approach: not that alerts are sent to all, but that all residents can genuinely receive, understand, and act on them. Applied to the U.S. alerting landscape, the framework functions as both diagnosis and design specification, and it frames an agenda for research, governance, and implementation centered on the populations current systems most often fail.},
keywords = {accessibility, equity, emergency alerts, universal design, disability, intersectionality, artificial intelligence, public safety, inclusive design},
month = {November},
doi = {https://doi.org/10.64388/IREV9I5-1722366}
}