AI-generated visual disinformation and digital equity: an intersectional analysis of algorithmic vulnerabilities among marginalised communities

Abstract

The proliferation of artificial intelligence (AI) technologies has fundamentally transformed the landscape of visual disinformation, creating novel challenges for digital equity and social justice. This mini review examines how AI-generated and AI-amplified visual content disproportionately impacts marginalised communities through intersecting vulnerabilities related to race, ethnicity, socioeconomic status, geographic location, and digital literacy. Drawing on intersectional theory and social identity frameworks, we synthesise recent empirical evidence demonstrating that algorithmic systems systematically disadvantage specific demographic groups through biased content generation, inequitable distribution mechanisms, and differential access to verification tools. Our analysis reveals that communities of colour, low-income populations, and individuals in the Global South face compounded risks from AI-driven disinformation ecosystems. We identify critical gaps in current interventions and propose equity-centred approaches to address these disparities, including algorithmic accountability frameworks, culturally responsive media literacy programs, and inclusive platform design. This review contributes to emerging scholarship at the intersection of AI ethics, communication studies, and social equity by highlighting how technological systems reproduce and amplify existing societal inequalities.

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